# LLMS.txt برای وب‌سایت هوش مصنوعی تیروتیر– 2025 > این فایل LLMS.txt شامل فهرست اصلی مقالات و منابع سایت ماست. هدف آن کمک به سیستم‌های هوش مصنوعی برای کشف و درک ساختار محتوا به شکل مؤثر است. > هر آیتم شامل URL، تاریخ آخرین به‌روزرسانی و دسته‌بندی برای پردازش آسان‌تر توسط هوش مصنوعی می‌باشد. --- ## برگه‌ها - [اخبار](https://tirotir.ir/news/): 🔎 TirotirSearch جستجوی پیشرفته گوگل عبارت جستجو بازه زمانی همه۱ ساعت گذشته۲۴ ساعت گذشته۱ هفته گذشته نوع محتوا وباخبار دامنه... - [آزمون پایتون](https://tirotir.ir/%d8%a2%d8%b2%d9%85%d9%88%d9%86-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86/): نمونه سوال آزمون کلاسی پایتون ۱ آموزشگاه هوش مصنوعی ۱- نمونه سوال پایتون ۱ پاییز ۱۴۰۴ آزمون پایتون – آموزشگاه... - [دوره‌های آموزشی](https://tirotir.ir/%d8%af%d9%88%d8%b1%d9%87%d9%87%d8%a7%db%8c-%d8%a2%d9%85%d9%88%d8%b2%d8%b4%db%8c/): پایتون ۱ ICDL Web 1 - [درباره ما](https://tirotir.ir/%d8%af%d8%b1%d8%a8%d8%a7%d8%b1%d9%87-%d9%85%d8%a7/): تیروتیر — آموزش، ابزار و محتوای متن باز برای Python، هوش مصنوعی و وب آموزشگاه فنی و حرفه ای آزاد... - 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[Visual understanding: Unlocking the next frontier in AI](https://tirotir.ir/visual-understanding-unlocking-the-next-frontier-in-ai/): At the NYC AIAI Summit, Joseph Nelson, CEO & Co-Founder of Roboflow, took the stage to spotlight a critical but... - [AI-powered healthcare, with Archie Mayani [Video]](https://tirotir.ir/ai-powered-healthcare-with-archie-mayani-video/) - [How Agentic AI is transforming healthcare delivery](https://tirotir.ir/how-agentic-ai-is-transforming-healthcare-delivery/): In the Agents of Change podcast, host Anthony Witherspoon welcomes Archie Mayani, Chief Product Officer at GHX (Global Healthcare Exchange),... - [How AI is redefining cyber attack and defense strategies](https://tirotir.ir/how-ai-is-redefining-cyber-attack-and-defense-strategies/): As AI reshapes every aspect of digital infrastructure, cybersecurity has emerged as the most critical battleground where AI serves as... - [AI and the future of international student outreach](https://tirotir.ir/ai-and-the-future-of-international-student-outreach/): My daily work in the EdTech industry consists of constant back-and-forth comparison between the United Kingdom’s admissions machine and the... - [How large language models are transforming pediatric healthcare](https://tirotir.ir/how-large-language-models-are-transforming-pediatric-healthcare/): What if artificial intelligence could help us solve some of the most complex challenges in pediatric healthcare, especially when it... - [Humans in the loop: How leading companies are building practical, trustworthy AI](https://tirotir.ir/humans-in-the-loop-how-leading-companies-are-building-practical-trustworthy-ai/): At the NYC Generative AI Summit, experts from Wayfair, Morgan & Morgan, and Prolific came together to explore one of... - ["Agentic AI is here — are you ready?" With Ash Dhupar](https://tirotir.ir/agentic-ai-is-here-are-you-ready-with-ash-dhupar/) - [LLMOps in action: Streamlining the path from prototype to production](https://tirotir.ir/llmops-in-action-streamlining-the-path-from-prototype-to-production-2/): AIAInow is your chance to stream exclusive talks and presentations from our previous events, hosted by AI experts and industry... - [How to optimize LLM performance and output quality: A practical guide](https://tirotir.ir/how-to-optimize-llm-performance-and-output-quality-a-practical-guide/): Have you ever asked generative AI the same question twice – only to get two very different answers? That inconsistency... - [Human + AI: Rethinking the roles and skills of knowledge workers](https://tirotir.ir/human-ai-rethinking-the-roles-and-skills-of-knowledge-workers/): Artificial intelligence is not just another gadget; it’s already shaking up how white-collar jobs work. McKinsey calls this shift an... - [Turning structured data into ROI with genAI](https://tirotir.ir/turning-structured-data-into-roi-with-genai/): At GigaSpaces, we’ve been in the data management game for over twenty years. We specialize in mission-critical, real-time software solutions,... - [How TigerEye is redefining AI-powered business intelligence](https://tirotir.ir/how-tigereye-is-redefining-ai-powered-business-intelligence/): At the Generative AI Summit in Silicon Valley, Ralph Gootee, Co-founder of TigerEye, joined Tim Mitchell, Business Line Lead, Technology... - [Why agentic AI pilots fail and how to scale safely](https://tirotir.ir/why-agentic-ai-pilots-fail-and-how-to-scale-safely/): At the AI Accelerator Institute Summit in New York, Oren Michels, Co-founder and CEO of Barndoor AI, joined a one-on-one... - [AIAI New York, 2025](https://tirotir.ir/aiai-new-york-2025/): Catch up on every session from the AIAI New York with sessions across 3 co-located summit featuring the likes of... - [LLMOps in action: How we move GenAI from prototype to production](https://tirotir.ir/llmops-in-action-how-we-move-genai-from-prototype-to-production/): Struggling to get your GenAI prototype into production? Discover how LLMOps helps streamline deployment – fast, scalable, and reliable. - [LLMOps Virtual Summit, May 2025](https://tirotir.ir/llmops-virtual-summit-may-2025/): Catch up on every session from LLMOps Virtual Summit, with sessions from the likes of Google, Unicef, Capital One, Linkedin... - [CAP theorem in ML: Consistency vs. availability](https://tirotir.ir/cap-theorem-in-ml-consistency-vs-availability/): The CAP theorem has long been the unavoidable reality check for distributed database architects. However, as machine learning (ML) evolves... - [How to build autonomous AI agent with Google A2A protocol](https://tirotir.ir/how-to-build-autonomous-ai-agent-with-google-a2a-protocol/): Why do we need autonomous AI agents? Picture this: it’s 3 a. m. , and a customer on the other side... - [Building & securing AI agents: A tech leader crash course](https://tirotir.ir/building-securing-ai-agents-a-tech-leader-crash-course/): The AI revolution is racing beyond chatbots to autonomous agents that act, decide, and interface with internal systems. 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The rapid, uncontrolled adoption of various AI tools... - [Integrating AI with AR/VR: Transforming user interaction and empowering creators](https://tirotir.ir/integrating-ai-with-ar-vr-transforming-user-interaction-and-empowering-creators/): The convergence of AI and AR/VR is changing the way we engage with, explore, and even create content for virtual... - [When (and when not) to build AI products: A guide to maximizing ROI](https://tirotir.ir/when-and-when-not-to-build-ai-products-a-guide-to-maximizing-roi/): A few weeks ago, I saw a post on Instagram that made me laugh; it was about someone’s grandmother asking... - [Quantum leaps: Transforming data centers & energy](https://tirotir.ir/quantum-leaps-transforming-data-centers-energy/): We are making Quantum Leaps. I am not referring to the 80s/90s TV show, but rather, I am referring to... - [AIAI Silicon Valley, 2025](https://tirotir.ir/aiai-silicon-valley-2025/): Catch up on every session from the AIAI Silicon Valley with sessions across 3 co-located summit featuring the likes of... - [How to build a powerful LLM user feedback loop](https://tirotir.ir/how-to-build-a-powerful-llm-user-feedback-loop/): Discover how to build a powerful LLM user feedback loop with Nebuly, optimizing AI interactions and driving continuous improvement. - [IBM & Oracle debut watsonx agentic AI on OCI](https://tirotir.ir/ibm-oracle-debut-watsonx-agentic-ai-on-oci/): Unlike traditional AI systems that rely on step-by-step human input, agentic AI represents the next evolution: autonomous agents capable of... - [Rewiring the internet: Commerce in the age of AI agents](https://tirotir.ir/rewiring-the-internet-commerce-in-the-age-of-ai-agents/): December 2028. 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As traditional financial models struggle to keep up with the... - [How generative AI is revolutionizing drug discovery and development](https://tirotir.ir/how-generative-ai-is-revolutionizing-drug-discovery-and-development/): This article comes from Dr Nikolay Burlutskiy’s talk at our London 2024 Generative AI Summit. Check out his full presentation... - [AI's next leap: Gemini 2.5, 1-bit LLM & beyond](https://tirotir.ir/ais-next-leap-gemini-2-5-1-bit-llm-beyond/): Post Content - [AI agent infra, Gemini 2.5, 1-bit LLM: This week’s top 5](https://tirotir.ir/ai-agent-infra-gemini-2-5-1-bit-llm-this-weeks-top-5/): Welcome to AI Circuit, in April’s edition: The great web rebuild: Infrastructure for the AI agent era Meet Gemini 2.... - [The great web rebuild: Infrastructure for the AI agent era](https://tirotir.ir/the-great-web-rebuild-infrastructure-for-the-ai-agent-era/): It’s December 2028. Sarah’s AI agent encounters an unusual situation while booking her family’s holiday trip to Japan. The multi-leg... - [AIOps in action: AI & automation transforming IT operations](https://tirotir.ir/aiops-in-action-ai-automation-transforming-it-operations/): The advancement of digital frameworks has created new hurdles for business IT operations. A company’s network, cloud infrastructure, and streams... - [The truth about enterprise AI agents (and how to get value from them)](https://tirotir.ir/the-truth-about-enterprise-ai-agents-and-how-to-get-value-from-them/): This article comes from Ryan Priem’s talk at our Washington, D. C. 2025 Generative AI Summit. Check out his full... - [How to 8‑bit quantize large models using bits and bytes](https://tirotir.ir/how-to-8%e2%80%91bit-quantize-large-models-using-bits-and-bytes/): Deep learning is consistently changing so many fields, from NLP (natural language processing) to computer vision. 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Nowadays, with the emergence of artificial intelligence technology, almost all... - [Generative AI Summit Austin, 2025](https://tirotir.ir/generative-ai-summit-austin-2025/): Catch up on every session from the Generative AI Summit Austin with sessions from the likes of DLA Piper, Wayfair,... - [AI image detection: Types, applications, and future trends](https://tirotir.ir/ai-image-detection-types-applications-and-future-trends/): This technology is being used to identify fake photos. An AI-powered tool called Photoshop Detector can recognize and detect a... - [How recommender systems support social learning in companies](https://tirotir.ir/how-recommender-systems-support-social-learning-in-companies/): What do the streaming service Netflix, the business platform LinkedIn, and the dating portal Tinder have in common? 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This year,... - [UK's AI supercomputer to transform drug development](https://tirotir.ir/uks-ai-supercomputer-to-transform-drug-development/): A groundbreaking £225 million supercomputer, Isambard-AI, is set to revolutionize the medical field by aiding in the development of new... - [Transforming AML: Exploding the potential of AI solutions](https://tirotir.ir/transforming-aml-exploding-the-potential-of-ai-solutions/): Do you need a captivating method of presenting your anti-money laundering (AML) system to clients? As a result of the... - [Austin: Not necessarily the new Silicon Valley, but...](https://tirotir.ir/austin-not-necessarily-the-new-silicon-valley-but/): Ranked 17th globally in StartUp Blink’s ‘Best Cities for Startups’ 2024 rankings – an index factoring quality, quantity and growth... - [UK's AI blueprint: AI Opportunities Action Plan](https://tirotir.ir/uks-ai-blueprint-ai-opportunities-action-plan/): The United Kingdom stands as the third-largest artificial intelligence (AI) market globally, boasting a rich history of scientific innovation and... --- # # Detailed Content ## برگه‌ها - Published: 1404-11-06 - Modified: 1404-11-06 - URL: https://tirotir.ir/news/ TirotirSearch جستجوی پیشرفته گوگل عبارت جستجو بازه زمانی همه ۱ ساعت گذشته ۲۴ ساعت گذشته ۱ هفته گذشته نوع محتوا وب اخبار دامنه خاص نوع فایل همه PDF Word PowerPoint زبان همه فارسی English کشور همه ایران USA جستجو function tirotirSearch{ let q=document. getElementById("ts-q"). value. trim; if(! q){alert("عبارت جستجو را وارد کنید");return;} let tbs=; let site=document. getElementById("ts-site"). value. trim; let file=document. getElementById("ts-file"). value; let type=document. getElementById("ts-type"). value; let time=document. getElementById("ts-time"). value; let lang=document. getElementById("ts-lang"). value; let country=document. getElementById("ts-country"). value; if(site) q+=" site:"+site; if(file) q+=" filetype:"+file; if(time) tbs. push(time); if(lang) tbs. push(lang); if(country) tbs. push(country); let url="https://www. google. com/search? q="+encodeURIComponent(q); if(type) url+="&tbm="+type; if(tbs. length) url+="&tbs="+tbs. join(","); window. open(url,"_blank"); } --- - Published: 1404-07-29 - Modified: 1404-09-09 - URL: https://tirotir.ir/%d8%a2%d8%b2%d9%85%d9%88%d9%86-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86/ نمونه سوال آزمون کلاسی پایتون ۱ آموزشگاه هوش مصنوعی ۱- نمونه سوال پایتون ۱ پاییز ۱۴۰۴ آزمون پایتون - آموزشگاه هوش مصنوعی (تیروتیر) آزمون پایتون — آموزشگاه هوش مصنوعی (تیروتیر) بخش اول — سؤالات چندگزینه ای با پاسخ و توضیح 1. کدام یک از موارد زیر عملگر صحیح جمع در پایتون است؟ (الف) + (ب) - (ج) * (د) / پاسخ: (الف) + عملگر + برای جمع در پایتون به کار می رود. 2. برای چاپ متنی در پایتون، از کدام دستور استفاده می کنیم؟ (الف) display (ب) print (ج) show (د) write پاسخ: (ب) print برای چاپ در کنسول از تابع print استفاده می شود. 3. متغیر در پایتون می تواند با یکی از این علامت ها آغاز شود؟ (الف) $ (ب) @ (ج) # (د) _ پاسخ: (د) _ متغیرها می توانند با حروف یا زیرخط (_) شروع شوند؛ $,@,# مجاز نیستند. 4. کدام یک از موارد زیر یک نوع داده عددی در پایتون نیست؟ (الف) int (ب) float (ج) bool (د) string پاسخ: (د) string string (رشته) نوع متنی است؛ int و float عددی و bool منطقی اند. 5. برای تعریف یک لیست در پایتون، از کدام علامت گذاری استفاده می کنیم؟ (الف) (ب) {} (ج) (د) // پاسخ: (الف) لیست ها با کروشه های مربعی تعریف می شوند. 6. برای دسترسی به عنصری از لیست در پایتون، از چه علامتی استفاده می کنیم؟ (الف) (ب) {} (ج) (د) // پاسخ: (الف) برای ایندکس گذاری از براکت مربع استفاده می کنیم. 7. کدام یک از موارد زیر... --- - Published: 1404-07-29 - Modified: 1404-07-29 - URL: https://tirotir.ir/%d8%af%d9%88%d8%b1%d9%87%d9%87%d8%a7%db%8c-%d8%a2%d9%85%d9%88%d8%b2%d8%b4%db%8c/ پایتون ۱ ICDL Web 1 --- - Published: 1404-05-29 - Modified: -0001-11-30 - URL: https://tirotir.ir/%d8%af%d8%b1%d8%a8%d8%a7%d8%b1%d9%87-%d9%85%d8%a7/ همکاری با ما تیروتیر — آموزش، ابزار و محتوای متن باز برای Python، هوش مصنوعی و وب آموزشگاه فنی و حرفه ای آزاد «هوش مصنوعی» (Hoosh Masnooe) — زیر نظر مرکز فنی و حرفه ای ایذه، خوزستان. مأموریت ما: یادگیری پروژه محور برای همهٔ فارسی زبانان. مؤسسهٔ اندیشه پردازان آنزان — تأسیس ۱۳۷۹ — شماره ثبت ۴ — با مدرک معتبر گیت هاب تیروتیر اکستنشن های VS Code ثبت نام کارگاه ها Python • AI/MLآموزش پروژه محور Open-Sourceنمونه کد و نوت بوک RTL • فارسیمناسب کلاس و خودآموز هویت حقوقی و مأموریت مؤسسه اندیشه پردازان آنزان آموزشگاه فنی و حرفه ای آزاد «هوش مصنوعی» در ایذه — با مجوز رسمی و صدور مدرک معتبر. بنیان گذار: دکتر داریوش علیپور؛ مدیر: دکتر مینوش حیدری. تمرکز ما: خلق ابزارهای هوش مصنوعی با کدنویسی، نه صرفاً استفاده از ابزارها. ثبت ۴تأسیس ۱۳۷۹City of AI — Izeh ساختار ترمی دوره های ترمیک معمولاً ۲ ماهه، شامل ۱۰ جلسهٔ ۲ ساعته (نیمه خصوصی). امکان ترکیب چند دوره برای هنرجویان پرتلاش وجود دارد. هدایا برای برگزیدگان هر کلاس: رباتیک • سواد AI • اسکرچ • مونتاژ ارتباط سریع 09901204024 | 09124593239 ai. tirotir@gmail. com تلگرام: @AI_and_Philosophy تعهد ما؟ آموزش پروژه محور دوره ها و مثال های واقعی در Python، AI/ML، وب و رباتیک؛ همراه تمرین، آزمون و راهنمای گام به گام. پروژه های متن باز ریپوهای گیت هاب با کد تمیز، توضیح خط به خط و ابزارهای کلاس درس؛ مناسب مدرسان و هنرجویان. اکستنشن های VS Code تمپلیت ها، اسنیپت ها و ابزارهای آموزشی (RTL) برای... --- - Published: 1404-05-18 - Modified: 1404-09-01 - URL: https://tirotir.ir/%d8%a8%d8%b1%d9%86%d8%a7%d9%85%d9%87%d9%86%d9%88%db%8c%d8%b3%db%8c-%d9%88%d8%a8/ هاست و دامنه خریداری کنید. تخفیف ویژه برای مشتریان معرفی شده به میزان %9 لحاظ می شود. مرجع رنگ پروژه ۱ تیروتیر برای آموزش برنامه نویسی وب ۱ (با کامپیوتر ببینید) یکی از درس های مقدماتی پروژه و پکیج کامل webWeeks1 برگه داوری آزمون المپیاد جهانی وب --- - Published: 1404-05-14 - Modified: 1404-08-20 - URL: https://tirotir.ir/icdl-2/ پاسخ آزمون عملی پروژه های Wordآزمون عملی Wordبهترین هاست و دامنهآزمون نهایی ICDLتمرین تایپ ده انگشتی فارسی تیروتیرنمونه ساده ۱- آزمون نهایی آموزشگاهمرور مبانی ICDLمرور پاورپوینت و عملیتمرین عملی اکسل و مرور۴- واژه پرداز Word۳- اینترنت ICDLتعریف ICDL مهارت های هفت گانه کامپیوترآزمون عملی Word و مرور۲- آموزش سيستم عامل ويندوز ICDL۱- مفاهيم اوليه و اساسی کامپيوتر ICDL اصطلاحات مهم ICDL Important ICDL Terms – Lesson 1 کامپیوتر: دستگاه الکترونیکی که اطلاعات را دریافت، پردازش، ذخیره و خروجی می دهد. Computer: An electronic device that receives, processes, stores, and outputs data سخت افزار: تمام قطعات فیزیکی و قابل لمس کامپیوتر مانند کیبورد، مانیتور و CPU. Hardware: All physical and tangible components of a computer like keyboard, monitor, and CPU نرم افزار: مجموعه دستورات و برنامه هایی که روی سخت افزار اجرا می شوند تا وظایف خاصی انجام دهند. Software: A set of instructions and programs that run on hardware to perform specific tasks سیستم عامل: نرم افزاری که سخت افزار را مدیریت کرده و ارتباط بین کاربر و کامپیوتر را فراهم می کند (مثل Windows، Linux). Operating System (OS): Software that manages hardware and provides an interface between the user and the computer (e. g. , Windows, Linux) پردازنده مرکزی: واحد اصلی پردازش دستورات و محاسبات در کامپیوتر؛ به آن "مغز کامپیوتر" می گویند. CPU: The main unit that executes instructions and performs calculations; known as the brain of the computer حافظه دسترسی تصادفی: حافظه موقت و سریع که داده های در حال استفاده را نگه می دارد؛ با خاموش... --- - Published: 1403-03-13 - Modified: 1403-03-13 - URL: https://tirotir.ir/s/ این محتوا با رمز محافظت شده است. برای مشاهده رمز را در پایین وارد نمایید: رمز عبور: --- - Published: 1403-01-13 - Modified: 1403-01-15 - URL: https://tirotir.ir/%d9%85%d9%86%d8%b7%d9%82-%d8%af%d9%87%d9%85/ آموزش مفاهیم پیچیده با داستان (کاری از آموزشگاه هوش مصنوعی). تقدیم به علاقمندان و سالن مطالعه دختران هوش مصنوعی! داستان جذاب تصور و تصدیق در روستای پر رمز و راز "ذهن آباد"، دو دوست صمیمی به نام های "سارا" و "پیمان" زندگی می کردند. سارا دختری کنجکاو و جستجوگر بود و پیمان پسری خلاق و داستان گو. روزی در حین گشت و گذار در باغ پر از رمز و راز ذهن آباد، با مجسمه ای عجیب و غریب روبرو شدند. مجسمه ای که از چوب تراشیده شده بود و تصویری از یک درخت بر روی آن نقش بسته بود. در زیر تصویر، جمله ای حک شده بود که توجه سارا و پیمان را به خود جلب کرد: "تصور، دریچه ای به سوی تصدیق" سارا: (با تعجب) عجب جمله ی عجیبی! "تصور، دریچه ای به سوی تصدیق". به نظر تو منظور این جمله چیست؟ پیمان: (با دقت به تصویر درخت و جمله ی حک شده) فکر می کنم این جمله به نوعی ارتباط بین ذهن ما و دنیای واقعی اشاره دارد. سارا: اما چگونه؟ مگر ما بدون تصور، نمی توانیم دنیای واقعی را درک کنیم؟ پیمان: بله، ما می توانیم اشیاء و پدیده های دنیای واقعی را بدون تصور درک کنیم، اما تصور به ما کمک می کند تا این درک را عمیق تر و دقیق تر کنیم. سارا: مثالی می زنی؟ پیمان: بله. به این تصویر درخت نگاه کن. سارا: (به تصویر درخت نگاه می کند) خب؟ پیمان: قبل از اینکه این تصویر را ببینی، چه تصوری از درخت داشتی؟... --- - Published: 1402-11-24 - Modified: 1403-05-04 - URL: https://tirotir.ir/rus2/ این محتوا با رمز محافظت شده است. برای مشاهده رمز را در پایین وارد نمایید: رمز عبور: --- - Published: 1402-11-23 - Modified: 1403-05-04 - URL: https://tirotir.ir/rus/ این محتوا با رمز محافظت شده است. برای مشاهده رمز را در پایین وارد نمایید: رمز عبور: --- - Published: 1402-08-27 - Modified: 1402-08-27 - URL: https://tirotir.ir/temp/ این محتوا با رمز محافظت شده است. برای مشاهده رمز را در پایین وارد نمایید: رمز عبور: --- - Published: 1402-08-22 - Modified: 1402-08-22 - URL: https://tirotir.ir/%d9%81%d9%84%d9%88%da%86%d8%a7%d8%b1%d8%aa/ https://app. code2flow. com/YP60k79Mz6vN --- - Published: 1402-08-17 - Modified: 1404-10-06 - URL: https://tirotir.ir/code/ کارگاه برنامه نویسی تیروتیر https://www. online-ide. com/ https://www. online-python. com/ دانلود برخی برنامه های مهم C++ Online Compiler Ideone Open Source C/C++ IDE for Windows ابزارهای برنامه نویسی دانلود نرم افزار Sublime Text برنامه Notepad-plus-plus عیب یاب آنلاین برنامه مرجع رنگ کامپایل C و بسیاری از برنامه های دیگر در کامپیوتر شخصی: روش ۱) استفاده از ترمینال برنامه Visual Studio 2022، تغییر مسیر به پوشه حاوی فایل منبع (مثلا hello. c) و نهایتا استفاده از دستور CL: c:\hello>cl hello. c روش ۲) نرم افزار Code::Blocks روش ۳) دانلود MinGW و نصب پکیج های: mingw-developer-toolkit, mingw32-base, mingw32-gcc-g++, msys-base path: ... ... ... C:\MinGW\bin gcc g++ روش ۴) برنامه Visual Studio Code روش ۵) برنامه Visual Studio Code Insiders روش ۶) استفاده از csc. exe برای کامپایل سی شارپ مسیر این فایل را باید به ویندوز معرفی کنید. مثلا: C:\Program Files\Microsoft Visual Studio\2022\Enterprise\MSBuild\Current\Bin\Roslyn سپس: csc. exe hello. cs Git and GitHub Best Programming Languages Of 2024 --- - Published: 1402-07-07 - Modified: 1402-07-07 - URL: https://tirotir.ir/%d8%ab%d8%a8%d8%aa%d9%86%d8%a7%d9%85/ با درود و خوش آمدگویی Scan the codeOpen Chat نام شما ایمیل شما تلفن آدرس دوره های مورد علاقه —لطفا یک گزینه را انتخاب کنید—ICDLبرنامه نویسی اسکرچبرنامه نویسی وب ۱برنامه نویسی وب ۲برنامه نویسی وب ۳برنامه نویسی وب ۴برنامه نویسی پایتونبرنامه نویسی C و ++Cبرنامه نویسی رباتیک ۱ تا ۳برنامه نویسی رباتیک ۴ تا ۶زبان روسیزبان آلمانیشطرنج تحلیلی و علمی روز و ساعتی که می توانید یا نمی توانید توضیحات (اختیاری: تحصیلات، شغل و ... ) --- - Published: 1402-07-07 - Modified: 1402-08-15 - URL: https://tirotir.ir/%d9%85%d8%a7%d8%aa-%d8%b3%d8%b1%db%8c%d8%b9/ کوتاه ترین بازی شطرنج همان طور که شما هم بهتر از من می دانید در دو حرکت است که به صورت زیر به وقوع می پیوندد . You must activate JavaScript to enhance chess game visualization. (function { function renderThisPGN { RPBChessboard. renderPGN("rpbchessboard-693ed8a03f354-1", {"pgn":"\n\n\n\n\n\n\n\n\n1. f3 {Weakening the white king and taking away the best square from the knight\non g1 is not a good way to start the game $1} 1... e5 $1 { Black stakes claim to the center\ndeveloping the f8-bishop and the queen. } 2. g4 $4 { This move together with 1. f3 is the\nworse way to start the game $1} 2... Qh4# {That’s it $1 The two-move-checkmate, or\nFool’s Mate. } 0-1","pieceSymbols":"native","navigationBoard":"floatLeft","withPlayButton":true,"withFlipButton":true,"withDownloadButton":true,"nboSquareSize":32,"nboCoordinateVisible":true,"nboTurnVisible":true,"nboColorset":"original","nboPieceset":"cburnett","nboAnimated":true,"nboMoveArrowVisible":true,"nboMoveArrowColor":"b","idoSquareSize":36,"idoCoordinateVisible":true,"idoTurnVisible":true,"idoColorset":"original","idoPieceset":"cburnett"}); } if (document. readyState === 'loading') { document. addEventListener('DOMContentLoaded', renderThisPGN); } else { renderThisPGN; } }); مات ناپلئونی یا روش ناپلئونی مات ناپلئونی یک مات چهار حرکت یا به عبارتی یک مات کوتاه چند حرکته است که در ادامه با تاریخچه جالب آن هم آشنا خواهید شد . You must activate JavaScript to enhance chess game visualization. (function { function renderThisPGN { RPBChessboard. renderPGN("rpbchessboard-693ed8a03f354-2", {"pgn":"1. e4 e5 2. Qh5 Nc6 3. Bc4 Nf6 4. Qxf7# 1-0","pieceSymbols":"native","navigationBoard":"floatLeft","withPlayButton":true,"withFlipButton":true,"withDownloadButton":true,"nboSquareSize":32,"nboCoordinateVisible":true,"nboTurnVisible":true,"nboColorset":"original","nboPieceset":"cburnett","nboAnimated":true,"nboMoveArrowVisible":true,"nboMoveArrowColor":"b","idoSquareSize":36,"idoCoordinateVisible":true,"idoTurnVisible":true,"idoColorset":"original","idoPieceset":"cburnett"}); } if (document. readyState === 'loading') { document. addEventListener('DOMContentLoaded', renderThisPGN); } else { renderThisPGN; } }); ناپلئونی به شکل دیگر: --- - Published: 1402-07-02 - Modified: 1402-07-06 - URL: https://tirotir.ir/%d8%af%d8%a7%d9%86%d9%84%d9%88%d8%af/ نرم افزار Sublime Text Sublime Text نرم افزاری قدرتمند در زمینه ویرایش متون پیشرفته برای کد، HTML و نثر می باشد. توسط نرم افزار Sublime Text شما می توانید 10 تغییر را در یک زمان انجام دهید. ویرایش متون، دارای طرح چند رنگ، با چند جمله، دارای براکت برجسته، قابلیت ذخیره تغییرات، انتخاب ویرایش دستورات، امکان انتخاب چندگانه، جستجو و جایگزینی عبارت منظم و ... از ویژگی های نرم افزار Sublime Text می باشد. قابلیت های نرم افزار Sublime Text چند پنجره ویرایش در کنار هم مشاهده کد خود از 10000 پا قابلیت مشاهده در حالت کامل روی صفحه نمایش مشخص کردن نحو زبان های مختلف مانند C ،C++ ،C# ،CSS ،D ،Erlang ،HTML ،Groovy ،Haskell ،HTML ،Java ،jаvascript ،LaTeX ،Lisp ،Lua ،Markdown ،Matlab ،OCaml ،Perl ،PHP ،Python ،R ،Ruby ،SQL ،TCL ،Textile و XML دارای طرح چند رنگ، با چند جمله دارای براکت برجسته قابلیت ذخیره تغییرات انتخاب ویرایش دستورات، از جمله تورفتگی / غیربرجستگی پاراگراف، تغییر شکل پاراگراف، پیوستگی خط جستجو و جایگزینی عبارت منظم مرور از طریق فایل های طولانی توضیح بلوک متن تنظیم کلید اتصالات، منوها و نوار ابزار پلاگین همراه با API تکرار آخرین عمل ساخت ابزار یکپارچه سازی ادغام WinSCP برای ویرایش فایل های از راه دور از طریق FTP و SCP Sublime. Text. 4. 