Videos de large language models
Videos etiquetados con "large language models"
large language models 17 videos
AI That Never Forgets | Dendritron Transformer Explained (The Future of LLMs)
AI That Never Forgets | Dendritron Transformer Explained (The Future of LLMs) What if AI never forgot anything it learned? In this video, we explore the groundbreaking Dendritron Transformer, a next-generation AI architecture designed to overcome one of the biggest limitations of today's Large Language Models (LLMs): catastrophic forgetting. Unlike traditional Transformer models that become static after training, the Dendritron Transformer introduces a bio-inspired internal memory system that enables continuous learning, real-time knowledge updates, and lifelong memory retention without losing previously learned information. If you're interested in Artificial Intelligence, Machine Learning, Deep Learning, Large Language Models (LLMs), AI Agents, Neural Networks, or the future of AI research, this video provides a clear and easy-to-understand explanation of one of the most exciting new AI architectures. 📌 In this video, you'll learn: ✅ What is the Dendritron Transformer? ✅ Why traditional Transformers forget information ✅ What is Catastrophic Forgetting in AI? ✅ How Continuous Learning AI works ✅ Dendritic Computation Explained ✅ Internal Memory vs KV Cache ✅ Lifelong Learning for Large Language Models ✅ Future AI Agents with Persistent Memory ✅ Real-Time Learning in Artificial Intelligence ✅ Applications in Robotics, Healthcare, Finance, Autonomous Systems, and Scientific Research 📚 Colab Notebook: https://colab.research.google.com/drive/1nao2tDffdIThxoH0Nd8_pe_5Gc3JfCZQ?usp=sharing ⭐ If you enjoy videos about Artificial Intelligence, Machine Learning, ChatGPT, OpenAI, Neural Networks, AI Agents, Python, LLMs, Deep Learning, and the latest AI breakthroughs, make sure to Subscribe and turn on notifications so you never miss future videos. 👍 Like the video if you learned something new. 💬 Comment your thoughts about the future of AI memory and continuous learning. • AI News • Machine Learning • Deep Learning • LLM Tutorials • Prompt Engineering • Generative AI • Python for AI • AI Agents • Future Technology #AI #MachineLearning #Dendritron #Transformer #DeepLearning #ContinuousLearning #nlp Dendritron Transformer, AI Memory, Artificial Intelligence, Machine Learning, Deep Learning, Transformer Architecture, Large Language Models, LLM, Continuous Learning, Lifelong Learning, Catastrophic Forgetting, Neural Networks, AI Research, AI Agents, Bio Inspired AI, Real-Time Learning, Future of AI, AI Explained, GPT Alternative, Next Generation AI, AI Architecture, Persistent Memory AI, Memory-Augmented Neural Networks, Cognitive AI, Intelligent Systems #ArtificialIntelligence #MachineLearning #DeepLearning #LLM #Transformer #AI #AIResearch #GenerativeAI #NeuralNetworks #AIAgents #ContinuousLearning #Dendritron #ArtificialGeneralIntelligence #FutureOfAI #AITechnology
Neural Network - How it Works
Neural Network - How it Works 📲 For More Content like this, be sure to Subscribe to our channel! ✅Thanks For Watching: Neural Network - How it Works Here at Thinking Machines, we aim to create top-quality videos about artificial intelligence, machine learning, tech documentaries, AI controversies, big tech developments, robotics, automation, future concepts, and the science shaping tomorrow—covering everything happening in the world of technology and AI. Our goal is to help you understand how AI is changing the world, uncover the stories behind major tech revolutions, and explore the ideas, companies, and breakthroughs building our future. Neural networks learn to recognize patterns by adjusting millions of mathematical connections instead of relying on manually programmed rules. The video explains how raw input data, such as image pixels, flows through layers of neurons that detect increasingly complex features before producing a final prediction. It breaks down key concepts like weights, biases, activation functions, and training in a simple, intuitive way, showing how each component contributes to the network's learning process. You'll also discover why neural networks have become the foundation of modern AI applications, from image recognition and translation to speech processing and self-driving cars. By the end, you'll understand that the power of neural networks comes not from magic or human-like thinking, but from countless simple mathematical operations working together to uncover meaningful patterns. 