Videos de agentic AI
Videos etiquetados con "agentic AI"
agentic AI 6 videos
Enterprise AI in Europe: IDA Ireland on Regulation, Talent & What's Driving Global Investment
What makes a country truly AI-ready in 2026? In this episode of UC Today, host Christopher Carey sits down with John Durcan, Chief Technologist at IDA Ireland — Ireland's Foreign Direct Investment Agency — to explore how enterprises are approaching AI adoption, what's driving global tech investment decisions, and why regulation might actually be Europe's secret weapon. John shares insights from his conversations with multinational companies on the ground in Ireland, covering: What separates AI-ready countries from the rest How the EU AI Act is shaping enterprise strategy The rise of agentic AI across financial services, MedTech, and life sciences Why digital sovereignty is now a boardroom conversation The real impact of AI on jobs — and what companies are doing about it Whether you're a technology leader, investor, or enterprise decision-maker, this is a conversation you won't want to miss.
Day - 03 : GEN AI + LLM + RAG + Agentic AI Overview by Mr. Ashok
Artificial Intelligence is changing the way software applications are built. In this session, Mr. Ashok explains the most important AI concepts every student and developer should know. In this video, you will learn: ✅ What is Generative AI? ✅ What are Large Language Models? ✅ How RAG works in real-time applications ✅ What is Agentic AI? ✅ Difference between LLM, RAG, and AI Agents ✅ Real-world use cases of Gen AI ✅ Career opportunities in AI This session is useful for students, freshers, working professionals, Java developers, Python developers, and anyone who wants to start learning AI from basics. 📌 Watch the full session and start your AI learning journey today. #GenAI #LLM #RAG #AgenticAI #ArtificialIntelligence #AIOverview #GenerativeAI #PromptEngineering #AIForBeginners #AshokIT #MrAshok #PythonAI #AICareer #MachineLearning #TechLearning
Europe’s AI Rulebook Bias, Surveillance, and the Brussels Effect
What happens when governments decide artificial intelligence is too important to be left unregulated? In this episode of The Human Workforce Podcast, Simon Carver, Lachlan Reed, and CJ Murphy explore the European Union's landmark AI Act—the world's first comprehensive framework for regulating artificial intelligence. The discussion examines why Europe became the first major region to establish AI governance rules, how the Act classifies AI systems based on risk, and what the new requirements mean for employers, technology providers, and workers. Topics include: • Why the EU chose a rights-based approach to AI regulation • The four AI risk categories and what they mean • AI-powered hiring and recruitment systems • Employee monitoring and workplace surveillance concerns • AI scoring of workers and performance management implications • Transparency, accountability, and explainability requirements • Compliance challenges for multinational organizations • How European regulations may influence AI governance globally • What workers should understand about AI decision-making in the workplace As AI becomes embedded into hiring, promotions, workforce analytics, and organizational decision-making, the questions of fairness, privacy, and accountability are becoming impossible to ignore. Will the EU AI Act become the global standard for responsible AI governance, or will it slow innovation in a rapidly evolving technology landscape? Join us as we examine one of the most important workforce and technology developments of the decade. #EUAIAct #ArtificialIntelligence #AIGovernance #FutureOfWork #HumanWorkforce #AIRegulation #WorkplaceAI #AIEthics #EmploymentLaw #DigitalTransformation #AICompliance #TechnologyPolicy