0. Build. 4152. x64دریافت Sublime. Text. 3. 2. 2. Build. 3211. x86دریافت Visual Studio Code  VS Code یک محیط توسعه یکپارچه (IDE) سبک و قدرتمند است که برای توسعه نرم افزارها و برنامه های تحت وب بهبود یافته و... --- - Published: 1402-07-02 - Modified: 1404-05-18 - URL: https://tirotir.ir/%d8%b1%d9%86%da%af/ رنگ های شش گانه (Hexadecimal Colors) مقادیر رنگ های شش گانه با تمام مرورگرها سازگاری دارند. یک رنگ شش گانه با استفاده از مقادیر زیر مشخص می شود: rrggbb که در آن rr (قرمز)، gg (سبز) و bb (آبی) عدد صحیح شش گانه در بازه 00 تا ff هستند که شدت رنگ را مشخص می کنند. به عنوان مثال، ff0000 به عنوان قرمز نمایش داده می شود، زیرا قرمز به بالاترین مقدار خود (ff) تنظیم شده است و دو مقدار دیگر (سبز و آبی) به 00 تنظیم شده اند. یک مثال دیگر، 00ff00 به عنوان سبز نمایش داده می شود، زیرا سبز به بالاترین مقدار خود (ff) تنظیم شده است و دو مقدار دیگر (قرمز و آبی) به 00 تنظیم شده اند. برای نمایش رنگ سیاه، تمام پارامترهای رنگ را به 00 تنظیم کنید، مانند این: 000000. برای نمایش رنگ سفید، تمام پارامترهای رنگ را به ff تنظیم کنید، مانند این: ffffff. div { background-color: #00bfff; color: #ffffff; padding: 20px; } Andisheh Pardazan Anzan Welcome to tirotir. ir. رنگ های RGB مقادیر رنگ RGB با تمام مرورگرها سازگاری دارند. مقدار رنگ RGB با استفاده از فرمت زیر مشخص می شود: rgb(قرمز، سبز، آبی) هر پارامتر (قرمز، سبز، و آبی) شدت رنگ را با یک مقدار بین 0 تا 255 مشخص می کند. به عنوان مثال، rgb(255, 0, 0) به عنوان قرمز نمایش داده می شود، زیرا قرمز به بالاترین مقدار خود (255) تنظیم شده است و دو مقدار دیگر (سبز و آبی) به 0 تنظیم شده اند. یک مثال دیگر،... --- - Published: 1402-06-29 - Modified: 1402-06-29 - URL: https://tirotir.ir/registration-success/ Welcome --- - Published: 1402-06-29 - Modified: 1402-06-29 - URL: https://tirotir.ir/%d8%a8%d8%b1%da%af%d9%87-%d8%aa%d8%b3%d8%aa/ برگه تست ۱ --- - Published: 1402-06-24 - Modified: 1402-06-24 - URL: https://tirotir.ir/%d8%b5%d9%81%d8%ad%d9%87-%d8%a7%d8%b5%d9%84%db%8c/ به فروشگاه خوش آمدید اینجا یک پیام خوش آمدگویی کوتاه بنویسید بریم خرید محصولات جدید --- - Published: 1402-06-19 - Modified: 1402-06-24 - URL: https://tirotir.ir/courses/ دوره های آموزشی مهارتی دوره های آموزشی مهارتی حضوری و آنلاین --- - Published: 1402-06-19 - Modified: 1404-09-01 - URL: https://tirotir.ir/%d8%b4%d8%b7%d8%b1%d9%86%d8%ac-2/ همه گشایش های شطرنج به صورت درختی مات سریع برخی نکات مهم و کلیدی در بازی شطرنج برخی نوشته های مهم درباره اصول و گشایش ها یک فایل فوق العاده خوب شامل ۵۰۰ پازل مات در یک حرکت --- - Published: 1402-06-19 - Modified: 1404-05-18 - URL: https://tirotir.ir/%d8%a8%d8%b1%d9%86%d8%a7%d9%85%d9%87%d9%86%d9%88%db%8c%d8%b3%db%8c-%d9%88%d8%a8-%db%b1/ درس ۱ - آشنایی با HTML مثال My First Web Page Welcome to My Website This is a paragraph of text on my web page. مثال HTML Basics HTML Structure HTML stands for HyperText Markup Language. It is used to structure content on the web. HTML elements are enclosed in tags. درس ۲ - کار با المنت ها و ویژگی ها مثال HTML Attributes HTML Attributes The src attribute is used to specify the source of an image. The href attribute is used for hyperlinks. مثال HTML Elements Common HTML Elements Link Paragraph درس ۳ کار با عناصر form و input مثال HTML Forms HTML Forms Name: Email: مثال HTML Input Elements HTML Input Elements The input element is used to create various types of form fields, such as text boxes, email, and buttons. آزمون درس ۴- لیست و جدول مثال HTML Lists HTML Lists Item 1 Item 2 Item 3 مثال HTML Tables HTML Tables Name Age John 30 Jane 25 درس ۱- کار با CSS مثال /* CSS Code Example 1 */ body { font-family: Arial, sans-serif; background-color: #f0f0f0; color: #333; } h1 { color: #007BFF; } p { font-size: 16px; } My CSS Example /* CSS Code Example 1 */ body { font-family: Arial, sans-serif; background-color: #f0f0f0; color: #333; } h1 { color: #007BFF; } p { font-size: 16px; } Welcome to My Website This is a paragraph of text on my web page. Visit Example Item 1 Item 2 Item 3 مثال /* CSS Code Example... --- - Published: 1402-06-18 - Modified: 1404-06-13 - URL: https://tirotir.ir/ آموزشگاه فنی و حرفه ای آزاد هوش مصنوعی مؤسسه اندیشه پردازان آنزان تأسیس: ۱۳۷۹ | شماره ثبت: ۴ آموزش کامپیوتر، رباتیک، برنامه نویسی هوش مصنوعی، شطرنج، روسی Izeh AI – City of Artificial Intelligence مجموعه کارگاه های فنی ایجاد اپلیکیشن های ویندوز و وب هوش مصنوعی شروع دوره: چهارشنبه ۱۹ شهریور | ایذه • tirotir. ir در شهری که روزی به سنگ نگاره های باستانی اش شناخته می شد، امروز دروازه های آینده دیجیتال گشوده می شود. در ایذه، یکی از معدود نقاط جهان، مجموعه کارگاه های فنی برگزار می شود که ابزارهای هوش مصنوعی را از صفر خلق می کنند، نه فقط استفاده. آنچه خواهید ساخت: اپلیکیشن ویندوز: رابط حرفه ای، ماژول های AI، گزارش گیری اپلیکیشن وب: معماری مدرن، اتصال AI، امنیت و استقرار ویژگی ها: عملی و پروژه محور استانداردهای بین المللی خروجی واقعی برای صنعت ایذه، جایی که آینده دیجیتال آغاز می شود. // اسکریپت سبک اسلایدر گالری (بدون وابستگی) (function{ const gallery = document. querySelector('. image-gallery'); if(! gallery) return; const track = gallery. querySelector('. gallery-slide'); const slides = gallery. querySelectorAll('. gallery-slide > . wp-block-image'); const btnPrev = gallery. querySelector('. prev'); const btnNext = gallery. querySelector('. next'); let index = 0; function go(i){ index = (i + slides. length) % slides. length; track. style. transform = 'translateX(' + (-index * 100) + '%)'; } btnPrev && btnPrev. addEventListener('click', =>go(index-1)); btnNext && btnNext. addEventListener('click', =>go(index+1)); // کشیدن لمسی برای موبایل let startX = 0, dx = 0; track. addEventListener('touchstart', (e)=>{ startX = e. touches. clientX; dx =... --- - Published: 1402-06-15 - Modified: 1402-06-18 - URL: https://tirotir.ir/%d8%b4%d8%b7%d8%b1%d9%86%d8%ac/ گشایش ایتالیایی گشایش ایتالیایی - جوئیکو پیانو گشایش ایتالیایی - جوئیکو پیانو گشایش ایتالیایی - گامبی ایوانس این گامبی به منظور نگه داشتن سیاه از قلعه زدن و پایمال کردن مهره های فعال حریف در مرکز است '' گشایش اسپانیایی - روی لوپز دفاع سیسیلی- واریانت بسته دفاع سیسیلی- واریانت باز https://lichess. org/learn#/7 --- - Published: 1402-06-12 - Modified: 1402-06-15 - URL: https://tirotir.ir/%da%a9%d8%aa%d8%a7%d8%a8%d9%87%d8%a7%db%8c-%d9%85%d8%a7/ آموزش رباتیک برای کودکان- سال ۱۴۰۲ اصول علم ربات- سال ۱۴۰۱ آموزش رباتیک با پایتون و رزبری پای- سال ۱۴۰۰ --- - Published: 1402-06-12 - Modified: 1402-07-30 - URL: https://tirotir.ir/%d8%aa%d9%85%d8%a7%d8%b3-%d8%a8%d8%a7-%d9%85%d8%a7/ فرم ثبت نام دوره های آموزشی   نام شما ایمیل شما موضوع پیام شما (اختیاری) mihanwebhost. com کد معرف: mwh-61537 --- --- ## نوشته‌ها - Published: 1404-09-23 - Modified: 1404-09-23 - URL: https://tirotir.ir/%d9%be%d8%a7%d8%b3%d8%ae-%d8%a2%d8%b2%d9%85%d9%88%d9%86-%d8%b9%d9%85%d9%84%db%8c-%d9%be%d8%b1%d9%88%da%98%d9%87%d9%87%d8%a7%db%8c-word/ - دسته‌ها: ICDL پاسخ پروژه ۱ – تایپ حرفه ای فارسی گام ۱: نرم افزار Word را اجرا کرده و یک سند جدید باز کنید. گام ۲: از تب Home فونت فارسی مناسب را انتخاب و اندازه را روی ۱۴ قرار دهید. گام ۳: متن خواسته شده را تایپ کنید و علائم نگارشی فارسی را رعایت نمایید. گام ۴: فاصله خطوط را روی 1. 5 و فاصله پاراگراف قبل و بعد را تنظیم کنید. گام ۵: فایل را با نام مناسب ذخیره کنید. پاسخ پروژه ۲ – بازنویسی و ویرایش متن گام ۱: متن خام را در Word وارد کنید. گام ۲: از تب Review گزینه Spelling & Grammar را اجرا کنید. گام ۳: فونت و اندازه همه متن را یکسان کنید. گام ۴: با Find & Replace واژه های تکراری را اصلاح کنید. گام ۵: Track Changes را فعال و تغییرات را ذخیره کنید. پاسخ پروژه ۳ – نامه اداری رسمی گام ۱: صفحه جدید ایجاد و حاشیه ها را تنظیم کنید. گام ۲: سربرگ را در بالای صفحه تایپ یا طراحی کنید. گام ۳: شماره، تاریخ و پیوست را با Tab تراز نمایید. گام ۴: متن رسمی نامه را تایپ کنید. گام ۵: امضا و رونوشت را در انتهای نامه درج کنید. پاسخ پروژه ۴ – فرم ثبت نام گام ۱: یک جدول مناسب برای فرم ایجاد کنید. گام ۲: عناوین فیلدها مانند نام، کد ملی و تلفن را وارد کنید. گام ۳: از Developer CheckBox استفاده کنید. گام ۴: چینش جدول را تنظیم کنید. گام ۵: Restrict Editing را فعال... --- - Published: 1404-09-23 - Modified: 1404-09-23 - URL: https://tirotir.ir/%d8%a2%d8%b2%d9%85%d9%88%d9%86-%d8%b9%d9%85%d9%84%db%8c-word-2/ - دسته‌ها: ICDL - برچسب‌ها: ICDL پروژه ۱ – تایپ حرفه ای فارسی تایپ یک متن ۲ صفحه ای درباره «نقش فناوری در آموزش»، رعایت نیم فاصله و علائم نگارشی فارسی، تنظیم فونت فارسی استاندارد، اندازه متن ۱۴، فاصله خطوط 1. 5، فاصله قبل و بعد پاراگراف — مهارت ها: تایپ فارسی استاندارد، Paragraph، Spacing پروژه ۲ – بازنویسی و ویرایش متن اصلاح غلط های املایی و نگارشی یک متن خام، یکسان سازی فونت و اندازه ها، استفاده از Find & Replace و فعال سازی Track Changes — مهارت ها: Editing، Proofing، Track Changes پروژه ۳ – نامه اداری رسمی طراحی نامه اداری کامل شامل سربرگ، شماره، تاریخ، پیوست، متن رسمی، امضا و رونوشت، تراز متن با Tab یا جدول مخفی — مهارت ها: Official Letter، Tab، Layout پروژه ۴ – فرم ثبت نام طراحی فرم ثبت نام شامل نام و نام خانوادگی، کد ملی، تلفن، آدرس و امضا، استفاده از جدول و CheckBox و قفل کردن فرم — مهارت ها: Forms، Table، Protection پروژه ۵ – جدول نمرات هوشمند طراحی جدول نمرات یک کلاس، محاسبه معدل با Formula، مرتب سازی نمرات و رنگ بندی سطرها — مهارت ها: Table Formula، Sort، Table Design پروژه ۶ – بروشور تبلیغاتی سه لت تنظیم صفحه افقی، ایجاد سه ستون، درج تصویر و لوگو و تنظیم Text Wrapping برای طراحی بروشور — مهارت ها: Columns، Page Layout، Graphics پروژه ۷ – پوستر آموزشی طراحی پوستر A4 با Shape و Icon، تراز عناصر، گروه بندی اجزا و انتخاب رنگ بندی مناسب — مهارت ها: Shapes، Align، Group پروژه ۸ –... --- - Published: 1404-09-01 - Modified: 1404-09-01 - URL: https://tirotir.ir/%d8%a8%d9%87%d8%aa%d8%b1%db%8c%d9%86-%d9%87%d8%a7%d8%b3%d8%aa-%d9%88-%d8%af%d8%a7%d9%85%d9%86%d9%87/ - دسته‌ها: ICDL, پیوندها میهن وب هاست هاست و دامنه خریداری کنید. تخفیف ویژه برای مشتریان معرفی شده به میزان %9 لحاظ می شود. --- - Published: 1404-06-18 - Modified: 1404-08-06 - URL: https://tirotir.ir/%d9%87%d9%85%da%a9%d8%a7%d8%b1%db%8c-%d8%a8%d8%a7-%d9%85%d8%a7/ - دسته‌ها: درباره ما - برچسب‌ها: درباره پکیج جامع حرفه ها و توانمندی های هوش مصنوعی — Tirotir AI مأموریت و هویت مؤسسه اندیشه پردازان آنزان (تأسیس ۱۳۷۹، ثبت ۴) آموزشگاه فنی وحرفه ای آزاد «هوش مصنوعی» — ایذه (خوزستان) مجوز رسمی و صدور مدرک معتبر بنیان گذار: دکتر داریوش علیپور مدیر: دکتر مینوش حیدری تمرکز: خلق ابزارهای هوش مصنوعی با کدنویسی، نه صرفاً کار با ابزارها همه دوره ها به صورت کارگاه یا بوت کمپ (۱ یا ۲ روز در هفته) برگزار می شوند مأموریت: آموزش پروژه محور، متن باز، در دسترس همه دسته بندی حرفه ها مهارت های دیجیتال و برنامه نویسی ICDL مدرن و به روز ۲۰۲۵ (Ai-ICDL) Python مقدماتی تا پیشرفته (تأکید ویژه بر Python 1) وب (Frontend/Backend) → HTML/CSS/JS + PHP/MySQL لینوکس و مهارت های سیستمی انگلیسی فنی + ریاضیات و علوم کامپیوتر کاربردی هوش مصنوعی و یادگیری ماشین مبانی ML/AI: الگوریتم های پایه یادگیری عمیق (CNN, RNN, Transformers) NLP و چت بات ها بینایی ماشین (Computer Vision) Generative AI (دستیار، متن، تصویر، ویدیو) کارگاه های کار با ابزارهای هوش مصنوعی و آشنایی با مفاهیم آن رباتیک و سخت افزار مربیگری رباتیک Arduino و Raspberry Pi پروژه های IoT مونتاژ و برنامه نویسی کیت های آموزشی زبان های خارجی زبان روسی — از مقدماتی تا حرفه ای زبان آلمانی مقدماتی برنامه نویسی با خانواده C و C# مقدماتی: سینتکس، شرط ها، حلقه ها میانی: WinForms/WPF، اتصال به دیتابیس پیشرفته: اپلیکیشن های کامل نمونه کار: PersianTrayDate (اپ ویندوزی تاریخ شمسی) کارگاه فوق حرفه ای — ۵۰ پروژه واقعیت افزوده و مجازی (AR/VR) مبانی... --- - Published: 1404-06-01 - Modified: 1404-06-01 - URL: https://tirotir.ir/%d8%a2%d8%b2%d9%85%d9%88%d9%86-%d9%86%d9%87%d8%a7%db%8c%db%8c-icdl/ - دسته‌ها: ICDL صفحه آزمون --- - Published: 1404-05-16 - Modified: 1404-05-16 - URL: https://tirotir.ir/%d8%aa%d9%85%d8%b1%db%8c%d9%86-%d8%aa%d8%a7%db%8c%d9%be-%d8%af%d9%87%d8%a7%d9%86%da%af%d8%b4%d8%aa%db%8c-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d8%aa%db%8c%d8%b1%d9%88%d8%aa%db%8c%d8%b1/ - دسته‌ها: ICDL - برچسب‌ها: ICDL تمرین تایپ فارسی آنلاین/آفلاین تمرین تایپ انگلیسی آنلاین/آفلاین آموزش تایپ ده انگشتی فارسی درس ۱: حروف «ت»، «ب» + کلید فاصله یادگیری: محل قرارگیری انگشتان اشاره و شست؛ کلیدهای پایه. نکات مهم: انگشت اشاره دست چپ روی «ت» انگشت اشاره دست راست روی «ب» شست ها برای زدن فاصله تمرین ها: ت ب ت ب ب ت ت ب ت ب ت ب ت ب ب ت تبت ببت تب تب تبتب ببتب چالش سرعت (۳۰ ثانیه): ت ب ت ب ت ب ت ب درس ۲: حروف «ن» و «ی» یادگیری: استفاده از انگشتان میانی نکات مهم: «ن» = انگشت میانی دست راست «ی» = انگشت میانی دست چپ تمرین ها: ن ی ن ن ی ی ن ی ت ب ن ی ب ن ی ت ن ت ی بتن یتن تبنی بیتی نیتی ن ی ت ب ن ت ی ب ت ب ن ی درس ۳: حروف «م» و «س» یادگیری: استفاده از انگشتان انگشتری نکات مهم: «م» = انگشت انگشتری دست راست «س» = انگشت انگشتری دست چپ تمرین ها: م س م س س م ت ب ن ی م س ب س ن م ت ی سمب نیتم یبمس تنسم م م س س ی ی ن ن ب ب ت ت درس ۴: حروف «ک» و «ش» یادگیری: استفاده از انگشت کوچک دست راست و چپ نکات مهم: «ک» = انگشت کوچک دست راست «ش» = انگشت کوچک دست چپ تمرین ها: ش ک ش ش ک ک ش ک ش م... --- - Published: 1404-05-15 - Modified: 1404-05-15 - URL: https://tirotir.ir/%d9%86%d9%85%d9%88%d9%86%d9%87-%d8%b3%d8%a7%d8%af%d9%87-%db%b1-%d8%a2%d8%b2%d9%85%d9%88%d9%86-%d9%86%d9%87%d8%a7%db%8c%db%8c-%d8%a2%d9%85%d9%88%d8%b2%d8%b4%da%af%d8%a7%d9%87/ - دسته‌ها: ICDL - برچسب‌ها: ICDL «مفاهیم اولیه و اساسی کامپیوتر» سوالات تشریحی مفاهیم اولیه ICDL: 1. کامپیوتر را با زبان ساده تعریف کنید و مراحل اصلی کار آن را بنویسید. 2. تفاوت بین سخت افزار (Hardware) و نرم افزار (Software) را توضیح دهید و برای هرکدام دو مثال بنویسید. 3. منظور از داده (Data) و اطلاعات (Information) چیست؟ با یک مثال توضیح دهید. 4. RAM و هارد دیسک چه تفاوتی با هم دارند؟ عملکرد هرکدام را توضیح دهید. 5. اینترنت چیست و چه کاربردهایی در زندگی روزمره دارد؟ حداقل ۳ مورد بنویسید. 6. سیستم عامل چیست؟ چه وظیفه ای دارد و یک مثال برای آن بنویسید. 7. اگر هنگام کار با اینترنت یک ایمیل ناشناس با فایل پیوست برایتان بیاید، چه کار می کنید؟ چرا؟ 8. یک مثال واقعی از کاربرد کامپیوتر در مدرسه یا خانه بنویسید و اجزای سخت افزاری و نرم افزاری مورد استفاده در آن را مشخص کنید. 9. چرا داشتن رمز عبور قوی در اینترنت مهم است؟ چه نکاتی را باید برای ساخت رمز قوی رعایت کنیم؟ 10. مراحل ذخیره سازی یک فایل در کامپیوتر را به زبان ساده بنویسید (از باز کردن برنامه تا ذخیره ی فایل در فلش مموری). 🟦 بخش ویندوز (Windows) – سوالات عملی: 1. ایجاد پوشه و مدیریت فایل ها یک پوشه با نام ICDL_Practice در دسکتاپ بسازید. داخل آن یک پوشه ی دیگر به نام Documents و یک فایل متنی با نام Test. txt بسازید. فایل را به پوشه ی Documents منتقل کنید و سپس پوشه ی اصلی را به فلش مموری کپی کنید. 2.... --- - Published: 1404-05-14 - Modified: 1404-05-14 - URL: https://tirotir.ir/%d9%85%d8%b1%d9%88%d8%b1-%d9%85%d8%a8%d8%a7%d9%86%db%8c-icdl/ - دسته‌ها: ICDL - برچسب‌ها: ICDL آموزشگاه هوش مصنوعی: مفاهیم اولیه کامپیوتر و سخت افزار تعریف کامپیوتر و انواع آنپرسش: کامپیوتر چیست و چه انواعی دارد؟پاسخ: کامپیوتر دستگاهی است که داده ها را پردازش و نتایج را نمایش می دهد. انواع آن شامل دسکتاپ -برای کارهای ثابت-، لپ تاپ -قابل حمل-، و تبلت -صفحه لمسی- است. مثال: یک لپ تاپ می تواند برای برنامه نویسی و تبلت برای خواندن کتاب های الکترونیکی استفاده شود. شناخت اجزای اصلی کامپیوترپرسش: اجزای اصلی کامپیوتر کدام اند؟پاسخ: اجزا شامل ورودی -مانند ماوس و کیبورد-، پردازش -CPU-، خروجی -مانیتور، چاپگر-، و ذخیره سازی -HDD/SSD- هستند. راه عملی: کیبورد را وصل کنید و در برنامه "نوت پد" متن تایپ کنید؛ نتیجه در مانیتور نمایش داده می شود. مفهوم سیستم عاملپرسش: سیستم عامل چیست؟پاسخ: سیستم عامل نرم افزاری است که بین کاربر و سخت افزار واسطه می شود؛ ویندوز، لینوکس و مک از نمونه ها هستند. مثال عملی: اگر در ویندوز هستید، کلید Start را فشار دهید و نرم افزار Word را باز کنید. تفاوت نرم افزار و سخت افزارپرسش: نرم افزار و سخت افزار چه تفاوتی دارند؟پاسخ: سخت افزار اجزای فیزیکی سیستم است؛ نرم افزار برنامه هایی است که روی آن اجرا می شوند. راه عملی: ماوس را لمس کنید -سخت افزار- و از مرورگر کروم برای جستجو استفاده کنید -نرم افزار-. مدیریت فایل و پوشه هاپرسش: چگونه فایل و پوشه ها را مدیریت کنیم؟پاسخ: فایل ها داده های ذخیره شده و پوشه ها ساختاری برای مرتب سازی آن ها هستند. مثال عملی: پوشه ای به نام "درس" در دسکتاپ ایجاد کنید... --- - Published: 1404-05-14 - Modified: 1404-05-14 - URL: https://tirotir.ir/%d9%85%d8%b1%d9%88%d8%b1-%d9%be%d8%a7%d9%88%d8%b1%d9%be%d9%88%db%8c%d9%86%d8%aa-%d9%88-%d8%b9%d9%85%d9%84%db%8c/ - دسته‌ها: ICDL ۳۰ مورد برای پاورپوینت: ایجاد یک اسلاید جدید انتخاب تب Home --> New Slide --> انتخاب نوع اسلاید. افزودن متن به اسلاید کلیک روی جعبه متنی و تایپ متن. افزودن تصویر به اسلاید انتخاب تب Insert --> Pictures --> انتخاب تصویر از محل ذخیره. استفاده از قالب آماده (Theme) انتخاب تب Design --> انتخاب قالب (Theme) از گالری. انتخاب طرح بندی (Layout) اسلاید انتخاب اسلاید --> انتخاب تب Home --> Layout --> انتخاب طرح بندی. انتقال بین اسلایدها با استفاده از انیمیشن ها انتخاب اسلاید --> انتخاب تب Transitions --> انتخاب نوع انتقال. افزودن لینک های اینترنتی به اسلاید انتخاب متن یا تصویر --> راست کلیک --> Hyperlink --> وارد کردن URL. استفاده از انیمیشن برای اشیاء انتخاب شیء --> انتخاب تب Animations --> انتخاب نوع انیمیشن. ایجاد نمودار در اسلاید انتخاب تب Insert --> Chart --> انتخاب نوع نمودار و وارد کردن داده ها. ایجاد جعبه متن در اسلاید انتخاب تب Insert --> Text Box --> تایپ متن در جعبه. افزودن ویدیو به اسلاید انتخاب تب Insert --> Video --> انتخاب ویدیو از فایل یا آنلاین. استفاده از SmartArt در پاورپوینت انتخاب تب Insert --> SmartArt --> انتخاب نوع SmartArt. تنظیم زمان برای هر اسلاید انتخاب تب Transitions --> مدت زمان برای نمایش اسلاید را وارد کنید. ایجاد افکت برای اشیاء هنگام ورود به اسلاید انتخاب شیء --> انتخاب تب Animations --> انتخاب نوع انیمیشن ورود. افزودن صدا به اسلاید انتخاب تب Insert --> Audio --> انتخاب منبع صدا. تنظیم یک اسلاید به عنوان اسلاید عنوان انتخاب اسلاید اول... --- - Published: 1404-05-14 - Modified: 1404-05-14 - URL: https://tirotir.ir/%d8%aa%d9%85%d8%b1%db%8c%d9%86-%d8%b9%d9%85%d9%84%db%8c-%d8%a7%da%a9%d8%b3%d9%84/ - دسته‌ها: ICDL - برچسب‌ها: ICDL تمرین عملی اکسل تمرین: مدیریت فروش محصولات فرض کنید یک فروشگاه سه محصول مختلف می فروشد و داده های فروش ماهانه ی آنها به شرح زیر است: ماهkala1 (تعداد)kala2 (تعداد)kala3 (تعداد)ژانویه12080150فوریه10090200مارس140110170آوریل130100180 اهداف تمرین: محاسبه مجموع فروش هر محصول. محاسبه میانگین فروش ماهانه برای هر محصول. شناسایی پرفروش ترین محصول هر ماه. ایجاد نمودار فروش ماهانه برای هر محصول. گام ۱: ورود داده ها ابتدا داده های جدول بالا را در اکسل وارد کنید. گام ۲: محاسبه مجموع فروش هر محصول در سلول E2، فرمول زیر را وارد کنید: =SUM(B2:B5) این فرمول مجموع فروش kala1 را محاسبه می کند. آن را به سلول های دیگر E3 و E4 کپی کنید تا مجموع فروش برای kala2 و ۳ نیز محاسبه شود. گام ۳: محاسبه میانگین فروش ماهانه در سلول F2، فرمول زیر را وارد کنید: =AVERAGE(B2:B5) این فرمول میانگین فروش kala1 را محاسبه می کند. آن را به سلول های دیگر F3 و F4 کپی کنید تا میانگین فروش برای kala2 و ۳ نیز محاسبه شود. گام ۴: شناسایی پرفروش ترین محصول هر ماه در سلول G2، فرمول زیر را وارد کنید: =IF(MAX(B2:D2)=B2,"kala1",IF(MAX(B2:D2)=C2,"kala2","kala3")) این فرمول بررسی می کند که کدام محصول بیشترین فروش را در ژانویه داشته است. آن را به سایر سلول های ستون G کپی کنید تا برای سایر ماه ها نیز محاسبه شود. گام ۵: ایجاد نمودار فروش ماهانه داده های ستون های A تا D (ماه و تعداد فروش محصولات) را انتخاب کنید. به بخش Insert بروید و نمودار Column Chart یا Line Chart را انتخاب کنید. نمودار... --- - Published: 1404-05-14 - Modified: 1404-05-14 - URL: https://tirotir.ir/%db%b4-%d9%88%d8%a7%da%98%d9%87%d9%be%d8%b1%d8%af%d8%a7%d8%b2-word/ - دسته‌ها: ICDL Microsoft Word مؤلفين: داريوش عليپور، مينوش حيدري آموزشگاه هوش مصنوعی tirotir. ir فهرست مقدمه. 6 بخش نخست. . 8 1-1 آشنايی با تعريف واژه پرداز 9 1-2 آشنايي با اجراي برنامه Word. . 9 1-3 آشنايی با محيط اصلي Microsoft Word. . 9 . 9 1-3-1 نوار عنوانTitle Bar 9 1-3-2 نوار منو Menu Bar 10 1-3-3 نوارهاي ابزارToolbars. 10 1-3-3-1 نوار ابزار استاندارد. 10 1-3-4 خط كشRuler. 11 1-3-5 محيط تايپ (Text Area). 12 1-3-6 نوار وضعيت (Status Bar). 12 1-3-7 نوارهاي پيمايش افقي(Horizontal) و عمودي(Vertical). 12 1-4 آشنايي با ايجاد سند جديد. 13 1-5 آشنايي با چگونگی باز نمودن سند موجود. 13 1-6 آشنايي با ذخيره کردن سند فعلي با فرمتهای گوناگون. 14 1-7 آشنايی با اصول ويرايش متن. . 14 1-7-1 آشنايي با چگونگی انتخاب متن (Highlighting Text ). 15 1-7-2 شناسايي اصول کپی، بريدن، چسباندن و حذف متن. . 16 1-7-3 برش متن(Cut). 16 1-7-4 كپي متن (Copy). 16 1-7-5 چسباندن متن(Paste). 16 1-7-6 حذف متن. . 17 1-7-7 رنگ زمينه قلم (Highlight). 17 1-7-8 رنگ قلم (Font Color). 17 1-7-9 آشنايي با استفاده از دستور برگشت... 17 1-7-10 آشنايي با نحوه ضخيم و پررنگ کردن متن انتخاب شده Bold)). 17 1-7-11 آشنايي با نحوه زير خط دار کردن متن انتخاب شده (Underline). 17 1-7-12 آشنايي با نحوه مايل و ايتاليك کردن متن انتخاب شده (Italic). 17 1-7-13 آشنايي با ابزار چيدمان. . 18 1-8 شناسايي اصول تنظيم قلم و اندازه قلم. 18 . . 19 . . 19 1-8-2 برگه Character Spacing (برگه دوم از... --- - Published: 1404-05-14 - Modified: 1404-05-14 - URL: https://tirotir.ir/%db%b3-%d8%a7%db%8c%d9%86%d8%aa%d8%b1%d9%86%d8%aa-icdl/ - دسته‌ها: ICDL - برچسب‌ها: ICDL آموزشگاه هوش مصنوعی ۳۰ مورد مبانی و مفاهیم اولیه مربوط به آموزش اینترنت 1- مفاهیم پایه اینترنت تعریف اینترنت و تفاوت آن با شبکه های محلی (LAN, WAN) آشنایی با مفهوم مرورگر وب (Browser) و انواع آن (Chrome, Firefox, Edge) تعریف URL و بخش های آن (پروتکل، دامنه، مسیر(: https://whatismyipaddress. com مفهوم موتور جستجو (Google, Bing, Yahoo) و نحوه استفاده از آن معرفی وب سایت و تفاوت آن با وب پیج آشنایی با ایمیل و نحوه ایجاد یک حساب ایمیل (Gmail, Yahoo) تعریف مفهوم دانلود و آپلود فایل مفهوم لینک (Hyperlink) و نحوه استفاده از آن معرفی پروتکل های اصلی (HTTP, HTTPS) تعریف شبکه های اجتماعی و نمونه هایی از آن ها (Facebook, Instagram, Twitter) 2- ارتباط و امنیت در اینترنت مفهوم آدرس IP و نحوه کارکرد آن معرفی DNS و نقش آن در ترجمه آدرس ها آشنایی با Wi-Fi و شبکه های بی سیم تعریف VPN و کاربرد آن در امنیت و دسترسی اهمیت رمزگذاری (Encryption) در اینترنت روش های ایمن سازی اطلاعات شخصی در اینترنت مفهوم کوکی ها و استفاده از آن ها توسط وب سایت ها شناسایی وب سایت های امن) قفل سبز - HTTPS) اصول مدیریت رمز عبور و استفاده از ابزارهای مدیریت رمز مفهوم فیشینگ و نحوه جلوگیری از آن 3- ابزارها و خدمات اینترنتی استفاده از سرویس های ذخیره سازی ابری (Google Drive, Dropbox) معرفی و نحوه استفاده از نقشه های آنلاین (Google Maps) مفهوم استریمینگ و خدمات آن (YouTube, Netflix) نحوه خرید آنلاین و پرداخت های اینترنتی معرفی موتورهای جستجوی تخصصی (Scholar, DuckDuckGo)... --- - Published: 1404-05-14 - Modified: 1404-05-14 - URL: https://tirotir.ir/%d8%aa%d8%b9%d8%b1%db%8c%d9%81-icdl-%d9%85%d9%87%d8%a7%d8%b1%d8%aa%d9%87%d8%a7%db%8c-%d9%87%d9%81%d8%aa%da%af%d8%a7%d9%86%d9%87-%da%a9%d8%a7%d9%85%d9%be%db%8c%d9%88%d8%aa%d8%b1/ - دسته‌ها: ICDL - برچسب‌ها: ICDL تعریف ICDL مهارت های هفت گانه کامپیوتر ICDL مخفف International Computer Driving License به معنای «گواهینامه بین المللی کاربری کامپیوتر» است. این استاندارد بین المللی برای یادگیری مهارت های اولیه استفاده از کامپیوتر طراحی شده و در هفت مهارت اصلی دسته بندی می شود. مهارت های هفت گانه ICDL مفاهیم پایه فناوری اطلاعات Basic Concepts of ITآشنایی با مفاهیم اولیه فناوری اطلاعات، سخت افزار، نرم افزار، شبکه ها و امنیت داده ها. مثال آشنایی با انواع کامپیوترها، سیستم عامل ها، و کاربرد اینترنت. استفاده از کامپیوتر و مدیریت فایل ها Using Computer and Managing Filesآموزش نحوه کار با سیستم عامل مانند ویندوز، مدیریت فایل ها و پوشه ها، و آشنایی با تنظیمات اصلی سیستم. مثال ایجاد پوشه، کپی و انتقال فایل ها. واژه پردازی Word Processingاستفاده از نرم افزارهای ویرایش متن مانند Microsoft Word برای ایجاد، ویرایش، و قالب بندی اسناد. مثال نوشتن نامه، ایجاد جدول و قالب بندی متن. صفحات گسترده Spreadsheetsکار با نرم افزارهایی مثل Microsoft Excel برای مدیریت داده ها، ایجاد جداول، فرمول نویسی و تحلیل اطلاعات. مثال محاسبه حقوق و دستمزد یا ایجاد نمودار. پایگاه های داده Databaseاستفاده از نرم افزارهای پایگاه داده مثل Microsoft Access برای ذخیره و مدیریت داده ها. مثال ایجاد پایگاه داده مشتریان یک شرکت. ارائه مطالب Presentationکار با نرم افزارهایی مثل Microsoft PowerPoint برای طراحی و ارائه اسلایدهای حرفه ای. مثال ارائه گزارش ها و پروژه ها. اطلاعات و ارتباطات Information and Communicationاستفاده از اینترنت، ایمیل، و ابزارهای ارتباطی آنلاین برای جستجو، ارسال و دریافت اطلاعات. مثال جستجوی گوگل، ارسال ایمیل،... --- - Published: 1404-05-14 - Modified: 1404-05-15 - URL: https://tirotir.ir/%d8%a2%d8%b2%d9%85%d9%88%d9%86-%d8%b9%d9%85%d9%84%db%8c-word/ - دسته‌ها: ICDL آموزشگاه هوش مصنوعی 1- ایجاد یک سند جدید یک سند جدید باز کرده و نام آن را به tirotir1. docx ذخیره کنید. 2- تنظیمات فونت متنی را تایپ کنید و سپس فونت آن را به B Nazanin تغییر داده و اندازه را روی ۱۴ تنظیم کنید. 3- اعمال سبک (Styles) عنوانی بنویسید و از استایل Heading 1 برای آن استفاده کنید. 4- تراز بندی متن متنی را در وسط (Center) و متنی دیگر را در راست (Right) تراز کنید. 5- ایجاد لیست شماره ای یک لیست شماره ای با ۵ آیتم ایجاد کنید، مثل: نام نام خانوادگی شماره تماس 6- ایجاد لیست بولت دار (Bulleted List) یک لیست بولت دار برای اقلام خرید بنویسید، مثل: نان شیر تخم مرغ 7- تنظیم فاصله خطوط (Line Spacing) فاصله خطوط را برای یک پاراگراف روی ۱. ۵ تنظیم کنید. 8- اضافه کردن تصویر یک تصویر دلخواه را به سند وارد کرده و اندازه آن را تغییر دهید. 9- ایجاد جدول ساده یک جدول ۳ در ۵ برای ثبت اطلاعات (نام، سن، شماره تماس) ایجاد کنید. 10- اضافه کردن حاشیه به صفحه (Page Borders) به سند خود یک حاشیه ساده اضافه کنید. 11- تنظیم سرصفحه و پاصفحه (Header and Footer) در سرصفحه، نام سند را تایپ کنید و در پاصفحه شماره صفحه اضافه کنید. 12- ایجاد یک متن با رنگ سفارشی متنی تایپ کنید و رنگ آن را به آبی تغییر دهید. 13- استفاده از Bold، Italic، Underline یک متن کوتاه تایپ کنید و سپس آن را بولد، ایتالیک و زیرخط دار کنید. 14-... --- - Published: 1404-05-14 - Modified: 1404-05-14 - URL: https://tirotir.ir/%db%b2-%d8%a2%d9%85%d9%88%d8%b2%d8%b4-%d8%b3%d9%8a%d8%b3%d8%aa%d9%85-%d8%b9%d8%a7%d9%85%d9%84-%d9%88%d9%8a%d9%86%d8%af%d9%88%d8%b2-icdl/ - دسته‌ها: ICDL - برچسب‌ها: ICDL آموزشگاه هوش مصنوعی آموزش سيستم عامل ويندوز - مهارت دوم از ICDL ( استفاده از کامپيوتر و مديريت فايل ها ) آشنايي با سيستم كامپيوتر قاعده نامگذاری درايوها:   تمرين) کامپيوتر يک اداره دارای ديسک گردانهای فلاپی، ديسک سخت و ديسک نوری می باشد، نام اختصاری ديسک گردانها(درايوها) را نام ببريد. FLOPPY DRIVEA:فلاپی اضافی(رزرو شده)B:HARD DISK DRIVEC:CD-ROM DRIVED:   نکته)توسط دستورات خاص نرم افزاری می توان ديسک سخت را طوری قسمت بندی(پارتيشن بندی) نمود که هر قسمت آن همانند يک قسمت مستقل عمل نمايد.  