💻For Business Inquiries, Collaborations or Promotions, contact us at: odedschannel1@gmail.com #neuralnetworks Networks, #artificialintelligence Intelligence, #AI, #machinelearning Learning, Deep Learning, How Neural Networks Work, Neural Network Explained, AI Explained, #aivideo for Beginners, Deep Learning Tutorial, #artificialintelligencetechnology Neural Network, ANN, Weights and Biases, Activation Functions, ReLU, Sigmoid Function, Hidden Layers, Input Layer, Output Layer, Pattern Recognition, Image Recognition, Handwritten Digit Recognition, Computer Vision, AI Training, Backpropagation, Neural Network Training, Parameters, AI Models, Mathematics of AI, Modern AI, Generative AI, Large Language Models, Deep Learning Fundamentals, Data Science, Computer Science, AI Technology, AI Education, #aigenerated Concepts, How AI Learns, Pattern Detection, Predictive Models, Educational Technology, Future of AI, Thinking Machines, Tech Explained, AI Tutorial, Neural Network Basics, Machine Intelligenc
Large Language Models (LLMs) Explained From Scratch (Complete Beginner's Guide) | TAB 47
#largelanguagemodels #llmfullcourse #llmfromscratch Want to understand Large Language Models (LLMs) without complicated math? In this video, you'll learn what a Large Language Model is, how LLMs work, and why models like ChatGPT, Claude, Gemini, and DeepSeek are transforming AI. This complete LLM tutorial for beginners explains every fundamental concept step by step, including language models, AI models, next-word prediction, pre-training, fine-tuning, parameters, weights, biases, datasets, compute, and the difference between Small Language Models (SLMs) and Large Language Models (LLMs). Whether you're preparing for AI Engineering, Machine Learning, Generative AI, Prompt Engineering, or simply want to understand how modern AI works, this video builds a strong foundation from scratch. Click to start your Career in GenAI - MICROSOFT GenAI Course - https://bit.ly/4oxRGaF only Rs 299/ Join our WhatsApp Channel to get the latest updates, learning resources, job trends, and exclusive content : https://whatsapp.com/channel/0029Vb7v6JA3LdQdLhL9rQ2i Below are the concepts covered in this video : 00:26 – Introduction & What You'll Learn 01:54 – What Is a Large Language Model (LLM)? 03:50 – What Is Language? (Vocabulary, Grammar & Meaning) 05:31 – Programming Languages vs Human Languages 06:45 – What Is an AI Model? 10:33 – Models as Mathematical Approximations 12:13 – What Is a Language Model? 12:48 – Next Word Prediction Explained 15:10 – Why Is It Called a Large Language Model? 17:27 – Datasets, Parameters & Compute 18:43 – Weights, Biases & Parameters 19:22 – Small Language Models (SLMs) vs Large Language Models (LLMs) 21:48 – LLM Recap: Language + Model + Large 22:24 – Sequence Prediction Example 26:44 – Pre-training vs Fine-tuning 28:57 – Discriminative vs Generative Models 29:41 – What Is a Generative Model? #generativeai #deeplearning #llm #softwareengineer #webdevelopment #localllm #aiagents #aitools #llmtutorial
Large Language Models (LLMs) Explained | No Coding Required | Vishwa sir | Tab 47
#llm #machinelearning #softwareengineering Want to understand how ChatGPT, Claude, Gemini, and other modern AI models actually work? Join this LIVE LLM Masterclass where we'll break down Large Language Models (LLMs) in the simplest possible way—no coding or programming experience required. Whether you're a student, working professional, AI enthusiast, or someone planning to build AI applications in the future, this live session will help you understand the core concepts behind today's most powerful AI systems. 🔗 Ready to build a career in AI? Join upGrad's Artificial Intelligence Courses and start learning from industry experts: https://bit.ly/4uRBTFU What you'll learn: What are Large Language Models (LLMs)? How ChatGPT and modern AI models work Tokens, embeddings, transformers, and attention explained Training vs inference Prompt engineering fundamentals Open-source vs closed-source LLMs Real-world applications of LLMs How LLMs power AI Agents, RAG, copilots, and automation The best roadmap to start learning Generative AI
Best AEO Tool: Boost Your ChatGPT & Perplexity SEO (GEO)