04 How Large Language Models (LLMs) Works? | All about LLMs | What are Tokens & Context Length?
Generative AI | LLM | GenAI | NN | Large Language Models ⏰ Scheduled to be Public from Members Only on 01st Jun 2026 16:00 HRS IST ⏰ ===== In this video, you will learn ===== What is Large Language Model? What is LLM? How LLMs work? Next Token Prediction in LLM, What are Tokens and Context Length? Importance on Tokens in LLM, Different Sampling Controls, LLM Personas and Prompts, Probability Distribution for LLMs ===== Chapters ===== 00:00 - Introduction 00:27 - What are Large Language Models or LLMs? 03:44 - How Large is Large in LLMs? 05:44 - Transformers 08:07 - What are Tokens and their Importance in LLM? 08:18 - What is Vocabulary in LLM? 14:27 - Probability Distribution for Tokens 19:01 - Sampling Controls - Temperature, Top-p 25:51 - Auto-Regressive Generation Loop 28:53 - How LLMs preserves meaning? 30:58 - How LLMs are Trained? 33:15 - What is Fine Tuning? 34:28 - LLM Personas/Roles and Prompts 36:55 - What is Context Length? 39:01 - Model Knowledge Cutoff and Hallucination 41:23 - Open and Closed LLM Models 42:36 - Reasoning Models 43:24 - Multimodal Models ===== Links ===== Google's "Attention is all You Need" Paper - https://arxiv.org/pdf/1706.03762 Groq Cloud - https://console.groq.com/home GPT Tokenizer - https://platform.openai.com/tokenizer ===== Other Playlists ===== Checkout all other playlists on Data Engineering 👇🏻 https://www.youtube.com/@easewithdata/playlists ===== GitHub Repo ===== https://github.com/subhamkharwal ===== Connect with ME ===== LinkedIn - https://www.linkedin.com/in/subhamkharwal Medium - https://subhamkharwal.medium.com ===== Hashtags ==== #genai #dataengineering #python #agenticai #aiagents #aiagent #nn #neuralnetworks
Google's I/O 2026 LineUp - OMNI, XR Glasses & Gemini 3.5 That Runs Your Life
The tech titans are spending billions for the prize: our complete digital life. Google is shifting its focus from chatbots to Gemini AI, aiming to make Android an active intelligence system that usheres in the agentic AI era. This push towards AI agents and AI integration highlights the future of AI where Android becomes a truly intelligent system. #GoogleIO #AIAgent #XRGlasses #Gemini #FrontPage #AIMNetwork ------------------------------------------------------------------------------------------ 👋 ABOUT AIM NETWORK AIM Network is India's leading voice on the intersection of AI, Technology, and Business. We bring you sharp analysis, breaking news, and original perspectives on everything from Generative AI breakthroughs to geopolitical market shifts. 🔔 Subscribe for daily insights: https://www.youtube.com/@aimmediahouse?sub_confirmation=1 📺 WATCH OUR POPULAR SERIES: - Front Page (Daily Tech News): https://www.youtube.com/playlist?list=PL9Kc1zSa46OxR8h0ZgAfEENta0vaxfWrs - Tech Talks (Podcast): https://www.youtube.com/playlist?list=PL9Kc1zSa46OyXflFLWtmF5MN3jvdxDFE3 -Simulated Reality (Podcast) - https://www.youtube.com/playlist?list=PL9Kc1zSa46OwqKv91j8W6vZ-V5DucIU4Y 📰 STAY UPDATED: Website: https://analyticsindiamag.com/ LinkedIn: https://in.linkedin.com/company/analytics-india-magazine Twitter/X: https://x.com/Analyticsindiam Instagram: https://www.instagram.com/aim.media.house/ ------------------------------------------------------------------------------------------
AI Evals Explained in 3 Steps 🤯 | How Top AI Companies Test Intelligence
Building an AI model is easy now… But proving that it actually works reliably? That’s the real challenge. In this BazAI breakdown, we explore how modern AI evaluation systems work using a simple 3-step framework. This video covers: ✅ Picking the Right AI Task ✅ Collecting Evaluation Datasets ✅ Developing AI Graders We explain how AI companies evaluate: LLMs, RAG systems, coding agents, autonomous AI workflows, reasoning models, safety systems, and multi-agent architectures. You’ll also learn about: 🔹 LLM-as-a-Judge systems 🔹 Human evaluation pipelines 🔹 Code-based grading 🔹 Benchmark datasets 🔹 AI safety testing 🔹 Agent evaluation frameworks As AI becomes more autonomous, evaluation is becoming more important than model size itself. The future of AI belongs to systems that are measurable, reliable, and trustworthy in real-world environments. Subscribe to BazAI for deep AI engineering breakdowns, autonomous agent systems, multimodal AI, and future technology explained simply.