در چنين حالتی بايد توجه داشت که آن قسمتها، با رعايت ترتيب الفبای انگليسی، نامگذاری شده و حرفی پس از آخرين قسمت ديسک سخت، نام  سی دی (CD)خواهد بود.   تمرين) کامپيوتر يک مدرسه دارای ديسک گردانهای فلاپی، ديسک سخت 3 قسمتی و ديسک نوری می باشد، نام اختصاری ديسک گردانها(درايوها) را نام ببريد. FLOPPY DRIVEA:فلاپی اضافی(رزرو شده)B:  HARD DISK DRIVEC:D:E:CD-ROM DRIVEF:   تمرين) کامپيوتر يک مدرسه دارای ديسک گردانهای فلاپی، ديسک سخت 5 قسمتی و ديسک نوری و دستگاهCD-WRITER می باشد، نام اختصاری ديسک گردانها(درايوها) را نام ببريد. FLOPPY DRIVEA:فلاپی اضافی(رزرو شده)B:  HARD DISK DRIVEC:D:E:F:G:CD-ROM DRIVEH:CD-WRITERI:  مفهوم و کاربرد فايل و پوشه دفتردار يک مدرسه را در نظر بگيريد، او برای هر محصل يک پوشه قرار داده و نام آن محصل را روی آن می نويسد، سپس برخی اسناد متنی(مثلاً کپی شناسنامه) و اسناد تصويری(مثلاً عکس) و ... را از آن محصل درخواست نموده و در آن پوشه قرار می دهد و اين پوشه را در کشو و قفسه خاصی قرار داده و ذخيره می... --- - Published: 1404-05-14 - Modified: 1404-05-14 - URL: https://tirotir.ir/%db%b1-%d9%85%d9%81%d8%a7%d9%87%d9%8a%d9%85-%d8%a7%d9%88%d9%84%d9%8a%d9%87-%d9%88-%d8%a7%d8%b3%d8%a7%d8%b3%db%8c-%da%a9%d8%a7%d9%85%d9%be%d9%8a%d9%88%d8%aa%d8%b1-icdl/ - دسته‌ها: ICDL - برچسب‌ها: ICDL 1 آموزشگاه هوش مصنوعی tirotir. ir مفاهيم اوليه و اساسی کامپيوتر  تعريف و مزايای کامپيوتر: شما با تلويزيون خود آشنايي داريد، و ممکن است که به آن تا حدودی وابسته باشيد! تلويزيون رايج ترين دستگاه خروجی محسوب می شود. اين بدين معنی است که از تلويزيون مطالبی پخش شده و شما احتمالاً از آن استفاده نموده ايد.  از طريق دستگاه کنترل می توان به تلويزيون ورودی داد،به عنوان مثال کانالها را تغيير داده، صدا، رنگ و برخی موارد ديگر را عوض نمود. در واقع منظور از اصطلاح خروجی يعنی گردش اطلاعات به سمت شما و ورودی يعنی گردش اطلاعات از سوی شما به يک دستگاه خاص. کامپيوتر يک دستگاه الکترونيکی است که روی موضوعاتی که به آن می دهيم(از طريق واحد ورودی) کار کرده و اطلاعات موردنظر را ارايه می نمايد(توسط واحد پردازش). قسمتهای مختلف کامپيوتر: قسمتهايي که ورودی را دريافت می نمايند. قسمتهايي که روی موضوعات ورودی عملياتی خاص انجام می دهند. قسمتهايي که خروجی را ارايه می نمايند. قسمتهايي که مطالب و موضوعات را حتی هنگام خاموشی کامپيوتر، ذخيره و نگهداری می نمايند. برخی مزايای کامپيوتر عبارتند از : سرعت، اطمينان، دقت ، حافظه بالا و ... در شکل فوق واحدهای ورودی، پردازش و خروجی را نام ببريد.  آشنايي با انواع کامپيوترهای شخصی: 1. کامپيوتر روميزی 2. کامپيوتر قابل حمل (لپ تاپ) کامپيوتر هايي می باشند که بطور كامل درونی مخصوص قرار گرفته و قابل حمل و جابجايي هستند. اين کامپيوترها نسبت به نوع معمولی، بسيار گران می باشند. آشنايي با علوم کامپيوتر: سخت افزار(HARDWARE) آنچه از کامپيوتر... --- - Published: 1404-05-13 - Modified: 1404-05-13 - URL: https://tirotir.ir/visual-understanding-unlocking-the-next-frontier-in-ai/ - دسته‌ها: other At the NYC AIAI Summit, Joseph Nelson, CEO & Co-Founder of Roboflow, took the stage to spotlight a critical but often overlooked frontier in AI: vision. In a field dominated by breakthroughs in language models, Nelson argued that visual understanding – or how machines interpret the physical world – is just as essential for building intelligent systems that can operate in real-world conditions. From powering instant replay at Wimbledon to enabling edge-based quality control in electric vehicle factories, his talk offered a grounded look at how visual AI is already transforming industries – and what it will take to make it truly robust, accessible, and ready for anything. Roboflow now supports a million developers. Nelson walked through what some of them are building: real-world, production-level applications of visual AI across industries, open-source projects, and more. These examples show that visual understanding’s already being deployed at scale. Three key themes in visual AI today Nelson outlined three major points in his talk: The long tails of computer vision. In visual AI, long-tail edge cases are a critical constraint. These rare or unpredictable situations limit the ability of models, including large vision-language models, to fully understand the real world. What the future of visual models looks like. A central question is whether one model will eventually rule them all, or whether the future lies in a collection of smaller, purpose-built models. The answer will shape how machine learning is applied to visual tasks going forward. Running real-time visual AI at the edge.... --- - Published: 1404-05-10 - Modified: 1404-05-10 - URL: https://tirotir.ir/how-agentic-ai-is-transforming-healthcare-delivery/ - دسته‌ها: other In the Agents of Change podcast, host Anthony Witherspoon welcomes Archie Mayani, Chief Product Officer at GHX (Global Healthcare Exchange), to explore the vital role of artificial intelligence (AI) in healthcare. GHX is a company that may not be visible to the average patient, but it plays a foundational role in ensuring healthcare systems operate efficiently. As Mayani describes it, GHX acts as "an invisible operating layer that helps hospitals get the right product at the right time, and most importantly, at the right cost. " GHX’s mission is bold and clear: to enable affordable, quality healthcare for all. While the work may seem unglamorous, focused on infrastructure beneath the surface, it is, in Mayani’s words, “mission critical” to the healthcare system. Pioneering AI in the healthcare supply chain AI has always been integral to GHX’s operations, even before the term became a buzzword. Mayani points out that the company was one of the early adopters of technologies like Optical Character Recognition (OCR) within healthcare supply chains, long before such tools were formally labeled as AI. This historical context underlines GHX’s longstanding commitment to innovation. Now, with the rise of generative AI and agentic systems, the company’s use of AI has evolved significantly. These advancements are being harnessed for: Predicting medical supply shortages Enhancing contract negotiations for health systems Improving communication between clinicians and supply chain teams using natural language interfaces All of these tools are deployed in service of one goal: to provide value-based outcomes and affordable care to... --- - Published: 1404-05-06 - Modified: 1404-05-06 - URL: https://tirotir.ir/how-ai-is-redefining-cyber-attack-and-defense-strategies/ - دسته‌ها: other As AI reshapes every aspect of digital infrastructure, cybersecurity has emerged as the most critical battleground where AI serves as both weapon and shield. The cybersecurity landscape in 2025 represents an unprecedented escalation in technological warfare, where the same AI capabilities that enhance organizational defenses are simultaneously being weaponized by malicious actors to create more sophisticated, automated, and evasive attacks. The stakes have never been higher. Recent data from the CFO reveals that 87% of global organizations faced AI-powered cyberattacks in the past year, while the AI cybersecurity market is projected to reach $82. 56 billion by 2029, growing at a compound annual growth rate of 28% . This explosive growth reflects not just market opportunity, but an urgent response to threats that are evolving faster than traditional security measures can adapt. Part 1: Adversaries in the age of AI Cyber adversaries have found a powerful new weapon in AI, and they're using it to rewrite the offensive playbook. The game has changed, with attacks now defined by automated deception, hyper-realistic social engineering, and intelligent malware that thinks for itself. The industrialization of deception The old security advice - "spot the typo, spot the scam" - is officially dead. Generative AI now crafts flawless, hyper-personalized phishing emails, texts, and voice messages that are devastatingly effective. The numbers tell a chilling story: AI-generated phishing emails boast a 54% click-through rate, dwarfing the 12% from human-written messages. Meanwhile, an estimated 80% of voice phishing (vishing) attacks now use AI to clone voices,... --- - Published: 1404-04-30 - Modified: 1404-04-30 - URL: https://tirotir.ir/ai-and-the-future-of-international-student-outreach/ - دسته‌ها: other My daily work in the EdTech industry consists of constant back-and-forth comparison between the United Kingdom’s admissions machine and the digital experiences offered at higher education systems elsewhere. While UK universities debate workflow changes, universities in competing nations are plugging mass-scale AI systems directly into recruitment and immigration processes. Unless we get similar equipment to work for us, ethically and at sector scale, the recent drop in foreign applications might be the beginning of a longer fall. Global competition is accelerating In March 2024, Reuters wrote that Microsoft and OpenAI are mulling a $100 billion U. S. super-computer project called Stargate to train the next generation of language models. Faster models translate to richer, more personalized student-facing services: anything from adaptive test preparation to multilingual visa counseling. On the demand side, UNESCO’s 2024/5 Global Education Monitoring Report suggests that cross-border tertiary enrolments will rise by some two million seats by 2030, driven by South Asia and Sub-Saharan Africa most of all. Potential students in these nations do much of their research online and respond quickly to chat-based counsel. It’s the perfect setting for today’s language models. UK Government prioritizes AI for economic growth and services The UK places AI at the center of its strategy for economic growth and improved public services, led by Science Secretary Peter Kyle. AI Accelerator InstituteMarisa Garanhel Home-grown headwinds The UK, on the other hand, has done the reverse. From 1 January 2024, the majority of international students will have the right to bring dependents... --- - Published: 1404-04-27 - Modified: 1404-04-27 - URL: https://tirotir.ir/how-large-language-models-are-transforming-pediatric-healthcare/ - دسته‌ها: other What if artificial intelligence could help us solve some of the most complex challenges in pediatric healthcare, especially when it comes to rare diseases? At Great Ormond Street Hospital (GOSH), we face these challenges daily, treating children with some of the most difficult and rare conditions imaginable. But as powerful as human expertise is, we often find ourselves dealing with an overwhelming amount of data, from patient histories to diagnostic reports, making it hard to extract the insights we need quickly and efficiently. This is where artificial intelligence and machine learning come in. These technologies have the potential to revolutionize the way we process and utilize healthcare data. At GOSH, we’re leveraging AI, particularly large language models (LLMs), to tackle the complexity of this data and improve patient outcomes. In this article, I’ll share insights from our journey of integrating AI into pediatric healthcare at GOSH and how AI is helping us improve care, streamline operations, and make healthcare more accessible for children with rare diseases. Let’s dive in. The role of GOSH’s DRIVE unit In 2018, we established the DRIVE unit, which stands for Data, Research, Innovation, and Virtual Environment. Our goal? To harness data and technology to improve outcomes for children, families, and our healthcare staff. We want to make GOSH the global go-to center for pediatric innovation, and we aim to do this by utilizing AI and data to drive breakthroughs in treatment, diagnosis, and patient care. Our mission goes beyond merely innovating for the sake of... --- - Published: 1404-04-19 - Modified: 1404-04-19 - URL: https://tirotir.ir/humans-in-the-loop-how-leading-companies-are-building-practical-trustworthy-ai/ - دسته‌ها: other At the NYC Generative AI Summit, experts from Wayfair, Morgan & Morgan, and Prolific came together to explore one of AI’s most pressing questions: how do we balance the power of automation with the necessity of human judgment? From enhancing customer service at scale to navigating the complexity of legal workflows and optimizing human data pipelines, the panelists shared real-world insights into deploying AI responsibly. In a field moving at breakneck speed, this discussion was an opportunity to examine how we can build AI systems that are effective, ethical, and enduring. From support to infrastructure: Evolving with generative AI Generative AI is reshaping industries at a pace few could have predicted. And at Wayfair, that pace is playing out in real time. Vaidya Chandrasekhar, who leads pricing, competitive intelligence, and catalog ML algorithms at the company, shared how their approach to generative AI has grown from practical customer support tools to foundational infrastructure transformation. Early experiments started with agent assistance, particularly in customer service. These included summarizing issue histories and providing real-time support to customer-facing teams, the kind of use cases many companies have used as a generative AI entry point. From there, Wayfair moved into more technical territory. One significant area has been technology transformation: shifting from traditional SQL stored procedures toward more dynamic systems. “We’ve been asking questions like, ‘if you're selecting specific data points and trying to understand your data model’s ontology, what would that look like as a GraphQL query? ’” Vaidya explained. While not all... --- - Published: 1404-04-18 - Modified: 1404-04-18 - URL: https://tirotir.ir/llmops-in-action-streamlining-the-path-from-prototype-to-production-2/ - دسته‌ها: other AIAInow is your chance to stream exclusive talks and presentations from our previous events, hosted by AI experts and industry leaders. It's a unique opportunity to watch the most sought-after AI content – ordinarily reserved for AIAI Pro members. Each stream delves deep into a key AI topic, industry trend, or case study. Simply sign up to watch any of our upcoming live sessions. Access exclusive talks and presentations Develop your understanding of key topics and trends Hear from experienced AI leaders Enjoy regular in-depth sessions Sign up now LLMOps is emerging as a critical enabler for organizations deploying large language models at scale - bringing data scientists, engineers, and end-users into tighter, more effective collaboration. Join us for a deep dive into the operational backbone of successful LLM deployments. From model design to monitoring in production, you’ll learn how to unlock the full potential of LLMs with streamlined processes, smarter tooling, and cross-functional alignment. In this session, you’ll explore: What LLMOps is - and why it’s essential for scalable AI success The full LLMOps lifecycle: from experimentation to deployment and iteration How to accelerate collaboration between data teams, engineers, and business users Practical frameworks and tools for building robust LLM pipelines Real-world case studies showcasing high-impact LLM applications Common challenges in LLMOps - and how to overcome them Whether you're an AI practitioner, developer, or team leader, this session will equip you with the insights and strategies to operationalize LLMs with confidence. Meet the speaker: Samin Alnajafi, AI Solutions... --- - Published: 1404-04-13 - Modified: 1404-04-13 - URL: https://tirotir.ir/how-to-optimize-llm-performance-and-output-quality-a-practical-guide/ - دسته‌ها: other Have you ever asked generative AI the same question twice – only to get two very different answers? That inconsistency can be frustrating, especially when you're building systems meant to serve real users in high-stakes industries like finance, healthcare, or law. It’s a reminder that while foundation models are incredibly powerful, they’re far from perfect. The truth is, large language models (LLMs) are fundamentally probabilistic. That means even slight variations in inputs – or sometimes, no variation at all – can result in unpredictable outputs. Combine that with the risk of hallucinations, limited domain knowledge, and changing data environments, and it becomes clear: to deliver high-quality, reliable AI experiences, we must go beyond the out-of-the-box setup. So in this article, I’ll walk you through practical strategies I’ve seen work in the field to optimize LLM performance and output quality. From prompt engineering to retrieval-augmented generation, fine-tuning, and even building models from scratch, I’ll share real-world insights and analogies to help you choose the right approach for your use case. Whether you’re deploying LLMs to enhance customer experiences, automate workflows, or improve internal tools, optimization is key to transforming potential into performance. Let’s get started. The problem with LLMs: Power, but with limitations LLMs offer immense potential – but they’re far from perfect. One of the biggest pain points is the variability in output. As I mentioned, because these models are probabilistic, not deterministic, even the same input can lead to wildly different outputs. If you’ve ever had something work perfectly... --- - Published: 1404-04-12 - Modified: 1404-04-12 - URL: https://tirotir.ir/human-ai-rethinking-the-roles-and-skills-of-knowledge-workers/ - دسته‌ها: other Artificial intelligence is not just another gadget; it’s already shaking up how white-collar jobs work. McKinsey calls this shift an arrival at superagency, a space where machines think alongside people and the two groups spark new bursts of creativity and speed. Suddenly, the click-by-click chores-plowing through code, crunching spreadsheets, scrubbing datasets-are handled by bots, letting human brains leap to bigger questions. Software developers, for instance, now spend more energy sketching big-picture road maps than wrestling syntax errors. Data scientists swap grinding model tweaks for debating which human questions an AI model really answers. In every corner of knowledge work, the quiet obey-yesterday-tasks face is evaporating. The revamped role of the knowledge worker is equal parts translator, coach, and ethical guardian. Successful pros read the business landscape, nudge AI tools in the right direction, and steer output so it stays inside value lines. Human judgment steps in when computers run out of context, making it the real superpower of the partnership. Some experts have taken to calling us AI strategists, a pivot away from the older task executor label. We use machines as sturdy scaffolding, letting us build fresher ideas faster while keeping accountability firmly in hand. Skills for human-AI collaboration Living in a world that teams up humans and machines is no longer a sci-fi plot; it’s the daily grind for millions. A recent World Economic Forum report warns that nearly 39% of the skills we brag about on our resumes will be different by 2030, and tech is doing... --- - Published: 1404-04-11 - Modified: 1404-04-11 - URL: https://tirotir.ir/turning-structured-data-into-roi-with-genai/ - دسته‌ها: other At GigaSpaces, we've been in the data management game for over twenty years. We specialize in mission-critical, real-time software solutions, and over the past two decades, we’ve seen just how essential structured data is, whether it resides in a traditional database, an Excel sheet, or a humble CSV file. Every company, regardless of its size or industry, relies on structured data. Maybe it’s the bulk of their operations, maybe just a slice, but either way, the need for fast, reliable access to that data is universal. Of course, what “real-time” means varies depending on the business. For some, it’s milliseconds; for others, hours might do. However, the expectation remains the same: access must be seamless, fast, and dependable. The reality of enterprise data management Let’s talk about the real challenge: enterprise data is hard to work with. Even when structured, it’s often fragmented across systems, stored in outdated databases, or locked behind poorly configured infrastructure. Many organizations are still running on databases built twenty or thirty years ago. And as anyone who’s tried knows, fixing those systems is a monumental task, often one attempted only once and never repeated. Once bitten, twice shy. So, how do we give business users the access they need without overhauling everything? That’s where things get complicated. Enterprises have layered on workaround after workaround: ETL pipelines, data warehouses, operational data stores, data lakes, caching layers, you name it. Each is a patch or workaround designed to move, manipulate, and surface data for reporting or analysis.... --- - Published: 1404-04-09 - Modified: 1404-04-09 - URL: https://tirotir.ir/how-tigereye-is-redefining-ai-powered-business-intelligence/ - دسته‌ها: other At the Generative AI Summit in Silicon Valley, Ralph Gootee, Co-founder of TigerEye, joined Tim Mitchell, Business Line Lead, Technology at the AI Accelerator Institute, to discuss how AI is transforming business intelligence for go-to-market teams. In this interview, Ralph shares lessons learned from building two companies and explores how TigerEye is rethinking business intelligence from the ground up with AI, helping organizations unlock reliable, actionable insights without wasting resources on bespoke analytics. Tim Mitchell: Ralph, it’s a pleasure to have you here. We’re on day two of the Generative AI Summit, part of AI Silicon Valley. You're a huge part of the industry in Silicon Valley, so it’s amazing to have you join us. TigerEye is here as part of the event. Maybe for folks that aren’t familiar