https://crowdreply.io?fpr=guylian Start your 7-day free trial of CrowdReply and get your AI Visibility Score today! https://calendly.com/d/cv5z-ctz-x4g/crowdreply-demo Book a 1-on-1 demo call to see how it works for your brand. Most AI visibility tools are either way too expensive or just give you "nice data" without telling you what to do next. In this video, we take you inside the CrowdReply dashboard—the all-in-one tool designed to not only track your AI search visibility but give you the exact, actionable steps you need to move the needle. Whether you want to rank higher in ChatGPT, Perplexity, Gemini, or Google AI Overviews, we'll show you exactly how to track your prompts, reverse-engineer your competitors, and build the right citations to dominate AI search. What We Cover in This Tutorial: LLM Visibility Score: How to instantly see where your brand stands across different Large Language Models (LLMs). Cross-Model Prompt Tracking: Why you need to track user prompts across ChatGPT, Gemini, Perplexity, and more all at once—and how to do it without losing your mind. Competitor Reverse-Engineering: Discover exactly what sources (YouTube, Reddit, Wikipedia, high-authority blogs) the AI is using to recommend your competitors over you. Actionable AEO (Answer Engine Optimization): Stop guessing. Learn how to engage directly with cited Reddit threads and buy strategic backlinks that actually tell the AI to rank your brand. Why Actionable AI SEO Matters: Generative Engine Optimization (GEO) isn't just about knowing your rank; it's about closing the loop. By tracking brand mentions, share of voice, and exact citation sources, you can mimic the strategies of top brands in your niche and position yourself as the #1 alternative. CrowdReply puts everything under one roof so you can stop juggling multiple expensive dashboards. Ready to win in the era of Generative AI? Hit subscribe for more tutorials on AI search strategy, AIO tracking, and the future of digital marketing! Timestamps: 0:00 - The Problem with Most AI SEO Tools 0:42 - CrowdReply Dashboard: Your LLM Visibility Score 1:13 - Tracking Prompts Across Multiple LLMs 1:56 - Competitor Analysis: Stealing Your Rivals' Strategy 2:36 - Actionable Citations & Engaging on Reddit 4:35 - Building the Right Backlinks for AI Search 5:28 - Get Your 7-Day Free Trial! Tags & Keywords: #AISEO #CrowdReply #AISearch #ChatGPTSEO #PerplexitySEO #LLMOptimization #GenerativeEngineOptimization #AnswerEngineOptimization #DigitalMarketingTools
Neural Networks Explained in 10 Minutes
Neural Networks are the foundation of modern Artificial Intelligence—and they power many of the AI tools you use every day, including ChatGPT, Claude, Gemini, Copilot, and more. But what exactly is a neural network, and how does it actually work? In this video, you’ll get a simple, non-technical explanation of neural networks in just 10 minutes. No advanced mathematics, no coding, and no computer science degree required. We’ll break down the core concepts behind how AI learns, recognizes patterns, and generates intelligent responses. Whether you’re a manager, business professional, student, entrepreneur, or simply curious about AI, understanding neural networks is one of the most valuable skills you can build in today’s AI-driven world. 📌 In This Video: ✅ What is a Neural Network? ✅ Why Neural Networks Are Important in AI ✅ How Neural Networks Learn Patterns ✅ Input Layer, Hidden Layers & Output Layer Explained ✅ How AI Makes Predictions and Decisions ✅ The Connection Between Neural Networks and Deep Learning ✅ How ChatGPT, Claude, Gemini, and Copilot Use Neural Networks ✅ Real-World Examples of Neural Networks in Business 🎯 Who Should Watch? ✔ Business Professionals ✔ Managers & Team Leaders ✔ Supply Chain Professionals ✔ Operations Leaders ✔ Students & Career Switchers ✔ AI Beginners ✔ Entrepreneurs ✔ Anyone Curious About Artificial Intelligence Understanding neural networks helps you understand the technology behind today’s most powerful AI systems. Once you grasp this concept, topics like Machine Learning, Deep Learning, Large Language Models (LLMs), ChatGPT, and Generative AI become much easier to understand. 🚀 AI is changing every industry. The professionals who understand how it works will be better positioned to leverage it, manage it, and create value with it. 👇 What AI topic would you like explained next? Let me know in the comments. 🔔 Subscribe for more videos on: • Artificial Intelligence • Neural Networks • Machine Learning • Deep Learning • Large Language Models (LLMs) • Generative AI • AI for Business • Supply Chain & Operations • Career Growth • Future of Work
LLM 101: From Basics to Advanced in Minutes