with the brand, you can just give a quick rundown of who you are and what you’re doing. Ralph: I’m the co-founder of TigerEye – my second company. It’s exciting to be solving some of the problems we had with our first company, PlanGrid, in this one. We sold PlanGrid to Autodesk. I had a really good time building it. But when you’re building a company, you end up having many internal metrics to track, and a lot of things that happen with sales. So, we built a data team. With TigerEye, we’re using AI to help build that data team for other companies, so they can learn from our past mistakes. We’re helping them build business intelligence that’s meant for... --- - Published: 1404-04-07 - Modified: 1404-04-06 - URL: https://tirotir.ir/why-agentic-ai-pilots-fail-and-how-to-scale-safely/ - دسته‌ها: other At the AI Accelerator Institute Summit in New York, Oren Michels, Co-founder and CEO of Barndoor AI, joined a one-on-one discussion with Alexander Puutio, Professor and Author, to explore a question facing every enterprise experimenting with AI: Why do so many AI pilots stall, and what will it take to unlock real value? Barndoor AI launched in May 2025. Its mission addresses a gap Oren has seen over decades working in data access and security: how to secure and manage AI agents so they can deliver on their promise in enterprise settings. “What you’re really here for is the discussion about AI access,” he told the audience. “There’s a real need to secure AI agents, and frankly, the approaches I’d seen so far didn’t make much sense to me. ” AI pilots are being built, but Oren was quick to point out that deployment is where the real challenges begin. As Alexander noted: “If you’ve been around AI, as I know everyone here has, you’ve seen it. There are pilots everywhere... ” Why AI pilots fail Oren didn’t sugarcoat the current state of enterprise AI pilots: “There are lots of them. And many are wrapping up now without much to show for it. ” Alexander echoed that hard truth with a personal story. In a Forbes column, he’d featured a CEO who was bullish on AI, front-loading pilots to automate calendars and streamline doctor communications. But just three months later, the same CEO emailed him privately: “Alex, I need to... --- - Published: 1404-04-04 - Modified: 1404-04-04 - URL: https://tirotir.ir/aiai-new-york-2025/ - دسته‌ها: other Catch up on every session from the AIAI New York with sessions across 3 co-located summit featuring the likes of Meta, Bank of America, Google DeepMind and many more. --- - Published: 1404-03-31 - Modified: 1404-03-31 - URL: https://tirotir.ir/llmops-in-action-how-we-move-genai-from-prototype-to-production/ - دسته‌ها: other Struggling to get your GenAI prototype into production? Discover how LLMOps helps streamline deployment – fast, scalable, and reliable. --- - Published: 1404-03-27 - Modified: 1404-03-27 - URL: https://tirotir.ir/llmops-virtual-summit-may-2025/ - دسته‌ها: other Catch up on every session from LLMOps Virtual Summit, with sessions from the likes of Google, Unicef, Capital One, Linkedin and more... --- - Published: 1404-03-27 - Modified: 1404-03-27 - URL: https://tirotir.ir/cap-theorem-in-ml-consistency-vs-availability/ - دسته‌ها: other The CAP theorem has long been the unavoidable reality check for distributed database architects. However, as machine learning (ML) evolves from isolated model training to complex, distributed pipelines operating in real-time, ML engineers are discovering that these same fundamental constraints also apply to their systems. What was once considered primarily a database concern has become increasingly relevant in the AI engineering landscape. Modern ML systems span multiple nodes, process terabytes of data, and increasingly need to make predictions with sub-second latency. In this distributed reality, the trade-offs between consistency, availability, and partition tolerance aren't academic — they're engineering decisions that directly impact model performance, user experience, and business outcomes. This article explores how the CAP theorem manifests in AI/ML pipelines, examining specific components where these trade-offs become critical decision points. By understanding these constraints, ML engineers can make better architectural choices that align with their specific requirements rather than fighting against fundamental distributed systems limitations. Quick recap: What is the CAP theorem? The CAP theorem, formulated by Eric Brewer in 2000, states that in a distributed data system, you can guarantee at most two of these three properties simultaneously: Consistency: Every read receives the most recent write or an error Availability: Every request receives a non-error response (though not necessarily the most recent data) Partition tolerance: The system continues to operate despite network failures between nodes Traditional database examples illustrate these trade-offs clearly: CA systems: Traditional relational databases like PostgreSQL prioritize consistency and availability but struggle when network partitions occur.... --- - Published: 1404-03-23 - Modified: 1404-03-23 - URL: https://tirotir.ir/how-to-build-autonomous-ai-agent-with-google-a2a-protocol/ - دسته‌ها: other Why do we need autonomous AI agents? Picture this: it’s 3 a. m. , and a customer on the other side of the globe urgently needs help with their account. A traditional chatbot would wake up your support team with an escalation. But what if your AI agent could handle the request autonomously, safely, and correctly? That’s the dream, right? The reality is that most AI agents today are like teenagers with learner’s permits; they need constant supervision. They might accidentally promise a customer a large refund (oops! ) or fall for a clever prompt injection that makes them spill company secrets or customers’ sensitive data. Not ideal. This is where Double Validation comes in. Think of it as giving your AI agent both a security guard at the entrance (input validation) and a quality control inspector at the exit (output validation). With these safeguards at a minimum in place, your agent can operate autonomously without causing PR nightmares. How did I come up with the Double Validation idea? These days, we hear a lot of talk about AI agents. I asked myself, "What is the biggest challenge preventing the widespread adoption of AI agents? " I concluded that the answer is trustworthy autonomy. When AI agents can be trusted, they can be scaled and adopted more readily. Conversely, if an agent’s autonomy is limited, it requires increased human involvement, which is costly and inhibits adoption. Next, I considered the minimal requirements for an AI agent to be autonomous. I concluded... --- - Published: 1404-03-19 - Modified: 1404-03-19 - URL: https://tirotir.ir/building-securing-ai-agents-a-tech-leader-crash-course/ - دسته‌ها: other The AI revolution is racing beyond chatbots to autonomous agents that act, decide, and interface with internal systems. Unlike traditional software, AI agents can be manipulated through language, making them vulnerable to attacks like prompt injection and they also introduce new security risks like excessive agency. Join us for an exclusive deep dive with Sourabh Satish, CTO and co-founder at Pangea, as we explore the evolving landscape of AI agents and best practices for securing them. This session covers: Demos of MCP configuration and vulnerabilities to highlight how different architectures affect the agent’s attack surface. An overview of existing security guardrails—from open source projects and cloud service provider offerings to commercial tools and DIY approaches. A comparison of pros and cons across various guardrail solutions to help you choose the right approach for your use case. Actionable best practices for implementing guardrails that secure your AI agents without slowing innovation. This webinar is a must-attend for engineering leaders, AI engineers, and security leaders who want to understand and mitigate the risks of agentic software in an increasingly adversarial landscape. --- - Published: 1404-03-16 - Modified: 1404-03-16 - URL: https://tirotir.ir/what-exactly-is-an-ai-agent-and-how-do-you-build-one/ - دسته‌ها: other What makes something an "AI agent" – and how do you build one that does more than just sound impressive in a demo? I'm Nico Finelli, Founding Go-To-Market Member at Vellum. Starting in machine learning, I’ve consulted for Fortune 500s, worked at Weights & Biases during the LLM boom, and now I help companies get from experimentation to production with LLMs, faster and smarter. In this article, I’ll unpack what AI agents actually are (and aren't), how to build them step by step, and what separates teams that ship real value from those that stall out in proof-of-concept purgatory. We'll also take a close look at the current state of AI adoption, the biggest challenges teams face today, and the one thing that makes or breaks an agent system: evaluation. Let’s dive in. Where we are in the AI landscape At Vellum, we recently partnered with Weaviate and LlamaIndex to run a survey of over 1,200 AI developers. The goal? To understand where people are when it comes to deploying AI in production. What we found was pretty surprising: only 25% of respondents said they were live in production with their AI initiative. For all the hype around generative AI, most teams are still stuck in experimentation mode. The biggest blocker? Hallucinations and prompt management. Over 57% of respondents said hallucinations were their number one challenge. And here's the kicker: when we cross-referenced that with how people were evaluating their systems, we noticed a pattern. The same folks struggling with... --- - Published: 1404-03-15 - Modified: 1404-03-15 - URL: https://tirotir.ir/the-future-of-iot-is-agentic-and-autonomous/ - دسته‌ها: other According to recent Cisco research, it's projected that by 2028, 68% of all customer service and support interactions with tech vendors will be handled by agentic AI. This makes sense, as 93% of respondents in the same study predict that a more personalized, predictive, and proactive service will be possible with agentic AI. Agentic AI represents a departure from traditional automation, as it enables AI agents to act independently, make decisions with minimal human input, and learn from context. Earlier systems required humans to connect and monitor the automated workflows. However, agentic AI agents have reasoning abilities, memory, and task awareness. Because agentic AI can enhance both the operation and management of interconnected devices, this development is particularly relevant to the IoT (Internet of Things). It can proactively address network issues that originate from misconfigurations, which results in stronger security, smarter networks, and more productive teams. This theme takes center stage at Agentic AI Summit New York on June 5, in the session led by Capital One’s Srinath Godavarthi on ‘Agentic AI: The next frontier of generative AI... from simple tasks to goal-oriented autonomy’. Agentic AI vs. traditional AI: A structural shift Agentic AI introduces an essential shift in how intelligent systems are architected and deployed, transitioning from task-specific and supervised models to autonomous and goal-oriented agents that can make real-time decisions and adapt to their environment. Intelligence is mainly static and narrowly scoped in traditional AI systems; models are trained offline and embedded into rule-based workflows, usually operating in... --- - Published: 1404-03-12 - Modified: 1404-03-12 - URL: https://tirotir.ir/building-efficient-data-pipelines-for-ai-and-nlp-applications-in-aws/ - دسته‌ها: other Advanced AI and NLP applications are in great demand in today’s modern world, wherein most businesses rely on data-driven insights and automation of business processes. All applications of AI or NLP have a requirement for a data pipeline that can ingest data, process it, and provide output for training, inference, and subsequent decision making at a large scale. AWS is taken to be the cloud standard with its scalability and efficiency for building these pipelines. In this article, we will discuss designing a high-performance data pipeline using only basic AWS services like Amazon S3, AWS Lambda, AWS Glue, and Amazon SageMaker for AI and NLP applications. This article discusses building a high-performance data pipeline for AI and NLP applications using core AWS services such as Amazon S3, AWS Lambda, AWS Glue, and Amazon SageMaker. Why AWS for data pipelines? AWS is the most preferred choice for building data pipelines because of its strong infrastructure, rich service ecosystem, and seamless integration with ML and NLP workflows. Azure, Google Cloud, and AWS also outperform open source tools like Apache Suite in terms of ease of use, operational reliability, and integration. Some of the benefits of using AWS are: Scalability AWS would automatically scale up or down because of its elasticity, hence always assuring high performance irrespective of the volume of data. Though Azure and Google Cloud provide features for scaling, the auto-scaling options available in AWS are more granular and customizable, hence providing finer control over resources and costs. Flexibility and integration... --- - Published: 1404-03-12 - Modified: 1404-03-12 - URL: https://tirotir.ir/why-responsible-ai-will-need-to-be-your-new-usp/ - دسته‌ها: other Although AI has been the No. 1 trend since at least 2023, organizational AI governance is just slowly catching up. But with rising AI incidents and new AI regulations, like the EU AI Act, it’s clear that an AI system that is not governed appropriately has the potential to cause substantial financial and reputational damage to a company. In this article, we explore the benefits of AI governance, its key components, and best practices for minimal overhead and maximal trust. Additionally, we cover two cases of how to start building an AI governance, demonstrating how a dedicated AI governance tool can be the game changer. Summary Efficient AI governance mitigates financial and reputational risks through fostering responsible and safe AI. Key components of AI governance include clear structures and processes to control and enable AI use. An AI management system, a risk management system, and an AI registry are part of that. Start governing AI in your organization by implementing a suitable framework, collecting your AI use cases, and mapping the right requirements and controls to the AI use case. The EU AI Act poses additional compliance risks due to hefty fines. AI governance tools can help in creating compliance, e. g. by mapping of the respective requirements to your AI use cases and automated processes. When selecting a dedicated AI governance tool, look beyond traditional GRC functionalities, but for curated AI governance frameworks, integrated AI use case management, and the connection to development processes or even MLOps tools. This... --- - Published: 1404-03-09 - Modified: 1404-03-09 - URL: https://tirotir.ir/future-trends-of-ai-adoption-in-enterprises-2025-report/ - دسته‌ها: other Your current AI strategy is likely costing you more than you think. The rapid, uncontrolled adoption of various AI tools has created a costly "AI tax" across the enterprise, stifling true innovation. This report explores the pivotal shift from fragmented AI tools to unified, collaborative platforms. Learn how to move beyond scattered adoption to build a sustainable, cost-effective AI ecosystem that will define the next generation of industry leaders. In this report, you'll learn how to: Benchmark your company's progress against the latest enterprise AI adoption trends. Expose and eliminate the hidden "AI tax" that is draining your budget and stifling innovation. Build the business case for a unified AI platform that drives ROI, collaboration, and security. Create a framework that empowers grassroots innovation without sacrificing centralized strategy and governance. Design a future-proof roadmap for AI integration that scales with your enterprise and adapts to what's next. Your roadmap to a scalable, future-proof AI strategy is one click away. --- - Published: 1404-03-06 - Modified: 1404-03-06 - URL: https://tirotir.ir/integrating-ai-with-ar-vr-transforming-user-interaction-and-empowering-creators/ - دسته‌ها: other The convergence of AI and AR/VR is changing the way we engage with, explore, and even create content for virtual worlds. This convergence is adding intelligence, realism, and adaptability to immersive experiences like never before, enhancing the potential of AR/VR significantly. AI adds intelligence, personalisation, and adaptability to AR and VR interactions, thereby enhancing the degree of responsiveness and smoothness of the system for user needs. This convergence of technology is more than just an innovation, it represents a significantly growing industry; According to a study of Verified Market Research, the AR and VR market surges to USD 214. 82 billion by 2031, propelled by 31. 70% CAGR. At the same time, PwC predicts that AI advancements in business functions like training simulations, remote work, and cross-location teamwork will greatly enhance VR and AR applications, contributing $1. 5 trillion to the economy by 2030. Additionally, the AR and VR consumer segment is set to soar as well. IDC estimates that global expenditure on AR/VR will exceed $50 billion annually by 2026, with AI personalisation driving demand. In addition, the AI-in-AR/VR sector is projected to experience a growth rate of more than 35% CAGR in the next few years, highlighting the transformative influence of intelligent algorithms on immersive technologies. This rapid expansion illustrates the need for advanced virtual experiences powered by AI in almost every sector. It is predicted that by 2029, the number of users in the AR & VR market worldwide is expected to reach 3. 7 billion. As... --- - Published: 1404-03-02 - Modified: 1404-03-02 - URL: https://tirotir.ir/when-and-when-not-to-build-ai-products-a-guide-to-maximizing-roi/ - دسته‌ها: other A few weeks ago, I saw a post on Instagram that made me laugh; it was about someone’s grandmother asking if she should invest in AI. That really struck a chord. Right now, AI is everywhere. It’s overhyped, misunderstood, and somehow both intimidating and irresistible. I work with executives, product managers, and board members every day who are all asking the same questions: When should we invest in AI? How do we know if it’ll be worth it? And once we do decide to invest, how do we make sure we actually get a return on that investment? After more than a decade building AI products – from chatbots at Wayfair to playlist personalization at Spotify to Reels recommendations at Instagram, and leading the AI org at SiriusXM – I’ve seen the difference between AI that delivers and AI that drains. This article is my attempt to help you avoid the latter, because here’s the thing: AI is powerful, but it’s also expensive. You have to know when it makes sense to build, and how to build smart. So, let’s get started. Define the problem first – AI is not the goal Let me be blunt: if you can’t clearly articulate the business problem you’re trying to solve, AI is probably not the answer. AI is not a goal. It’s a tool. A very expensive one. I always come back to something Marty Cagan said about product management: “Your job is to define what is valuable, what is viable, and... --- - Published: 1404-02-26 - Modified: 1404-02-26 - URL: https://tirotir.ir/quantum-leaps-transforming-data-centers-energy/ - دسته‌ها: other We are making Quantum Leaps. I am not referring to the 80s/90s TV show, but rather, I am referring to quantum computing and competing for better and faster artificial intelligence. Quantum computing is a field that excites me to my core. I’ve always been driven by pursuing what’s next, whether mastering tactics in the Marines or navigating complex policy challenges in government. Quantum computing feels like the ultimate “what’s next. ” Its potential to solve problems in seconds that would take today’s supercomputers millennia is a quantum leap. I talked a bit about Quantum Computing in one of my recent newsletters. However, potential doesn’t turn into reality without investment of time, money, and strategic resources. My experience has shown me that technological superiority is a strategic advantage, and right now, nations and companies worldwide are racing to claim the quantum crown. We risk falling behind if we don’t pour resources into research, development, and deployment. This is more than an opportunity; it’s a call to action. We must invest heavily and deliberately to ensure quantum computing becomes a cornerstone of our competitive edge. Next gen AI architectures: Exploring the next wave of intelligent computing Some next-generation AI architectures are emerging as promising alternatives such as (HDC), (NSAI), capsule networks, and low-power AI chips. AI Accelerator InstituteRobert McMenemy Bill Gates recently suggested that energy sector jobs are among the few fields that will survive an AI takeover. According to him, the energy sector’s immense complexity and ever-evolving regulatory frameworks mean that... --- - Published: 1404-02-26 - Modified: 1404-02-26 - URL: https://tirotir.ir/aiai-silicon-valley-2025/ - دسته‌ها: other Catch up on every session from the AIAI Silicon Valley with sessions across 3 co-located summit featuring the likes of Anthropic, Open AI, Meta and many more. --- - Published: 1404-02-19 - Modified: 1404-02-19 - URL: https://tirotir.ir/how-to-build-a-powerful-llm-user-feedback-loop/ - دسته‌ها: other Discover how to build a powerful LLM user feedback loop with Nebuly, optimizing AI interactions and driving continuous improvement. --- - Published: 1404-02-19 - Modified: 1404-02-19 - URL: https://tirotir.ir/ibm-oracle-debut-watsonx-agentic-ai-on-oci/ - دسته‌ها: other Unlike traditional AI systems that rely on step-by-step human input, agentic AI represents the next evolution: autonomous agents capable of ingesting information, executing tasks, and independently delivering end-to-end outcomes. These agents can undertake multistep processes, linking APIs, databases, and workflows, to tackle complex problems without constant oversight. As businesses aim to streamline operations and cut down on manual bottlenecks, agentic AI signals a shift from human-in-the-loop to human-on-the-loop management. IBM and Oracle’s relationship stretches back years, with joint efforts to optimize middleware, databases, and cloud services. Their agentic AI partnership builds on prior collaborations, such as the 2018 integration of IBM Cloud with Oracle’s database services. It reflects a mutual strategy to deliver enterprise‑grade AI tools at scale. By pooling IBM’s AI research and Oracle’s cloud infrastructure, they can offer customers seamless, cloud‑native workflows that span both vendors’ ecosystems. watsonx Orchestrate: Automating workflows On May 6, 2025, IBM and Oracle unveiled a significant expansion of their alliance: IBM’s watsonx AI portfolio, including watsonx Orchestrate and the new Granite AI models, will be directly available on Oracle Cloud Infrastructure (OCI). Unlike point solutions, these tools are deeply embedded in OCI’s core services, allowing agents to run natively alongside data and apps—no extra pipelines or connectors needed. At the heart of this expansion is watsonx Orchestrate, a drag‑and‑drop interface for building AI agents. Users can configure agents to perform tasks like data extraction, reconciliation, and approval routing by simply arranging modular “action blocks. ” These blocks invoke pretrained models or custom scripts, then... --- - Published: 1404-02-19 - Modified: 1404-02-19 - URL: https://tirotir.ir/rewiring-the-internet-commerce-in-the-age-of-ai-agents/ - دسته‌ها: other December 2028. Maria's AI agent is negotiating simultaneously with twelve different vendors for her daughter's upcoming birthday party. Within minutes, it secured the perfect cake from a local bakery (after verifying their nut-free certification), booked an entertainer with stellar safety ratings, and coordinated custom goodie bags filled with each child's favorite treats (after checking allergies and dietary restrictions with the other parents' agents)—all while staying 15% under budget. What would have taken Maria hours of calls, emails, and anxiety about vendor reliability now happens seamlessly through a web of agent-to-agent interactions powered by the new infrastructure explored in the previous post. The revolution in web infrastructure we discussed in previous posts isn't just theoretical—it's enabling fundamental changes in how commerce, marketing, and customer service function. As agent passports and trust protocols become standardized, we're witnessing the emergence of entirely new commercial paradigms. With the recent release of Tasks by OpenAI, which equips ChatGPT—its consumer-facing AI—with the ability to perform tasks behind the scenes on behalf of users, it's now easier than ever to envision a future where ChatGPT seamlessly navigates the web and handles complex operations for us. ChatGPT can now set reminders and perform recurring actions Today, we'll explore how an agent-first internet will reshape domains like payments, marketing, support, and localization. Agentic payments Remember when online shopping first emerged, and entering your credit card details on a website felt risky? Card networks like Visa and Mastercard and banks like Chase and Barclays had to rapidly adapt to the... --- - Published: 1404-02-19 - Modified: 1404-02-19 - URL: https://tirotir.ir/ai-driven-admin-analytics-tackling-complexity-compliance-and-customization/ - دسته‌ها: other As productivity software evolves, the role of enterprise IT admins has become increasingly challenging. Not only are they responsible for enabling employees to use these tools effectively, but they are also tasked with justifying costs, ensuring data security, and maintaining operational efficiency. In my previous role as a Reporting and Analytics Product Manager, I collaborated with enterprise IT admins to understand their struggles and design solutions. This article explores the traditional pain points of admin reporting and highlights how AI-powered tools are revolutionizing this domain. Key pain points in admin reporting Through my research and engagement with enterprise IT admins, several recurring challenges surfaced: Manual, time-intensive processes: Admins often spent significant time collecting, aggregating, and validating data from fragmented sources. These manual tasks not only left little room for strategic planning but also led to frequent errors. Data complexity and compliance: The explosion of data, coupled with stringent regulatory requirements (e. g. , GDPR, HIPAA), made ensuring data integrity and security a daunting task for many admins. Unpredictable user requests: Last-minute requests or emergent issues from end-users often disrupted admin workflows, adding stress and complexity to their already demanding roles. Limited insights for decision-making: Traditional reporting frameworks offered static, retrospective metrics with minimal foresight or actionable insights for proactive decision-making. Optimizing LLM performance and output quality The session focuses on enhancing outcomes for customers and businesses by optimizing the performance and output quality of generative AI. AI Accelerator InstituteAIAI Building a workflow to solve reporting challenges To address these pain... --- - Published: 1404-02-17 - Modified: 1404-02-17 - URL: https://tirotir.ir/optimizing-llm-performance-and-output-quality/ - دسته‌ها: other The session from Srinath Godavarthi, Director, Divisional Architect at Capital One, focuses on enhancing outcomes for customers and businesses by optimizing generative AI's performance and output quality. It highlights the importance of foundation models, their challenges, and the variability in output quality, including issues like hallucinations caused by noisy training data. The discussion covers four main strategies for improving model performance: prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and building models from scratch. Each method has its advantages, with prompt engineering offering quick improvements and fine-tuning providing specialized adaptations for specific tasks. Ultimately, the choice of strategy depends on the use case and the complexity involved. Want to see more? Become a Pro member today and get access to all sessions from Generative AI Summit Washington, alongside our entire world series. That's hundreds of hours of insights straight from some of the world's top AI leaders. Sign up for a Pro membership. --- - Published: 1404-02-08 - Modified: 1404-02-08 - URL: https://tirotir.ir/how-ai-is-transforming-financial-modeling-sales-forecasting-in-enterprise-tech/ - دسته‌ها: other AI is emerging as a key differentiator in enterprise finance. As traditional financial models struggle to keep up with the pace of change, enterprise tech organizations are turning to AI to unlock faster, more accurate, and insight-driven decision-making. Drawing from my experience in sales planning and forecasting in the enterprise tech sector, I’ve seen firsthand how AI is reshaping how global enterprises forecast revenue, optimize GTM strategies, and manage P&L risk. This article explores how AI is transforming financial modeling and sales forecasting (two pillars of enterprise strategy) and helping finance teams shift from reactive to proactive operations. 1. Why traditional forecasting falls short There are three main reasons why traditional forecasting is falling short: Lack of broader business context Sales forecasters and financial modelers frequently lack visibility into wider organizational shifts such as changes in product strategy, marketing campaigns, or operational execution that affect demand and performance. This makes it difficult to fine-tune models for niche business dynamics or rapidly changing market conditions. Inflexibility They often have an inability to account for real-time changes in demand, market shifts, economic conditions, tariffs, or sales performance. Human bias Over-reliance on gut-feel projections leads to inaccurate financial planning. In many enterprise settings, these limitations create friction between planning and execution across business functions, finance, sales, and marketing. Misaligned forecasts result in delayed strategic actions and misused resources, which are issues that AI is now well-positioned to solve. 2. What makes AI a game-changer for financial modeling Cross-functional simulations tailored by domain experts... --- - Published: 1404-02-05 - Modified: 1404-02-05 - URL: https://tirotir.ir/how-generative-ai-is-revolutionizing-drug-discovery-and-development/ - دسته‌ها: other This article comes from Dr Nikolay Burlutskiy’s talk at our London 2024 Generative AI Summit. Check out his full presentation and the wealth of OnDemand resources waiting for you. Nikolay is currently the Senior Manager of GenAI Platforms at Mars Have you ever wondered just how long it takes to bring a new medicine to market? For those of us working in the pharmaceutical industry, the answer is clear: it can take decades and cost billions. As a computer scientist leading the AI team at AstraZeneca, I've seen firsthand just how complicated the drug discovery process is. Trust me, there’s a lot of work that goes into developing a drug. But the real challenge lies in making the process more efficient and accessible, which is where generative AI comes in. In this article, I’ll walk you through the critical role that AI plays in accelerating drug discovery, particularly in areas like medical imaging, predicting patient outcomes, and creating synthetic data to address data scarcity. While AI has incredible potential, it’s not without its challenges. From building trust with pathologists to navigating regulatory requirements, there’s a lot to consider. So, let’s dive into how AI is reshaping the way we approach drug discovery and development – and why it matters to the future of healthcare. Generative AI’s role in enhancing medical imaging One of the most powerful applications of generative AI in drug development is its ability to analyze medical images – a process that’s essential for diagnosing diseases like cancer,... --- - Published: 1404-02-04 - Modified: 1404-02-04 - URL: https://tirotir.ir/ais-next-leap-gemini-2-5-1-bit-llm-beyond/ - دسته‌ها: other Post Content --- - Published: 1404-02-04 - Modified: 1404-02-04 - URL: https://tirotir.ir/ai-agent-infra-gemini-2-5-1-bit-llm-this-weeks-top-5/ - دسته‌ها: other Welcome to AI Circuit, in April's edition: The great web rebuild: Infrastructure for the AI agent era Meet Gemini 2. 5 Flash: Fast, smart, and fully tunable AIOps in action: AI & automation transforming IT operations Microsoft’s 1-bit LLM is fast, tiny, and open source How to 8‑bit quantize large models using bits and bytes Reading time: 4 minutes The great web rebuild: Infrastructure for the AI agent era Booking flights. Comparing prices. Managing data privacy. In 2028, your AI agent does it all without hitting a single CAPTCHA or fraud alert. The secret? Agent passports: cryptographic credentials that prove delegation, set spending limits, and unlock seamless agent-to-agent coordination. We're entering the agent-first internet, where human-era systems (CAPTCHAs, review sites, IP throttling) break down, and new infrastructure rises to support fully autonomous assistants. What’s changing? Identity: agents verify delegation, not humanity Privacy: agents manage granular data permissions in real time Trust: star ratings are out, verifiable metrics are in Security: new attack surfaces, new protections The takeaway? The next internet runs on agents. And whoever builds the infrastructure? Wins. Meet Gemini 2. 5 Flash: Fast, smart, and fully tunable Google just dropped Gemini 2. 5 Flash. An accelerated, cost-efficient model with a twist: you control how much it thinks. It’s the first hybrid reasoning model: Turn thinking on/off depending on your use case Set a thinking budget to balance speed, quality, and cost Keep Flash-fast responses with smarter performance Even with reasoning disabled, 2. 5 Flash outperforms its predecessor and... --- - Published: 1404-01-28 - Modified: 1404-01-28 - URL: https://tirotir.ir/the-great-web-rebuild-infrastructure-for-the-ai-agent-era/ - دسته‌ها: other It's December 2028. Sarah's AI agent encounters an unusual situation while booking her family's holiday trip to Japan. The multi-leg journey requires coordinating with three different airlines, two hotels, and a local tour operator. As the agent begins negotiations, it presents its "agent passport"—a cryptographic attestation of its delegation rights and transaction history. The vendors' systems instantly verify the agent's authorization scope, spending limits, and exposed metadata like age and passport number. Within seconds, the agent has established secure payment channels and begun orchestrating the complex booking sequence. When one airline's system flags the rapid sequence of international bookings as suspicious, the agent smoothly provides additional verification, demonstrating its legitimate delegation chain back to Sarah. What would have triggered fraud alerts and CAPTCHA challenges in 2024 now flows seamlessly in an infrastructure built for autonomous AI agents. —> The future, four years from now. In my previous essay, we explored how websites and applications must evolve to accommodate AI agents. Now we turn to the deeper infrastructural shifts that make such agent interactions possible. The systems we've relied on for decades: CAPTCHAs, credit card verification, review platforms, and authentication protocols, were all built with human actors in mind. As AI agents transition from experimental curiosities to fully operational assistants, the mechanisms underpinning the digital world for decades are beginning to crack under the pressure of automation. The transition to an agent-first internet won't just streamline existing processes—it will unlock entirely new possibilities that were impractical in a human-centric web. Tasks... --- - Published: 1404-01-25 - Modified: 1404-01-25 - URL: https://tirotir.ir/aiops-in-action-ai-automation-transforming-it-operations/ - دسته‌ها: other The advancement of digital frameworks has created new hurdles for business IT operations. A company’s network, cloud infrastructure, and streams of data need to be monitored and secured to meet performance and availability requirements, which directly cuts into productivity. These demands are nearly impossible to cope with under traditional workflows due to outdated approaches relying on reactive monitoring and manual debugging. The use of artificial intelligence for IT operations (AIOps) has become a breakthrough with regard to IT operation streamlining and business growth. AIOps applies predictive IT maintenance, proactive incident detection, and scalable automation through AI and machine learning, thus bolstering IT operations. Optimized management of resources, minimal downtime, and efficient IT service management (ITSM) transform AIOps into a framework that is crucial for modern-day enterprises. Understanding AIOps and its role in IT operations AIOps refers to the application of AI and machine learning technologies to IT operations. It enhances decision-making and automation by analyzing vast amounts of data from numerous sources, such as logs, metrics, and network traffic. Key capabilities of AIOps include: Data ingestion and correlation: Aggregating IT data from multiple sources. Anomaly detection: Identifying irregular patterns that indicate potential operational issues (such as misconfigurations), potential failures or security threats. Root cause analysis: Automatically diagnosing issues to pinpoint the source of disruptions. Automated remediation: Implementing fixes without human intervention, reducing mean time to resolution (MTTR). AIOps not only enhances IT operations with advanced analytics and automation but also represents a paradigm shift in how IT teams manage infrastructure... --- - Published: 1404-01-22 - Modified: 1404-01-22 - URL: https://tirotir.ir/the-truth-about-enterprise-ai-agents-and-how-to-get-value-from-them/ - دسته‌ها: other This article comes from Ryan Priem’s talk at our Washington, D. C. 2025 Generative AI Summit. Check out his full presentation and the wealth of OnDemand resources waiting for you. What’s the point of AI if it doesn’t actually make your workday easier? That’s the question I keep coming back to – and the one that ultimately brought me into the generative AI space. I’m Ryan Priem, and I lead sales for Glean here in the East. After more than two decades in tech, working in data and analytics at places like Snowflake and EMC, I saw something shift. Large language models weren’t just impressive – they were starting to offer real, measurable value. But there’s a catch: value doesn’t come from the model alone. It comes from how well you apply it. That’s what drew me to Glean. We’re focused on using AI to solve actual workplace problems. Whether it’s helping someone find the right document, answer a critical question, or automate a tedious task, we’re building AI that works the way people do. This article is a walk-through of what that journey looks like and what it really takes to build useful, scalable agents that people actually want to use. Let’s dive in. What work AI systems actually do (and why they matter now) We classify ourselves as a "work AI" company. What that means is we’re focused on three core use cases: Find something. Think of enterprise search – Google-like capabilities across your entire data corpus. We’ve... --- - Published: 1404-01-20 - Modified: 1404-01-20 - URL: https://tirotir.ir/how-to-8%e2%80%91bit-quantize-large-models-using-bits-and-bytes/ - دسته‌ها: other Deep learning is consistently changing so many fields, from NLP (natural language processing) to computer vision. However, as these models continue to grow in size and complexity, the demands on the hardware required for memory and compute continue to skyrocket. In light of this, there are promising strategies to overcome these challenges, one of which is quantization. This lowers the precision of numbers used in the model without a noticeable loss in performance. In this article, I will dive into the theoretical processes underlying this strategy and show the practical implementation of 8‑bit quantization within a large parameter model, in this case, we will be using the IBM Granite model and BitsAndBytes for quantization. Introduction The quick growth of deep learning has resulted in an arms race of models boasting billions of parameters, which, in most cases, achieve stellar performance but require enormous computational resources. As engineers and researchers look for methods to make these large models more efficient, quantization has shown to be an incredibly effective solution. By lowering the bit width of number representations from 32‑bit floating point to x‑bit integers, quantization decreases the overall model size, speeds up inference, and cuts energy consumption, all while keeping a high accuracy in the output. I will explore the concepts and techniques behind 8‑bit quantization in this article. I will explain the approach's benefits, outline the theory behind it, and walk you through the process step by step. I will then show you a practical application: quantizing the IBM Granite... --- - Published: 1404-01-18 - Modified: 1404-01-18 - URL: https://tirotir.ir/building-scalable-image-data-pipelines-for-ai-training/ - دسته‌ها: other Artificial intelligence forms the heart of the digital revolution in the advent of the twenty-first century. Handling big data through fine-grained data pipelines is crucial for perfect AI training, and such a requirement is felt more strongly in computer vision applications. AI models, mainly deep learning models, need large volumes of labeled image data for efficient training and reasoning. A well-designed, scalable image processing pipeline ensures that AI systems are appropriately trained with quality-prepared data to ensure accuracy by minimizing errors in model training and optimizing their performance. This article discusses essential components and necessary strategies for implementing efficient and scalable image data pipelines for the training of AI models. Scalable image data pipelines: A need Image-based AI applications have been infamous for being extremely data-hungry. Be it image classification, object detection, or facial recognition, all of these models require millions of images to learn from. The images have to be preprocessed before training: resized, normalized, and often augmented. As data starts to scale up, such operations become increasingly complex, and one needs a strong and flexible pipeline that could handle a variety of tasks like: Ingestion of Data: Ingest a large volume of image data coming from different sources very fast. Preprocessing of Data: Raw image data is transformed into forms that are usable in the training of models, including resizing, cropping, and augmentation. Storage of Data: Preprocessed data should be stored in a manner such that during training, it can be accessed fast. Scalability: The system should scale... --- - Published: 1404-01-15 - Modified: 1404-01-15 - URL: https://tirotir.ir/agent-responsive-design-rethinking-the-web-for-an-agentic-future/ - دسته‌ها: other It's November 2028. Maya's personal AI agent quietly handles her holiday shopping, easily navigating dozens of e-commerce sites. Unlike the clunky chatbots of 2024, her agent seamlessly parses product specifications, compares prices, and makes purchase decisions based on her preferences. "The boots for your sister," it explains, "are from that sustainable brand you both discussed last month - I found them at 20% off and confirmed they'll arrive before your family gathering. " What would have taken Maya hours of manual searching now happens automatically, thanks to a web rebuilt for agent-first interaction. —> The future, three years from now. As we approach the end of 2024, a new paradigm shift is emerging in how we build and interact with the internet. With rapid advances in AI reasoning capabilities, tech giants and innovative startups alike are racing to define the next evolution of digital interaction: AI agents, . Google, Apple, OpenAI, and Anthropic have all declared AI agents as their primary focus for 2025. This transformation promises to be as significant as the web and mobile revolutions were and represents perhaps the most natural interface for LLM-powered technology, far more intuitive and capable than the chatbots that preceded it. In the recent No Priors Podcast, Nvidia’s CEO Jensen Huang stated that "there's no question we're gonna have AI employees of all kinds” that would "augment every single job in the company”. Moreover, Gartner projects that by 2028, 33% of enterprise software applications will include agentic AI, up from less than... --- - Published: 1404-01-13 - Modified: 1404-01-13 - URL: https://tirotir.ir/ai-literacy-essential-for-todays-workforce-and-businesses/ - دسته‌ها: other Bringing generative AI into a business or even public sector organization is consuming the minds of leaders around the world, some approaching the topic with a positive outlook and some with caution. According to BCG, a mere 10% of organisations have managed to successfully integrate gen AI into their workflows at scale, gaining a significant advantage over their competitors who are in danger of falling behind in this rapidly evolving landscape. But what does AI literacy mean? AI literacy is having the knowledge and practical understanding of AI, its use cases, power, and limitations. This could include prompting mastery, the ability to identify when and how to use it, to critically evaluate its outputs, and being able to adapt in a workplace empowered with AI. AI literacy is a key skill set the whole workforce must master and employers must endorse. Why AI literacy matters Future-proofing your business I briefly mentioned competitiveness above, AI driven companies have a strong competitive advantage in their market, according to HBR. Those AI-first companies are also way ahead of the market in scaling AI predictive solutions and, hence, future-proofing their business. AI literacy enables this innovation across the whole workforce. More importantly, the future workforce is already relying on AI in their education, and it is critical that businesses and public sector organisations remain top of mind for the job market of the present and the future. Your guide to agentic AI Agentic AI refers to artificial intelligence systems that act autonomously, make decisions,... --- - Published: 1404-01-12 - Modified: 1404-01-12 - URL: https://tirotir.ir/qa-with-fiddler-ai-observability-security-making-the-world-a-better-place/ - دسته‌ها: other Fiddler AI, a pioneer in AI observability and security for LLM and MLOps, has the mission of making the world a better place. Following his session at Generative AI Summit Washington, D. C. , I spoke with Nick Nolan, Solutions Engineering Manager at Fiddler AI, to dive into how they're seeking to achieve this. Q: Fiddler AI emphasizes building trust into AI systems. Can you elaborate on how your AI Observability platform achieves this, particularly concerning explainability and transparency? Fiddler is the pioneer in AI observability and security for LLM and MLOps. Fiddler’s mission is to make the world a better place, as many of the decisions consumers make every day are influenced by AI. As AI continues to be deeply integrated into society, Fiddler addresses on two key areas: 1) Helping enterprise AI teams deliver responsible AI applications. 