LLM 101: From Basics to Advanced in Minutes What is an LLM? How do Large Language Models work? How does ChatGPT generate human-like responses? In this video, we break down Large Language Models (LLMs) from basics to advanced concepts in a simple and practical way. If you’ve heard terms like LLM, Large Language Models, ChatGPT, Generative AI, Transformers, Tokens, Embeddings, RAG, Fine-Tuning, Prompt Engineering, and AI Agents, this video will help you understand how they all fit together. Large Language Models are the foundation of modern Artificial Intelligence and power tools such as ChatGPT, Claude, Gemini, Copilot, Perplexity, and many enterprise AI applications. What You’ll Learn ✅ What is a Large Language Model (LLM)? ✅ How Large Language Models Work ✅ How ChatGPT Works ✅ What Are Tokens in LLMs? ✅ Transformer Architecture Explained ✅ Neural Networks Explained ✅ How LLMs Are Trained ✅ What Are Embeddings? ✅ Fine-Tuning vs Prompt Engineering ✅ What is Retrieval-Augmented Generation (RAG)? ✅ AI Agents Explained ✅ Real-World Applications of Large Language Models Large Language Models Explained A Large Language Model (LLM) is an Artificial Intelligence model trained on massive amounts of text data to understand and generate human language. Large Language Models use Machine Learning, Deep Learning, Transformer Architecture, and Neural Networks to predict the next word in a sequence and generate intelligent responses. Modern LLMs power: * ChatGPT * Claude * Gemini * Microsoft Copilot * Enterprise AI Assistants * AI Agents * Customer Support Bots * AI Search Engines * Business Automation Systems Key Concepts Covered * Large Language Models (LLMs) * Artificial Intelligence * Machine Learning * Deep Learning * Transformer Models * Neural Networks * Tokens * Embeddings * Context Windows * Prompt Engineering * Fine-Tuning * RAG Architecture * AI Agents * Generative AI * Natural Language Processing (NLP) Real-World Applications of LLMs Learn how Large Language Models are transforming: ✔ Business Operations ✔ Supply Chain Management ✔ Customer Support ✔ Content Creation ✔ Research and Analysis ✔ Marketing and Sales ✔ Software Development ✔ Knowledge Management ✔ Enterprise Productivity Who Should Watch? * AI Beginners * Working Professionals * Managers * Business Leaders * Students * Data Analysts * Supply Chain Professionals * Operations Managers * Entrepreneurs * Technology Enthusiasts
AI Security Explained for Developers | Prompt Injection, Jailbreaking, AI Data Leakage & Guardrails
AI Security Explained for Developers | Prompt Injection, Jailbreaking, AI Data Leakage & Guardrails 🔐 AI Security is becoming one of the most important topics for developers building AI applications, LLM-based systems, and AI agents. In this video, we explore how attackers manipulate AI models using Prompt Injection, Jailbreaking techniques, and how sensitive information can leak through AI systems. This episode from **Prompt Engineering For Developers** explains the security challenges of Large Language Models (LLMs), why traditional security approaches are different for AI, how System Prompts and User Prompts work, and how developers can protect AI applications using Guardrails. You will learn: ✅ Why AI Security is different from traditional application security ✅ System Prompt vs User Prompt explained ✅ What is Prompt Injection and how attacks work ✅ What is AI Jailbreaking and why it is dangerous ✅ How AI Data Leakage happens ✅ How Guardrails help secure AI applications ✅ Best practices for building safer AI systems Whether you are an AI developer, software engineer, prompt engineer, or someone exploring Generative AI security, this video will help you understand the fundamentals of securing LLM applications. 🚀 Topics Covered: 00:00 – Introduction 00:45 – Why AI Security is Different? 03:52 – System Prompt vs User Prompt 06:34 – Prompt Injection 10:45 – Jailbreaking 14:35 – AI Data Leakage 18:54 – Guardrails 23:00 – Next Steps ━━━━━━━━━━━━━━━━━━ 📌 Channel Information Channel: My Digital Diaries (English) @mydigitaldiariesenglish Series: Prompt Engineering For Developers ▶ Episode 01 — Introduction to Prompt Engineering ▶ Episode 02 — How LLMs Work ▶ Episode 03 — Anatomy of a Good Prompt ▶ Episode 04 — Basic Prompting Techniques ▶ Episode 05 — Advanced Prompting Techniques ▶ Episode 06 — Best AI Prompts for Coding, Debugging, Testing ▶ Episode 07 — Why Your AI Gives Messy Answers (And How to Fix It) ▶ Episode 08 — Prompt Chaining Explained ▶ Episode 09 — AI Hallucination ▶ Episode 10 — RAG (Retrieval-Augmented Generation) ▶ Episode 11 — Context Engineering & Memory ▶ Episode 12 — AI Safety, Prompt Injection & Security (You are here! 📍) 📺 Playlist: https://www.youtube.com/playlist?list=PLt519PJr4jF9iDVju8UWE9LVtUqUFCR4f Join this channel to get access to perks: https://www.youtube.com/channel/UCCTAmLlY-Fns7F16cOuVI7Q/join 📸 Instagram: instagram.com/mydigitaldiaries_new ━━━━━━━━━━━━━━━━━━ 🔍 Video is for you if you are searching: AI security explained, AI security for developers, prompt injection explained, prompt injection attack, AI jailbreak explained, LLM security, large language model security, AI data leakage, generative AI security, ChatGPT security, system prompt vs user prompt, prompt engineering security, AI guardrails, LLM guardrails, secure AI applications, responsible AI, AI safety, developer guide to AI security, protecting AI applications 🎯 This Video is For: • AI Developers • Software Engineers • Machine Learning Engineers • Prompt Engineers • Generative AI Enthusiasts • Developers building LLM applications • Anyone interested in AI Security and Responsible AI #aisecurity #promptengineering #mydigitaldiaries #generativeai #llmsecurity