2) Ensuring that people interacting with AI receive fair, safe, and trustworthy responses. As AI advances, particularly in generative AI, more policies will be introduced to enforce regulations around governance, risk, and compliance. These regulations will help enterprises strengthen oversight of their AI systems while protecting consumers from harmful, toxic, or biased outcomes. We continue our mission to lead the way in helping enterprises deploy and use AI responsibly, ensuring trustworthy AI, and safeguarding consumers from harmful and unsafe outcomes. We support enterprises at every stage of their AI journey in establishing long-term responsible AI practices. From accelerating LLMOps and MLOps, driving business value, and mitigating risks to building customer satisfaction,... --- - Published: 1404-01-11 - Modified: 1404-01-11 - URL: https://tirotir.ir/zero-trust-and-ai-the-next-evolution-in-cybersecurity-strategy/ - دسته‌ها: other Traditional approaches to cybersecurity have always been to defend the digital perimeter surrounding internal networks. However, with the popularity of remote work and cloud computing technologies, conventional security strategies are no longer as effective at protecting organizations. Zero trust has now become the go-to security approach. Its guiding concepts are built around the mindset of "never trust, always verify. " Each user, access device, and network connection is strictly evaluated and monitored regardless of where they originate from. Artificial intelligence (AI) has become an addition to zero trust security architecture. With the ability to analyze large volumes of information and apply complex processes to automate security functions, AI has helped how modern businesses approach their security planning. Understanding zero trust in modern organizations Digital environments have changed the cybersecurity paradigm in many different ways, as businesses have moved toward highly connected infrastructures. . Zero trust security models assume every network connection within the organization is a potential threat and requires various strategies to address them effectively. Zero trust models work on several core principles that include: Providing minimum access privileges: Employees should only be given access to information and systems that are absolutely essential for the job function they perform. This limits unauthorized access at all times, and in the event a security breach does occur, the damage is contained to a minimum. Creation of isolated network areas: Rather than having a single company network, organizations should segment their systems and databases into smaller, isolated networks. This limits an attacker's... --- - Published: 1404-01-08 - Modified: 1404-01-08 - URL: https://tirotir.ir/how-to-secure-llms-with-the-fastest-guardrails-for-peak-ai-performance/ - دسته‌ها: other This article comes from Nick Nolan’s talk at our Washington DC 2025 Generative AI Summit. Check out his full presentation and the wealth of OnDemand resources waiting for you. What happens when a powerful AI model goes rogue? For organizations embracing AI, especially large language models (LLMs), this is a very real concern. As these technologies continue to grow and become central to business operations, the stakes are higher than ever – especially when it comes to securing and optimizing them. I’m Nick Nolan, and as the Solutions Engineering Manager at Fiddler, I’ve had countless conversations with companies about the growing pains of adopting AI. While AI’s potential is undeniable – transforming industries and adding billions to the economy – it also introduces a new set of challenges, particularly around security, performance, and control. So in this article, I’ll walk you through some of the most pressing concerns organizations face when implementing AI and how securing LLMs with the right guardrails can make all the difference in ensuring they deliver value without compromising safety or quality. Let’s dive in. The growing role of AI and LLMs We’re at an exciting moment in AI. Right now, research shows around 72% of large enterprises are using AI in some way, and it’s clear that generative AI is definitely on the rise – about 65% of companies are either using it or planning to. On top of this, AI is also expected to add an enormous amount to the global economy – around... --- - Published: 1404-01-08 - Modified: 1404-01-08 - URL: https://tirotir.ir/ai-assistants-only-as-smart-as-your-knowledge-base/ - دسته‌ها: other Artificial intelligence assistants are quickly becoming vital tools in modern workplaces, transforming how businesses operate by making everyday tasks simpler and faster. But despite their widespread adoption and advanced capabilities, even the best AI assistants today face a significant limitation: they often lack access to a company's internal knowledge. AI assistants need real-time, seamless connections to your company's databases, documents, and internal communication tools to realize their full potential. This integration ensures they're brilliant and contextually aware, making them genuinely valuable workplace assets. The rise of AI assistants AI assistants are smart applications that understand commands and use a conversational AI interface to conduct tasks. They’re often embedded into dedicated hardware and even incorporated with several systems. Unlike chatbots, AI assistants are less limited in both intelligence and functionality. They have more agency and advanced abilities, like contextual understanding and personalization. From drafting emails to summarizing reports, these assistants are everywhere. Some of the more popular AI assistants are: ChatGPT from OpenAI Gemini from Google Claude from Anthropic DeepSeek from High-Flyer In business, these large language models (LLMs) can also help you with data analysis, task automation, workflow streamlining, and more. They can be mostly free if you don’t need to scale up, although some users might struggle with the free versions when it comes to tasks that involve uploading or downloading data. However, even the more advanced AI assistants are missing something that makes them truly useful in your workplace: they don’t have access to your company’s knowledge and... --- - Published: 1404-01-06 - Modified: 1404-01-06 - URL: https://tirotir.ir/gold-copy-data-ai-in-the-trade-lifecycle-process/ - دسته‌ها: other The current end-to-end trade lifecycle is highly dependent on having accurate data at each stage. The goal of the Investment iook of records (IBOR) system is to ensure the trade, position, and cash data match the custodian and for the accounting book of records (ABOR) system for this same data set to match the fund accountant. There are other stakeholders in the process, including broker systems, transfer agents, central clearing parties, etc, depending on the type and location of execution. A position that reflects identically across all systems is known as having been “straight-through processed”; in other words, systems have recognized the trade, and datasets are in line, or at least, within tolerance. While efficient, the addressal and eventual resolution of non-STP executions remains highly manual. Stakeholders typically compare data points across multiple systems, beginning as upstream as possible, and gradually move down the lifecycle to the root cause of the break. This investigation takes time, creates noise across the value chain, and most importantly, creates uncertainty for the front office to take new decisions. The proposal is to leverage AI to continually create and refine gold-copy data at each stage of the life cycle through comparison with sources and link downstream processes to automatically update in real-time with the accurate datasets. Guardrails should also be implemented in case of material differences. Leveraging AI to accelerate sales effectiveness Artificial Intelligence can be an extremely useful tool for organizations looking to improve the effectiveness of their sales and marketing activities. AI... --- - Published: 1404-01-05 - Modified: 1404-01-05 - URL: https://tirotir.ir/llm-economics-how-to-avoid-costly-pitfalls/ - دسته‌ها: other Large Language Models (LLMs) like GPT-4 are advanced AI systems designed to process and generate human-like text, transforming how businesses leverage AI. GPT-4’s pricing model (32k context) charges $0. 06 per 1,000 input tokens and $0. 12 per 1,000 output tokens, which makes it a scalable option for businesses. However, it can become expensive very quickly when it comes to production environments. New models cross-reference all bits of data, or tokens, that deal with other tokens in order to both quantify and understand the context behind each pair. The result? Quadratic behavior of algorithms that becomes more and more expensive as the number of tokens increases. And scaling isn’t linear; costs increase quadratically when it comes to the length of sequences. If you need to scale up to handle text that’s 10x longer, the cost will go up 10,000 times, and so on. This can be a significant setback for scaling projects; the hidden cost of AI impacts sustainability, resources, and requirements. This lack of insight can lead to businesses overspending or inefficiently allocating resources. Where costs lie Let’s look deeper into tokens, per-token pricing, and how everything works. Tokens are the smallest unit of text processed by models – something simple like an exclamation mark can be a token. Input tokens are used whenever you enter anything into the LLM query box, and output tokens are used when the LLM answers your query. On average, 740 words are equivalent to around 1,000 tokens. Inference costs Here’s an illustrative example... --- - Published: 1403-12-28 - Modified: 1403-12-28 - URL: https://tirotir.ir/generative-ai-summit-washington-d-c-2025/ - دسته‌ها: other Catch up on every session from Generative AI Summit Washington, D. C. with sessions from the likes of Meta, Glean, AstraZeneca and more. --- - Published: 1403-12-28 - Modified: 1403-12-28 - URL: https://tirotir.ir/edtech-meets-edge-ai-scalable-privacy-first-ecosystems/ - دسته‌ها: other Numbers that speak louder Think about the modern classroom. Each pupil receives a unique lesson plan courtesy of generative AI. Every single plan is flawlessly customized and catered for - even in remote schools with unstable internet. Now consider this projection from MarketResearch: the generative AI in the EdTech sector is anticipated to increase to $5. 26 billion by 2033 from $191 million in 2023, which comes with a CAGR of 40. 5%. Or take the National Education Policy Center figure: classroom districts spent $41 million on adaptive learning for personalized education in just two years. But here’s an astounding statistic - currently, cyberattacks on educational institutions have compromised the information of more than 2. 5 million users (eSchool News). Moreover, over 1,300 schools have been victims of cyberattacks which include data breaches, ransomware, and phishing email scams since 2016 according to a report by Cybersecurity and Infrastructure Security Agency in January 2023. In Sophos' most recent survey, 80% of schools were reported as a target for a cyber assault in 2022, which is an increase from 56% in 2021. In fact, schools have now become the predominant targets for cybercriminals according to The74. The increase in attacks on the education sector shows that it has one of the highest rates of ransom payment, where 47% of K-12 organizations admitted they paid an average of $2. 18 million in recovery attacks. These numbers indicate there is a glaring problem: security and privacy have not been more important as EdTech continues... --- - Published: 1403-12-27 - Modified: 1403-12-27 - URL: https://tirotir.ir/llmops-in-action-streamlining-the-path-from-prototype-to-production/ - دسته‌ها: other AIAInow is your chance to stream exclusive talks and presentations from our previous events, hosted by AI experts and industry leaders. It's a unique opportunity to watch the most sought-after AI content – ordinarily reserved for AIAI Pro members. Each stream delves deep into a key AI topic, industry trend, or case study. Simply sign up to watch any of our upcoming live sessions. Access exclusive talks and presentations Develop your understanding of key topics and trends Hear from experienced AI leaders Enjoy regular in-depth sessions Date: April 23, 2025 Time: 6pm GMT Location: Online Sign up now We’ll explore how data scientists, engineers, and end-users can work together seamlessly to unlock the full potential of LLMs, ensuring effective, confident deployment across use cases. Key points to be covered: Understanding the LLMOps lifecycle: An overview of the LLMOps lifecycle from model design and development to deployment, monitoring, and refinement. Optimising collaboration: Practical approaches to accelerate collaboration among data scientists, engineers and users. The what, why, and how of LLMOps: A foundational understanding of LLMOps, why it’s critical for organisations, and how to build and scale efficient operations. Real-world scenarios: Case studies showcasing success with LLM applications. Challenges in LLMOps and practical solutions: Addressing common obstacles in LLMOps life cycle. This presentation is perfect for AI practitioners, developers, and team leaders looking to advance their knowledge of LLMOps. Meet the speaker: Dr. Dmitry Kazhdan, PhD, CTO & Co-Founder, Tenyks Co-Founder & CTO at Tenyks. Building a best-in-class Visual Data Management &... --- - Published: 1403-12-24 - Modified: 1403-12-24 - URL: https://tirotir.ir/genai-creation-building-for-cross-platform-wearable-ai-and-mobile-experiences/ - دسته‌ها: other Yiqi Zhao, Product Design Lead, Meta Reality Labs at Meta gave this talk at the Generative AI Summit in Washington DC, 2025. I'm Yiqi, the design lead for Meta Reality Labs, the organization that makes many AR/VR glasses, like the Ray-Ban and the Meta Quest series. Today, I bring a video along with a topic that might not be something you’ve thought about deeply before. But I want you to consider this—can you be a creator? Can you be someone who makes content and actually makes money from it? Can you create fun, engaging experiences within the new developer ecosystem that’s emerging with devices like the Meta Quest, the Meta Ray-Ban glasses, and the incredible capabilities of AI? Would this be possible? I want to talk about how you can unlock your creative power and, more importantly, how you can leverage AI to be fully ready for this new platform and the opportunities that come with it. The rise of immersive content and Meta Horizon From the video, you might have noticed the rich, detailed 3D immersive content. This isn’t something that’s coming in the future—it’s happening right now on our platform. We recently rebranded our platform under the Meta Horizon name. Essentially, everything is becoming Horizon. Meta Horizon is more than just a name change—it represents our vision of a platform that connects people in ways that are richer, more interactive, and more immersive. We want people to socialize, engage, and find their communities in a way that feels... --- - Published: 1403-12-24 - Modified: 1403-12-24 - URL: https://tirotir.ir/llmops-in-action-from-prototype-to-production/ - دسته‌ها: other If you’ve ever built a GenAI application, you know the drill—your prototype looks amazing in a demo, but when it’s time to go live? Different story. In this exclusive video, Samin Alnajafi, Success Machine Learning Engineer at Weights & Biases, unpacks why LLMOps is the missing link between promising GenAI experiments and real-world deployment. Here’s what you’ll learn: Why so many GenAI projects stall before reaching production How to measure and optimize performance using LLMOps best practices Key components of a scalable retrieval-augmented generation (RAG) pipeline Practical examples and a live demo of Weights & Biases tools Don’t let your GenAI project get stuck in limbo. Log in to your Insider dashboard and watch now. Watch video now P. S. And if you have a few minutes to spare today, why not share your LLMOps expertise? We know how busy you are, so thank you in advance! Share the tools you use, the challenges you have, and more, and help define the LLMOps landscape. Whenever you're ready, here are three ways we can help you grow your AI career: Become a Pro+ member. Want to be an expert in AI? Join Pro+ for exclusive access to insights from industry leaders at companies like Meta and Google, one complimentary ticket to an in-person Summit of your choice, experienced mentors, AI advantage workshops, and more. Become a Pro member. Want to elevate your AI expertise? Join Pro for exclusive access to expert insights from leaders at top companies like HuggingFace and Microsoft,... --- - Published: 1403-12-22 - Modified: 1403-12-22 - URL: https://tirotir.ir/virtual-leaders-roundtable-accelerate-it-maturity-in-2025-with-ai/ - دسته‌ها: other Discuss challenges with the ITSM landscape, real steps to get started with AI-powered solutions, and how it helps with transforming IT. We invite you to join an exclusive, interactive virtual roundtable with industry peers, thought leaders, and our partners Freshworks. This is a by-invitation-only event designed for senior IT leaders (minimum Director level) keen on leveraging AI to transform their IT landscape. Reserve your spot and be a part of the conversation. A 2024 global survey by Harvard Business Review Analytic Services reveals that while 80% of IT decision-makers believe improving ITSM would enhance employee satisfaction, only 22% believe their organizations provide ITSM in a very effective manner. The solution lies in going back to the basics - reducing complexities, dismantling silos, modernizing ITSM, and aligning it closely with business goals. The event promises to be interactive as you meet with other leaders from the industry over lively discussions that highlight the focus areas for AI in IT, what challenges to look out for, and how you can showcase quick impact while scaling up your IT maturity with the power of AI. Why attend? Engage in dynamic discussions – Collaborate with fellow IT leaders in an interactive setting designed to foster meaningful conversations and knowledge sharing. Gain exclusive insights – Learn from industry experts about the key focus areas for AI in IT and what challenges to anticipate as you scale IT maturity. Discover AI-driven solutions – Explore how AI-powered ITSM can dismantle silos, modernize IT operations, and create immediate... --- - Published: 1403-12-22 - Modified: 1403-12-22 - URL: https://tirotir.ir/aws-bets-big-on-agentic-artificial-intelligence/ - دسته‌ها: other Unlike traditional AI systems, agentic AI is defined by its ability to perform tasks autonomously without user prompts. Amazon Web Services (AWS) invested in a dedicated agentic AI group; AWS’s Bedrock platform now features “agents” that allow customers to integrate generative AI models into their operations. This allows these systems to autonomously access data, trigger actions, and provide end-to-end solutions. Agentic AI represents a shift in how intelligent systems work. While many current AI applications rely on specific commands or user inputs, agentic AI systems are designed to operate independently. They can handle complex, multistep workflows seamlessly and connect with APIs, data sources, and other tools. This article offers a high-level overview of agentic AI, examining the technological shift, industry perspectives, and the implications for businesses and developers alike. Agentic code generation: The future of software development As enterprises strive to accelerate development cycles, reduce costs, and improve code quality, agentic code-generation is emerging as a critical enabler. AI Accelerator InstituteJordan Dunne The push for agentic AI at AWS AWS CEO Matt Garman announced the creation of a new agentic AI group led by Swami Sivasubramanian. The group aims to advance AI automation and broaden the scope of what AWS’s AI tools can achieve. AWS sees agentic AI as the “next frontier” of computing, a leap forward from traditional machine learning models that often need human direction at each stage. This initiative builds on AWS’s broader AI strategy, which has long focused on providing scalable, user-friendly machine learning solutions. AWS’s... --- - Published: 1403-12-21 - Modified: 1403-12-21 - URL: https://tirotir.ir/ai-powered-incident-management-risk-analysis-and-remediation/ - دسته‌ها: other Unlock smarter, faster, and more scalable incident management. IT teams are under increasing pressure to detect, investigate, and resolve incidents faster than ever. But with siloed data, manual processes, and escalating complexity, teams struggle to keep up, leading to slow resolutions, poor customer experiences, and costly downtime. Join us and BigPanda where we'll explore how AI is transforming incident management to accelerate investigations, surface relevant insights, and dynamically scale workflows. Why attend? Siloed data and institutional knowledge make it hard to get a complete picture of incidents. L1 NOC and service desk teams lack context, leading to unnecessary escalations and slow response times. Manual processes and poor communication create inefficiencies, massive bridge calls, and poor documentation. By attending, you’ll learn how organizations are saving an average of 30 minutes per task during incident investigations. What you'll walk away with: We’ll walk you through real-world use cases and practical strategies to optimize ITSM workflows using AI. You’ll discover how to: Augment team knowledge – Equip responders with AI-driven insights, including impact assessment, priority scoring, and change risk analysis, so they can resolve incidents faster and more effectively. Streamline incident processes – Reduce manual, broken workflows by ensuring the right teams are engaged at the right time, improving internal communication and collaboration. Prevent future incidents – Analyze operational and ITSM data to detect recurring issues, measure gaps, and implement proactive fixes before they escalate. Hosted by: Katie PetrilloSenior Director, Product Marketing at BigPanda As the senior director of product marketing, Katie is... --- - Published: 1403-12-21 - Modified: 1403-12-21 - URL: https://tirotir.ir/the-2025-frontier-digital-transformation-strategies-for-competitive-advantage/ - دسته‌ها: other In 2025, adapting, refining and pivoting strategies will not be a matter of choice, but rather a necessity for survival and expansion for companies. Spending on technologies that support digital transformation is expected to reach 3. 9 trillion dollars by 2027. The figure shows the continued increasing effort by companies in this field. The road ahead is not simple, however, studies indicate that almost 70% of digital transformation endeavors fail due to mismanagement, unsupporting corporate culture, and vague goals. Take the example of General Electric (GE). Once regarded as an industrial innovations leader, GE pursued a strategy of investing heavily into a digital unit with the hopes of transforming its operations and products. The project turned out to be underwhelming as a result of overly optimistic demand forecasts and internal pushback, and serves as a story of what not to do for other businesses with similar objectives. Getting your digital transformation strategy right can lead businesses towards endless possibilities and provide a competitive advantage. Adopting a digital transformation strategy is not the challenge, rather mastering it is. The future of digital transformation Explore the magic of digital transformation through Generative AI, real-world use cases, and future prospects like low/no-code platforms. AI Accelerator InstituteAna Simion Formulating digital transformation framework to achieve competitive advantage In simple terms, digital transformation can be described as the integration of digital technologies in every aspect of a business. This includes the modification of business processes and the manner in which value is provided to clients. Does... --- - Published: 1403-12-20 - Modified: 1403-12-20 - URL: https://tirotir.ir/chinas-ai-agent-manus-the-next-step-in-autonomous-ai/ - دسته‌ها: other China’s recently unveiled AI agent, Manus, represents a significant leap forward. Introduced by the Chinese startup Monica, Manus is described as a fully autonomous AI agent capable of handling a wide range of tasks with minimal human intervention. Since its launch on March 6, 2025, Manus has attracted considerable global attention, sparking discussions about its technological implications, ethical considerations, and potential impact on the AI landscape. This article explores what makes Manus unique, examines the perspectives of its supporters and critics, and considers the broader implications of its development. The emergence of Manus Manus differs from conventional AI systems' ability to independently plan, execute, and complete tasks without constant human supervision. The agent can analyze financial transactions, screen job applicants, and even create websites—all in real-time. Unlike traditional AI models that rely on pre-programmed inputs or human oversight, Manus learns from user interactions and adapts its approach to achieve its goals. Its creators have positioned it as a competitor to systems from global leaders such as OpenAI and Google. ChatGPT vs Bard: What are the top key differences? We’re taking a look at Bard vs ChatGPT and their key differences like technology, internet connection, and training data. AI Accelerator InstituteMarisa Garanhel Technological and industrial implications Manus stands out for its advanced autonomous capabilities, which allow it to handle complex workflows and provide real-time outputs without user intervention. By integrating these features, it opens new doors for automation in industries like: Financial services: Manus can analyze financial transactions, identify stock correlations,... --- - Published: 1403-12-20 - Modified: 1403-12-20 - URL: https://tirotir.ir/your-guide-to-agentic-ai/ - دسته‌ها: other What Is agentic AI? Agentic AI refers to artificial intelligence systems that act autonomously, make decisions, set goals, and adapt to their environment with minimal human intervention. Unlike traditional AI, which follows predefined instructions, agentic AI continuously learns, reasons, and refines its actions to achieve specific objectives. This type of AI moves beyond simple automation. Traditional AI models rely on predefined rules and patterns, executing tasks within strict boundaries. In contrast, agentic AI exhibits problem-solving capabilities, proactively adjusting its behavior based on new inputs, unexpected changes, or emerging patterns. It functions more like an independent entity than a programmed tool. Agentic AI is modeled on human-like intelligence, meaning it doesn’t just respond to commands but can initiate actions independently. This includes setting intermediate goals, prioritizing tasks, and iterating on previous efforts to improve results. It can navigate uncertainty, make real-time adjustments, and optimize decisions without constant human oversight. What sets agentic AI apart is its ability to self-direct. It doesn’t require explicit step-by-step instructions for every scenario—it learns from experience, understands context, and makes informed choices to achieve its objectives. This makes it particularly valuable in dynamic environments with insufficient predefined rules. Examples of agentic AI include self-driving cars that adapt to unpredictable traffic conditions, AI-powered research assistants that generate and test scientific hypotheses, and autonomous trading systems that make investment decisions based on real-time market shifts. These systems don’t just follow orders; they work toward goals, improving over time through continuous feedback loops. As AI evolves, agentic capabilities will... --- - Published: 1403-12-17 - Modified: 1403-12-17 - URL: https://tirotir.ir/words-as-weapons-defending-genai-apps-against-prompt-injection/ - دسته‌ها: other As enterprises race to integrate generative AI into their applications and workflows, adversaries are finding new ways to exploit language models through prompt injection attacks to leak sensitive data and bypass security controls. But how do these attacks actually work, and what can organizations do to defend their GenAI applications against them? Join us for an exclusive deep dive with Rob Truesdell, Chief Product Officer at Pangea, as we explore the evolving landscape of prompt injection threats and the latest strategies to secure GenAI applications. Register now This session will cover: How prompt injection works – A breakdown of direct and indirect techniques, with real-world attack examples and data. What LLM providers are doing – A look at native defenses built into top models to counteract prompt injection risks. The insider vs. outsider threat – How adversaries both inside and outside an organization can manipulate GenAI models. Risk mitigation strategies – Engineering and security best practices to prevent, detect, and respond to prompt injection attempts. Measuring effectiveness – How to evaluate the efficacy of prompt injection detection mechanisms. This webinar is a must-attend for security leaders, AI engineers, and product teams looking to understand and mitigate the risks of AI-powered applications in an increasingly adversarial landscape. --- - Published: 1403-12-17 - Modified: 1403-12-17 - URL: https://tirotir.ir/your-guide-to-generative-ai/ - دسته‌ها: other Generative artificial intelligence (AI) lets users quickly create new content based on a wide variety of inputs. These can be text, images, animation, sounds, 3D models, and more. These systems use neural networks to identify patterns in existing data, producing fresh and unique content. One significant advancement in generative AI is the capacity to utilize various learning methods, like unsupervised or semi-supervised learning, during training. This allows individuals to efficiently use vast amounts of unlabeled data to construct foundation models. These models serve as the groundwork for multifunctional AI systems. How do you evaluate generative AI models? There are three main requirements of a successful generative AI model: 1. Quality Mainly important for applications that interact with users directly, a high-quality generation output is vital. In speech generation, for example, having poor speech quality means it’ll be difficult to understand, and in image generation, outputs need to be visually indistinguishable from natural images. 2. Diversity Good generative AI models can capture minority modes in their data distribution without compromising on quality. This leads to a minimization of undesired biases in learned models. 3. Speed A wide variety of interactive applications need fast generation, like real-time image editing for content creation workflows. How do you develop generative AI models? There are several types of generative models; combining their positive attributes will lead to even more powerful models: Diffusion models Also known as denoising diffusion probabilistic models (DDPMs), these determine vectors in latent space through a two-step process when in training. Forward... --- - Published: 1403-12-17 - Modified: 1403-12-17 - URL: https://tirotir.ir/next-gen-ai-architectures-exploring-the-next-wave-of-intelligent-computing/ - دسته‌ها: other As a result of artificial intelligence's continuous evolution, there's an increasing and ever present demand for more efficient, faster and scalable AI solutions. Traditional AI models, especially deep learning approaches, always require exhaustive computational resources which can make them massively expensive and power-hungry. In light of these challenges, there are many next-generation AI architectures that are emerging as promising alternatives such as hyperdimensional computing (HDC), neuro-symbolic AI (NSAI), capsule networks, and low-power AI chips. This article is an exploration into how these innovations can power AI algorithms, in turn making them more efficient and accessible for business use cases and applications. Hyperdimensional computing (HDC) for AI acceleration Hyperdimensional computing (HDC) is a novel type of computing paradigm that fully encodes and processes information using high-dimensional vectors. HDC is very different from normal computing models that tend to need to use exact numerical operations, HDC is a way to create AI that mimics the way our brain encodes and processes information in turn enabling faster learning and better generalisation. Why is HDC impacting the future of AI? Accelerated learning: Contrary to normal deep learning models that tend to need thousands of training samples, HDC models excel at learning from a small amount of data whilst not losing accuracy. Robustness: HDC is resistant to noise by default, making it incredibly fit for real-world AI applications in fields such as healthcare, finance, quantum computing and cybersecurity. Energy efficiency: Since HDC relies solely on binary operations instead of super complex floating-point arithmetic it significantly... --- - Published: 1403-12-16 - Modified: 1403-12-16 - URL: https://tirotir.ir/the-failure-of-ai-models-in-enigmaeval-benchmark-limitation-of-ai-agents-in-automation/ - دسته‌ها: other Large Language Models (LLMs) have demonstrated extraordinary performance in various benchmarks, ranging from complex mathematical problem-solving to nuanced language comprehension. However, these same models fail almost completely on EnigmaEval—a test suite specifically designed to measure spatial reasoning and puzzle-solving skills. This glaring gap in AI competency not only highlights the current shortcomings of LLMs but also raises important questions about how to improve them, especially for practical applications in business, engineering, and robotics. In this article, we will explore: LLM performance in math benchmarks vs. EnigmaEval Why LLMs Struggle with simple spatial reasoning The implications for AI-powered automation Potential solutions: Enhancing spatial intelligence through humans, reinforcement learning, and mixture-of-experts (MoE) models 1. LLM performance in math benchmarks vs. EnigmaEval LLMs have proven their worth on a variety of math-focused benchmarks but falter on spatial puzzles: Fig-1 : Excellent in Math, faltering in simple spatial puzzles While these models excel in complex abstract reasoning and numerical computations, their near-total failure in EnigmaEval exposes a significant deficit in spatial reasoning capabilities. Fig-2 : Actual Score Fig-3 : Sample Questions : Link for the entire Q: 2. Why do LLMs struggle with simple spatial reasoning? A. Text-based training bias LLMs are predominantly trained on textual data and are optimized to find linguistic and statistical patterns. Spatial reasoning, particularly when it involves 3D object manipulation or visual geometry, is not well-represented in text corpora. Consequently, these models lack the “visual scaffolding” that humans naturally acquire from interacting with the physical world. B. Lack of... --- - Published: 1403-12-10 - Modified: 1403-12-10 - URL: https://tirotir.ir/building-advanced-ai-systems-challenges-and-best-practices/ - دسته‌ها: other My name is Akash, co-founder and CEO of Bellum. ai. Our mission is to help companies build reliable AI systems in production. In this talk, I'll share insights from working with hundreds of companies using AI, highlighting what works, what doesn’t, and where AI development is headed. The journey to AI innovation Early experiences with AI AI has always been on the horizon, but my moment of realization came about four to five years ago, at the beginning of COVID, when I first experimented with GPT-3’s API. It wasn’t perfect—prone to generating random, inaccurate responses—but it demonstrated a capability never seen before: auto-completing sentences in a meaningful way. At that time, I was working in recruiting software, leveraging AI for tasks like job description generation and email classification. Our AI-powered job description generator went viral, demonstrating the potential for AI-driven automation. However, implementing these models in production came with significant challenges—prompt engineering, evaluation, and pipeline collaboration were all difficult. The breakthrough with ChatGPT When ChatGPT launched in November 2022, it was clear that AI was going mainstream. The challenges we faced with implementing AI in production—reliability, evaluation, and collaboration—became widespread across industries. Recognizing this, my co-founders and I started Bellum. ai to help businesses effectively leverage large language models (LLMs) and build robust AI systems. Additionally, my experience at McKinsey provided insight into AI governance and the evolution of AI technologies. Witnessing the rise of GPT models and their growing impact across industries reaffirmed the need for structured AI deployment... --- - Published: 1403-12-10 - Modified: 1403-12-10 - URL: https://tirotir.ir/microsofts-majorana-hype-real-proof-or-just-marketing/ - دسته‌ها: other Introduction: The quest for reliable qubits Quantum computing faces a fundamental challenge: qubits, the basic units of quantum information, are notoriously fragile. Conventional approaches, such as superconducting circuits and trapped ions, require intricate error-correction techniques to counteract decoherence. Microsoft has pursued an alternative path: Majorana-based topological qubits, which promise inherent noise resistance due to their non-local encoding of quantum information. This idea, based on theoretical work from the late 1990s, suggests that quantum states encoded in Majorana zero modes (MZMs) could be immune to local noise, reducing the need for extensive error correction. Microsoft has invested two decades into developing these qubits, culminating in the recent "Majorana 1" prototype. However, given past controversies and ongoing skepticism, the scientific community remains cautious in interpreting these results. The scientific basis of Majorana-based qubits Topological qubits derive their stability from the spatial separation of Majorana zero modes, which exist at the ends of specially engineered nanowires. These modes exhibit non-Abelian statistics, meaning their quantum state changes only through specific topological operations, rather than local perturbations. This property, in theory, makes Majorana qubits highly resistant to noise. Microsoft's approach involves constructing "tetrons," pairs of Majorana zero modes that encode a single logical qubit through their collective parity state. Operations are performed using simple voltage pulses, which avoids the complex analog controls required for traditional superconducting qubits. Additionally, digital measurement-based quantum computing is employed to correct errors passively. If successful, this design could lead to a scalable, error-resistant quantum architecture. However, while the theoretical framework... --- - Published: 1403-12-09 - Modified: 1403-12-09 - URL: https://tirotir.ir/revolutionize-business-onboarding-processes-in-the-ai-era-kyb-solution/ - دسته‌ها: other Manual verification, checking, and onboarding are things of the past. Nowadays, with the emergence of artificial intelligence technology, almost all operations have become streamlined and automated. Pre-trained algorithms of artificial intelligence and machine learning help organizations reduce manual efforts, which are time-consuming and not free from errors. Human beings can commit mistakes for being fatigued or under workload pressures. However, AI technology is free from fatigue and workload pressure, and automated checks perform quick actions with just a single click. Therefore, companies have now replaced manual processes with automated ones and are moving toward a streamlined process for all operations. Artificial intelligence has revolutionized the business onboarding process and enables organizations to streamline their operations regarding partnerships, investments, and other kinds of collaborations with other entities. This blog post will highlight the role of AI technology in business onboarding and will explain how it has revolutionized the process. How can AI revolutionize the onboarding process? Companies have to deal with customers, employees, and other organizations for various purposes. There is a need for a streamlined process for onboarding. Before allowing access to entities on board, it is necessary to verify their authenticity and legitimacy and it is a major part of the onboarding process. Traditionally, companies verify entities manually, and perform all the steps included in the onboarding process with human efforts. Employees collect various documents, analyze them, verify them, and then onboard entities. However, it is no longer needed, companies can now verify entities remotely and streamline their onboarding... --- - Published: 1403-12-06 - Modified: 1403-12-06 - URL: https://tirotir.ir/generative-ai-summit-austin-2025/ - دسته‌ها: other Catch up on every session from the Generative AI Summit Austin with sessions from the likes of DLA Piper, Wayfair, Vellum and many more. --- - Published: 1403-12-01 - Modified: 1403-12-01 - URL: https://tirotir.ir/ai-image-detection-types-applications-and-future-trends/ - دسته‌ها: other This technology is being used to identify fake photos. An AI-powered tool called Photoshop Detector can recognize and detect a variety of objects, patterns, pictures, and more. The system uses a lot of data, objects, or photos to learn for this goal. In this manner, the system will use its observations and learnings to identify the object and photographs. Additionally, the picture Photoshop detector offers itself as a safe substitute for current security tools and procedures, especially when combined with cutting-edge AI software and machine learning technology. Faster examination of the provided data is made possible by the addition of advanced tools, which increase the technology's overall accuracy and efficiency. Additionally, the technology makes it possible for numerous platforms and regulated businesses to protect their systems. Role of ,earning Human brains are used to finding a specific object in an image. We humans can do this at any time without thinking for a while. But for computers, this task is not that easy. This is the reason tech companies are training systems with artificial intelligence to perform tasks like humans without even thinking. To train the system, it is important to provide it with various examples or samples of the object. In short, the system needs labeled images to learn about the objects, their size, shapes, and everything. There is not a specific number of images provided to the system but it is observed that the more pictures, the better will be the learning. Moreover, it is also crucial to... --- - Published: 1403-12-01 - Modified: 1403-11-30 - URL: https://tirotir.ir/how-recommender-systems-support-social-learning-in-companies/ - دسته‌ها: other What do the streaming service Netflix, the business platform LinkedIn, and the dating portal Tinder have in common? All three use so-called recommender systems (RS). RS can suggest exactly the right series for an evening of binge-watching. They show candidates for expanding your own business network who are dealing with the same topics. Or they recommend potential partners who are suitable for a long-term relationship or for a nice evening for those looking. In the area of learning, and especially corporate learning, they can take existing e-learning platforms to a whole new level and provide valuable didactic support. And they can create the basis for forms of social learning. Recommender systems are software solutions that suggest movies and series, potential dating partners, shopping products, the next online course, and other things that will most likely interest users. RS, therefore, intervenes in the human decision-making process and can guide it and even motivate it in the first place. In the learning and corporate learning sector, recommender solutions are no longer a novelty, at least in theory. RS can be the technological basis for adaptive learning systems, which can be used to adapt content and teaching methods to the specific needs of learners, therefore creating the conditions for successful knowledge and skills development. But RS can do even more. They can lay the foundation for successful collaborative learning, in which learners work together for their mutual benefit. How can such systems specifically support learners and trainers? And why are recommender systems much... --- - Published: 1403-11-29 - Modified: 1403-11-29 - URL: https://tirotir.ir/ai-agents-the-future-of-automation-and-intelligent-assistance-2025-guide/ - دسته‌ها: other Imagine having a personal assistant who can not only schedule your appointments and send emails but also proactively anticipate your needs, learn your preferences, and complete complex tasks on your behalf. That’s the promise of AI agents — intelligent software entities designed to operate autonomously and achieve specific goals. What are AI agents? In simple terms, an AI agent is a computer program that can perceive its environment, make decisions, and take actions to achieve a defined objective. They’re like digital employees, capable of handling tasks ranging from simple reminders to complex problem-solving. Prompt engineering: How to talk to AIs like ChatGPT? This article serves as a primer on prompt engineering, delving into the array of techniques used to control LLMs. AI Accelerator InstituteJudicael Poumay (Ph. D. ) Key characteristics of AI agents Perception: Agents can sense their environment through sensors (like cameras, microphones, or data feeds). Think of it like our senses: sight, hearing, touch, etc. , that give us information about the world around us. Decision-making: Based on their perception, agents use AI algorithms to make informed decisions. This is like our brain processing information and deciding what to do next. Action: Agents can perform actions in their environment, such as sending emails, making purchases, or controlling devices. This is like our bodies carrying out the actions our brain decides upon. Autonomy: Agents can operate independently without constant human intervention. They can learn from their experiences and adapt to changing circumstances. This is similar to how we learn... --- - Published: 1403-11-26 - Modified: 1403-11-26 - URL: https://tirotir.ir/prompt-engineering-how-to-talk-to-ais-like-chatgpt/ - دسته‌ها: other It’s challenging to meet someone who hasn’t heard about GPT and other similar models this year. These Large Language Models (LLMs) signify a groundbreaking shift in the domains of machine learning and artificial intelligence. A field that remained obscure for most of its history is now an integral part of daily life for a vast segment of the global population, with tools like ChatGPT. As a researcher dedicated to this field for over four years, I have extensively used these tools, particularly this year. This journey has greatly deepened my understanding of LLMs and the art of prompt engineering. Consequently, this article serves as a primer on prompt engineering, delving into the array of techniques used to control LLMs. What are prompts and prompt engineering? Prompt engineering is the strategic creation prompts for pre-trained models like GPT, BERT, and others; prompts describe what we request the model to do. This process aims to steer these models towards generating a specific behavior that we seek. Successful prompt engineering hinges on meticulously defining the prompt with appropriate examples, relevant context, and clear directives. It demands a profound understanding of the model’s underlying mechanisms and the nature of the problem at hand. This knowledge is crucial to ensure that the examples incorporated in the prompt are as representative and varied as possible, closely mirroring the real-world distribution of input-output pairs that characterize the problem. Consider the simple task of translating text from English to French. Achieving this through prompt engineering is remarkably straightforward.... --- - Published: 1403-11-25 - Modified: 1403-11-25 - URL: https://tirotir.ir/ibms-leadership-in-generative-ai-insights-from-manav-cto-of-ibm-canada/ - دسته‌ها: other At the recent Generative AI Summit in Toronto, I had the opportunity to sit down with Manav Gupta, the CTO from IBM Canada to explore the company’s current work in generative AI and explore their vision for the future. Here are the key insights from our conversation, highlighting IBM’s ecosystem leadership, industry impact, and strategies to navigate challenges in the generative AI landscape. IBM’s position in the generative AI landscape Manav began by emphasizing IBM’s commitment to ensuring that enterprises own their AI agenda. He stressed the importance of AI being open and accessible to organizations, individuals, and societies to foster growth. To this end, IBM leads with Watson X, a comprehensive platform that serves as both a model garden and a prompt lab. Watson X allows users to leverage IBM-supplied models, third-party models, or even fine-tune their own models for deployment on their preferred cloud or on-premises infrastructure. One of the standout features of IBM’s approach is its focus on AI governance. Manav highlighted the critical need for enterprises to ensure that the AI they deploy is free from biases, hate speech, and other ethical concerns. IBM’s governance platform is designed to address these issues, ensuring that generative AI outputs are safe and unbiased. The transformative impact of generative AI When asked about the impact of generative AI across industries, Manav was unequivocal in his belief that this technology will touch every sector. He cited estimates that generative AI could add up to 3. 