✅ How Transformers Work - Attention Explained Step by Step | Chapter 06
How do transformers actually work inside an LLM? This video breaks down the full transformer architecture - attention, encoder vs decoder, and next-token prediction - in plain English, no scary math required. Transformers are the secret sauce behind GPT, Claude, and every frontier model. By the end of this video you'll be able to look at the "Attention Is All You Need" diagram and understand exactly what every block does and why it's there. ===== In this video, you will learn ===== • The one big idea behind attention (the "I left my phone on the bank" example) • Encoder vs decoder - and why GPT and Claude use only the decoder • How multi-head attention splits 768 dimensions into 12 heads • Query, Key and Value explained with a networking + Google search analogy • What the feed forward layer, residual connections and layer norm really do • How the output head turns a vector into the next token (logits + softmax) • What causal masking, the generation loop, KV cache and TTFT mean This is Part 06 of the GenAI Fundamentals series - for data engineers, developers, and anyone learning how AI language models actually work. Watch the tokenization + vector embeddings video first if you haven't already. ===== Chapters ===== 00:00 What is a Transformer? (Attention Is All You Need) 02:07 Recap - Tokens, Embeddings and Dimensions 03:06 Why Transformers are Math Machines (Matrix Multiplication) 04:37 The One Big Idea Behind Attention 07:30 Encoder vs Decoder - What's the Difference? 10:57 Why GPT and Claude Use Only the Decoder 12:40 The 3 Families of Models (BERT, GPT, Transformer) 13:25 The Big Picture - Embedding, Blocks, Output Head 16:12 Inside a Single Transformer Block 18:53 What is Layer Normalization? 20:11 How Attention Works? 23:21 What is Multi-Head Attention? 26:02 Query, Key and Value Explained 28:44 The Attention Math - Scores and Softmax 34:30 What is the Feed Forward Layer? 38:36 The Output Head - From Vector to Next Token 39:04 What is Causal Masking? 43:36 The Generation Loop 44:13 What is KV Cache and TTFT? 45:55 Reading the "Attention Is All You Need" Diagram 48:00 Recap and What's Next (Prompt Engineering) Tokenization and Word Embedding Video - https://youtu.be/JyaAmvsel9w ===== Other Playlists ===== Checkout all other playlists on Data Engineering 👇🏻 https://www.youtube.com/@easewithdata/playlists ===== GitHub Repo ===== https://github.com/subhamkharwal https://github.com/subhamkharwal/genai-for-data-engineers ===== Connect with ME ===== LinkedIn - https://www.linkedin.com/in/subhamkharwal Medium - https://subhamkharwal.medium.com ===== References ===== Jay Alammar - https://jalammar.github.io/illustrated-transformer/ 3Blue1Brown - https://www.3blue1brown.com/lessons/attention/ ===== Hashtags ===== #Transformers #AttentionIsAllYouNeed #LLM #GenerativeAI #genai #dataengineering #neuralnetworks #machinelearning
AI Family Tree Explained: Machine Learning, LLMs & AI Agents
AI Family Tree Explained: Machine Learning, LLMs & AI Agents Artificial Intelligence is evolving rapidly, but understanding how different AI technologies connect can be confusing. In this video, we break down the AI Family Tree and show how Machine Learning, Deep Learning, Neural Networks, Large Language Models (LLMs), Generative AI, and AI Agents are related. Whether you're a beginner, student, developer, business owner, or AI enthusiast, this guide will help you understand the complete AI ecosystem in a simple and visual way. 📌 In This Video: ✅ What Artificial Intelligence (AI) really is ✅ Machine Learning vs Deep Learning ✅ How Neural Networks work ✅ Understanding Large Language Models (LLMs) ✅ Generative AI and AI Agents explained ✅ The relationship between modern AI technologies ✅ Future trends in Artificial Intelligence This video is perfect for anyone interested in AI, Machine Learning, ChatGPT, Claude AI, Generative AI, AI Agents, Data Science, and emerging technology trends. Link to Artifact: https://claude.ai/public/artifacts/64a6f673-a4e2-4f9b-90d5-b7c7984646ef 🔔 Subscribe for more AI tutorials, technology insights, and practical guides. #AI #ArtificialIntelligence #MachineLearning #DeepLearning #LLM #AIAgents #GenerativeAI #ChatGPT #AITutorial #Technology