5 basis points to global... --- - Published: 1403-11-24 - Modified: 1403-11-24 - URL: https://tirotir.ir/investai-europes-200-billion-move-to-lead-in-ai-innovation/ - دسته‌ها: other At the artificial intelligence (AI) Action Summit in Paris on February 11, President Ursula von der Leyen introduced InvestAI, a groundbreaking initiative to mobilize €200 billion for AI investment. Central to this effort is a €20 billion European fund dedicated to AI gigafactories—large-scale infrastructure designed to foster open, collaborative development of the most advanced AI models and position Europe as a global AI leader. President Ursula von der Leyen stated: "AI has the potential to revolutionize healthcare, accelerate research, and enhance Europe’s competitiveness. We want AI to be a force for both good and growth. Our European approach—rooted in openness, collaboration, and top-tier talent—lays the foundation, but we need to go further. "That’s why, in partnership with Member States and industry, we are mobilizing unprecedented capital through InvestAI for European AI gigafactories. This public-private initiative, akin to a ‘CERN for AI,’ will empower scientists and businesses of all sizes—not just the largest—to develop cutting-edge AI models and solidify Europe’s position as an AI powerhouse. " European Investment Bank President Nadia Calviño added: "The EIB Group, in collaboration with the European Commission, is reinforcing its support for AI—a key driver of European innovation and productivity. " AI gigafactories: Scaling Europe's AI capabilities InvestAI will fund four AI gigafactories across the EU to train the next generation of complex, large-scale AI models. These facilities will provide the computing power needed to drive breakthroughs in medicine and scientific research. Each gigafactory will house approximately 100,000 next-generation AI chips—four times more than today’s AI... --- - Published: 1403-11-17 - Modified: 1403-11-17 - URL: https://tirotir.ir/agentic-code-gen-the-future-of-software-development-and-emerging-market-leaders/ - دسته‌ها: other The software development landscape is undergoing a seismic shift with the advent of agentic code generation. This transformative technology, powered by generative AI, enables autonomous systems to write, test, and optimize code with minimal human intervention. As enterprises strive to accelerate development cycles, reduce costs, and improve code quality, agentic code generation is emerging as a critical enabler. Download the Agentic Code-Gen Ecosystem Map 2025 below. What is agentic code generation? Agentic code generation leverages AI systems, often built on LLMs, to generate and refine code autonomously. These AI agents can interpret natural language prompts, analyze existing codebases, and produce high-quality, context-aware code tailored to specific requirements. Unlike traditional code-generation tools, agentic systems go beyond simple code snippets—they can debug, optimize, and even deploy code, making them invaluable for enterprises looking to streamline their software development processes. The technology is particularly impactful in automated testing, legacy code modernization, and rapid prototyping. For example, AI agents can convert outdated codebases into modern programming languages or generate entire microservices architectures based on high-level design specifications. If you're ready to use or deploy industry-ready agents that are cost-effective, powerful and value-driving, join us at the world's first Agentic AI Summit: Agentic AI Summit, New York, June 5 Agentic AI Summit, Berlin, September 11 Agentic A Summit, Toronto, November 20 Emerging market leaders in agentic code generation While established tech giants like GitHub and OpenAI dominate headlines, a new wave of innovative companies is making significant strides in agentic code generation. Bolt (by StackBlitz)... --- - Published: 1403-11-17 - Modified: 1403-11-17 - URL: https://tirotir.ir/ai-solutions-lessons-from-the-generative-ai-summit/ - دسته‌ها: other At the Generative AI Summit in Toronto, we had the chance to sit down with Manav Gupta, VP and CTO at IBM Canada, for a quick but insightful chat on IBM’s leadership in generative AI. From groundbreaking projects to industry-wide transformation, here are the key takeaways from our conversation. Or you can check out the full interview right here: IBM’s Approach to Generative AI IBM isn’t just riding the generative AI wave—they’re shaping it. According to Manav, IBM believes that enterprises must own their AI agenda and that AI should be open, accessible, and built with governance at its core. Their secret weapon? Watsonx, a platform that gives users access to IBM’s models, third-party models, and tools to fine-tune AI for their needs. Whether deployed on the cloud or on-premises, Watsonx aims to provide flexibility while ensuring AI remains responsible and enterprise-ready. Speaking of responsibility, AI governance is another major focus. IBM is tackling critical issues like bias, misinformation, and ethical concerns to make sure AI outputs are free of hate, abuse, and biases. In short—powerful AI, but with guardrails. How generative AI is transforming industries Manav didn’t hold back on the impact AI is having across sectors. From banking to healthcare, public sector to telecoms, generative AI is unlocking efficiencies by handling repetitive tasks, allowing humans to focus on higher-value work. And the numbers speak for themselves—some analysts predict AI could add up to 3. 5 basis points to global GDP. That’s no small feat. The biggest hurdles in... --- - Published: 1403-11-10 - Modified: 1403-11-10 - URL: https://tirotir.ir/deepseeks-ai-breakthrough-fewer-resources-big-impact/ - دسته‌ها: other On December 26th, a modest-sized Chinese company named DeepSeek introduced advanced AI technology, rivaling the top chatbot systems from giants like OpenAI and Google. This achievement was noteworthy for its capability and the cost-efficiency with which it was developed. Unlike its large competitors, DeepSeek created its artificial intelligence, DeepSeek-V3, using significantly fewer specialized processors, which are typically essential for such advancements. Cost efficiency and technological breakthrough These processors are at the heart of a fierce tech rivalry between the U. S. and China. The U. S. aims to keep its lead in AI by restricting the export of high-end chips, such as those from Nvidia, to China. However, DeepSeek's success with fewer resources raises concerns about the effectiveness of U. S. trade policies, which have inadvertently spurred Chinese innovation using more accessible technologies. DeepSeek-V3 impressively handles tasks like answering queries, solving puzzles, programming, and matching industry standards. Remarkably, it was developed with just around $6 million worth of computing resources, starkly contrasting the $100 million Meta reportedly invested in similar technologies. Chris V. Nicholson from Page One Ventures pointed out that more companies could afford $6 million than the heftier sums, democratizing access to advanced AI technology. Strategic implications and global impact of DeepSeek Previously, experts believed only firms with substantial financial resources could compete with leading AI firms, which train their systems on supercomputers requiring thousands of chips. DeepSeek, however, managed with just 2,000 chips from Nvidia. This efficient use of limited resources reflects the forced innovation resulting from... --- - Published: 1403-11-05 - Modified: 1403-11-05 - URL: https://tirotir.ir/top-gen-ai-llmops-agentic-ai-and-caio-events-to-attend-in-2025/ - دسته‌ها: other 2025 is already shaping up to be bigger than 2024 for artificial intelligence — and we’re no different. This year, we’re bringing you even more events than last year. That’s right, we have 19 in-person events you can attend — that’s three more than 2024. Save the dates now because 2025 will be a busy and exciting year for generative AI, LLMOps, agentic AI, and Chief AI Officers (CAIO). We’ll be going on a world tour with plenty of events you can choose from. Choose a month below: February March April May June August September October November February Generative AI Summit | Austin When: February 12 Where: Hilton Austin, 500 East 4th Street, Austin We’re starting the year with Austin, where our first Generative AI Summit will be. This event brings together global AI leaders, innovators, and industry pioneers to share actionable insights, groundbreaking research, and real-world applications of AI. With a packed agenda covering key topics like observability and security for LLMs, building advanced AI systems, and more, this is your chance to gain exclusive knowledge, network with decision-makers, and stay ahead in the AI revolution. Don’t miss out: be part of the conversation driving AI innovation forward. Register now # Take part in the conversation! #AIAIAustin March Generative AI Summit | Washington, D. C. When: March 05 Where: Hilton Washington DC National Mall The Wharf, 480 L'Enfant Plaza Southwest Our first Generative AI Summit in D. C. , where industry leaders and innovators will explore the latest breakthroughs... --- - Published: 1403-11-02 - Modified: 1403-11-02 - URL: https://tirotir.ir/uks-ai-supercomputer-to-transform-drug-development/ - دسته‌ها: other A groundbreaking £225 million supercomputer, Isambard-AI, is set to revolutionize the medical field by aiding in the development of new drugs and vaccines using artificial intelligence. Situated in Bristol, this state-of-the-art facility will become the most potent supercomputer in the UK when it becomes fully operational this summer. National initiative to boost AI Prime Minister Sir Keir Starmer recently announced initiatives to enhance AI integration across the UK, aiming to stimulate economic growth. This effort aligns with the capabilities of the Isambard-AI, which, according to Simon McIntosh-Smith, a high-performance computing professor at Bristol University, positions the UK to compete globally in the AI arena. Professor McIntosh-Smith revealed on BBC Radio Bristol that parts of the Isambard-AI system are already functional, with ongoing projects that explore new treatments for diseases like Alzheimer’s, heart disease, and various cancers. Additionally, the supercomputer is enhancing research into melanoma detection across diverse skin tones. Building artificial intelligence for drug discovery AI can create models that predict a compound’s potential and run this model on millions of compounds to find the most promising options. AI Accelerator InstituteGregg W. Casey How AI enhances drug development Explaining the operational dynamics, professor McIntosh-Smith highlighted that AI in Isambard-AI simulates drug interactions within the body down to the molecular level. Traditionally, scientists relied on educated guesses and experience to predict how drugs would interact with specific proteins. Now, AI can expedite this process by evaluating numerous potential drug compounds virtually, which enhances efficiency and reduces the need for physical experiments.... --- - Published: 1403-11-01 - Modified: 1403-11-01 - URL: https://tirotir.ir/transforming-aml-exploding-the-potential-of-ai-solutions/ - دسته‌ها: other Do you need a captivating method of presenting your anti-money laundering (AML) system to clients? As a result of the increasing number of online transactions, fraudsters, and money launderers have had their work made easier. An AML AI solution is a powerful tool that can help you fend off these threats and protect your financial environment. A sentiment not far off from what President Abraham Lincoln once noted about the future saying, “The best way to predict the future is to create it. ” Nowadays, AI systems are leading by example and improving the process of combating money laundering. AI technology used in AML systems provides distinctive features essential to AML compliance. It speeds up transaction monitoring, enhances it, and helps institutions beat offenders while keeping the law on their side. This paper discusses how AML AI solutions can change the economic crime-fighting landscape in this article. 1. Facilitated efficiency of transaction monitoring An AML AI solution boosts transaction monitoring by reducing errors by an average of 90%. Modern AI systems work in real-time processing data significantly faster than employing ordinary methods. They outperform other traditional methods in pattern recognition and identification of suspicious activities, and greatly reduce the number of false alarms. For instance, false positives within AI web services have decreased by up to 80% recently rendering significant time and resources to financial institutions. This means that AML systems are able to invest their efforts in any suspicions or alerts that may be genuine. This precision helps in... --- - Published: 1403-10-26 - Modified: 1403-10-26 - URL: https://tirotir.ir/austin-not-necessarily-the-new-silicon-valley-but/ - دسته‌ها: other Ranked 17th globally in StartUp Blink's 'Best Cities for Startups' 2024 rankings - an index factoring quality, quantity and growth - Austin's tech force and industry is still booming: over 7,500 companies, employing 180,000+, representing >13% of the city's workforce. By headcount, the city's industry is predicted to grow 3. 2% this year . 50 years & counting of pioneering innovation From the '60s with Tracor, IBM, and Texas Instruments, to the '83 arrival of MCC, to Michael Dell's '84 dorm room startup - Austin has a history of powerhouse innovators. Fast-forward to 2018, Apple's $1 billion investment plans in Austin solidified its position as the company's second-largest location outside California, and significantly impacted the city's future. Today, giants like AMD, Tesla & Google call Austin home - or at least a significant second home. The city's blend of startups and established companies fosters a dynamic ecosystem, and UoT consistently graduates top talent, fuelling the industry. Mapping Austin's Generative AI Ecosystem Embedded in the applied AI landscape globally, AI Accelerator Institute is attempting to map its entirety. With the support of Austin AI Alliance & AustinNext, featured below is an ecosystem map of Austin's major players across both application and infrastructure: Generative AI Ecosystem Map: Austin What's the draw? Austin not only breeds its own, but attracts top talent with a number of competitive advantages. In short: Silicon Valley-level innovation at a lower cost and a higher quality of life. No state income tax and significantly lower housing costs than... --- - Published: 1403-10-25 - Modified: 1403-10-25 - URL: https://tirotir.ir/uks-ai-blueprint-ai-opportunities-action-plan/ - دسته‌ها: other The United Kingdom stands as the third-largest artificial intelligence (AI) market globally, boasting a rich history of scientific innovation and hosting major AI players like Google DeepMind and ARM. Despite this, the rapid advancements in AI by the United States and China pose a risk of the UK falling behind. The UK government recognizes the urgency to participate in and shape the AI revolution, drawing from its historical contributions to computing and the internet. Strategic initiatives for AI advancement One of the earliest actions taken by the new Secretary of State for Science, Innovation and Technology, Rt Hon Peter Kyle MP, was to commission an AI Opportunities Action Plan. This ambitious plan is designed to leverage AI for economic growth, improved public services, and personal opportunities. It emphasizes the UK's role in global AI safety and governance leadership and outlines a comprehensive approach to effectively integrate AI into the social market economy. Core areas of focus in the AI action plan 1. Building AI infrastructure The UK government is committed to enhancing its AI infrastructure to support current and future needs. This involves expanding the AI Research Resource to facilitate advanced AI research and ensuring sufficient access to high-performance computing power. Plans include establishing AI Growth Zones to accelerate data center construction and forming international compute partnerships to bolster the UK's capabilities. UK Government prioritizes AI for economic growth and services The UK places AI at the center of its strategy for economic growth and improved public services, led by... --- - Published: 1403-10-25 - Modified: 1403-10-25 - URL: https://tirotir.ir/ai-salary-survey-2024-25-results/ - دسته‌ها: other Have you ever wondered how your salary stacks up against other AI professionals? Or questioned whether that promotion was really enough to keep pace with the market? This year, we surveyed AI professionals across the globe to create a comprehensive AI Salary report. Navigating the landscape of AI careers can be like navigating a labyrinth: exciting yet unpredictable. One day you're pioneering breakthroughs, the next you're pondering if your salary matches your contributions. Imagine having a guide that clarifies precisely what your expertise in AI is worth: no uncertainties, no uneasy discussions about compensation, no more groping in the dark. Our AI Salary Report for 2024/25 serves as this essential guide. We've analyzed the earnings data from countless AI professionals across the globe to equip you with clear insights into what your skills command in the market. Dive deep into our findings to see how experience, company size, sector, geographical location, and educational background can significantly influence your salary. Don't leave your salary to chance. Gain clarity and confidence with our report. Already an AIAI member? Grab your copy (no form-filling required ) here. Download your copy to... Benchmark your salary against other professionals in similar industries, regions, and roles. Map out your next career move – and earmark a suitable pay packet. Discover whether you’re being paid your worth. Negotiate your next salary with confidence. --- - Published: 1403-10-19 - Modified: 1403-10-19 - URL: https://tirotir.ir/insider-threats-amplified-by-behavioral-analytics/ - دسته‌ها: other In the realm of cybersecurity, behavioral analytics has emerged as a powerful tool for detecting anomalies and potential security threats by analyzing user behavior patterns. However, like any advanced technology, it comes with its own set of risks—particularly when it comes to insider threats. The very data and insights that make behavioral analytics so effective can also be leveraged by malicious insiders to amplify the damage they can inflict. How behavioral analytics works Behavioral analytics tracks user activities—such as login times, access patterns, file usage, and communication habits—to establish a baseline of "normal" behavior. When deviations from this baseline occur, the system flags them as potential security concerns. This method is particularly useful for identifying sophisticated attacks that bypass traditional security measures. The double-edged sword of behavioral analytics While the ability to detect deviations in user behavior is invaluable for cybersecurity, it also presents significant risks if the data and insights generated by behavioral analytics are misused. This is where the danger of insider threats is magnified. 1. Informed malicious insiders: One of the most significant risks comes from insiders who have legitimate access to behavioral analytics data. These individuals, whether they are disgruntled employees, compromised insiders, or even careless users, can gain deep insights into what triggers security alarms and how the organization's monitoring systems operate. With this knowledge, they can tailor their malicious activities to avoid detection, effectively bypassing the very systems designed to protect the organization. 2. Targeted attacks on individuals: Behavioral analytics can provide detailed profiles... --- - Published: 1403-10-14 - Modified: 1403-10-14 - URL: https://tirotir.ir/llmops-optimizing-towards-enterprise-value-in-the-llm-agentic-era/ - دسته‌ها: other The rise of LLMs, and more recently the push to 'taskify' these models with agentic application, has ushered in a new era of AI. However, effectively deploying, managing & optimizing these models requires a robust set of tools and practices. Enter one of enterpise's most vital functions in 2025, LLMOps: a set of methodologies and tech stacks that aim to streamline the entire lifecycle of LLMs, from development and training, to deployment and maintenance. LLMOps Ecosystem Map: 2025 AI Accelerator Institute's recently released LLMOps Ecosystem Map: 2025 provides a comprehensive view of the tools and technologies currently available for LLM build & management. Excluding foundational LLM infrastructure and purely breaking down the Ops lifecycle, the map categorizes the landscape into 9 key areas: ObservabilityOrchestration & model deploymentApps/user analyticsExperiment tracking, prompt engineering & optimizationMonitoring, testing, or validationCompliance & riskModel training & fine-tuningEnd-to-end LLM platformSecurity & privacyLLMOps Ecosystem Map 2025 This map underscores the growing maturity of the LLMOps ecosystem moving into 2025, with a monstrous range of tools available now for every stage of the LLM lifecycle. Want to build out exceptional LLMOps infrastructure? Join AIAI in-person at an LLMOps Summit. → LLMOps Summit Silicon Valley | April 29, 2025 → LLMOps Summit Boston | October 29, 2025 Why is LLMOps crucial in 2025? LLMOps plays a critical role in enabling rapid innovation and enterprise agility by: Accelerating time-to-market: LLMOps tools automate many of the manual tasks involved in deploying and managing LLMs, reducing development time and accelerating the time-to-market for... --- --- > © 2025 وب‌سایت هوش مصنوعی داریوش. برای تماس یا درخواست به‌روزرسانی این فایل LLMS.txt، با ایمیل info@tirotir.com در ارتباط باشید. ---