Understanding Large Language Models (LLM) | Transformer Architecture, AI Concepts & Future Explained
Discover the complete world of Large Language Models (LLMs) in this detailed educational video designed for students, researchers, AI enthusiasts, educators, developers, and technology learners. In this in-depth session, we explore the latest concepts behind modern Artificial Intelligence systems including Transformer Architecture, Self-Attention Mechanisms, Tokenization, Embeddings, Neural Networks, Context Windows, Retrieval-Augmented Generation (RAG), AI Agents, Multimodal AI, and the future of Generative AI technologies. This educational video explains how modern AI systems process and understand human language using billions of parameters and large-scale datasets. Whether you are beginning your AI journey or already exploring Machine Learning and Natural Language Processing, this video provides a structured and easy-to-understand explanation of the most important concepts behind modern LLMs. The video also covers the evolution from traditional NLP systems to advanced Transformer-based architectures that power today’s AI assistants, intelligent chatbots, research systems, coding assistants, and enterprise AI applications. 📘 Topics Covered in This Video What are Large Language Models (LLMs)? Evolution of NLP and AI Language Systems Transformer Architecture Explained Self-Attention Mechanism Tokens and Tokenization Word Embeddings and Vector Representations Parameters and Neural Networks Training and Fine-Tuning of LLMs Context Windows and Long-Context AI Encoder vs Decoder Models Retrieval-Augmented Generation (RAG) Hallucinations and Limitations of AI AI Safety and Alignment Multimodal AI Systems AI Agents and Autonomous Workflows Latest Trends in Generative AI Real-World Applications of LLMs 🎯 Who Should Watch This Video? This video is highly useful for: Artificial Intelligence Students Machine Learning Enthusiasts NLP Researchers Engineering Students Data Science Learners AI Developers Educators and Teachers Research Scholars Technology Professionals Anyone curious about modern AI systems 🚀 Why This Video Matters Large Language Models are rapidly transforming industries including: Education Healthcare Cybersecurity Software Engineering Scientific Research Business Automation Digital Content Creation Understanding how LLMs work is becoming an essential skill in the modern AI-driven world. This video aims to simplify advanced AI concepts into a structured educational format suitable for learning, teaching, research, and knowledge-building purposes. 📌 Educational Disclaimer This video is created strictly for educational, learning, research, awareness, and knowledge-building purposes only. Some portions of this content are AI-generated and may contain inaccuracies, omissions, outdated information, or unintended errors. Viewers are strongly encouraged to independently verify facts, technical details, research findings, and practical implementations from official and trusted sources before applying them in academic, professional, technical, legal, medical, or commercial environments. This content does not promote misuse of AI technologies and is intended solely for responsible educational understanding. 🔔 Support the Channel If you found this educational AI content useful: Like the video Share with learners and researchers Subscribe for more AI, Machine Learning, NLP, and Technology educational content Enable notifications for future updates #LLM #ArtificialIntelligence #GenerativeAI #MachineLearning #NLP #Transformers #LargeLanguageModels #AI #DeepLearning #NeuralNetworks #AIExplained #DataScience #AI2026 #Technology #EducationalVideo #AIResearch #NotebookLM #FutureOfAI #SelfAttention #RAG Large Language Models, LLM tutorial, What are LLMs, Transformer Architecture, Generative AI, Artificial Intelligence, NLP tutorial, Self Attention Mechanism, AI explained, Machine Learning tutorial, Deep Learning, Neural Networks, AI Agents, Multimodal AI, Retrieval Augmented Generation, RAG systems, Tokenization, Embeddings, Context Window, AI education, NotebookLM content, AI concepts explained, latest AI trends 2026, educational AI video, language models tutorial, ChatGPT concepts, Transformer neural network, AI learning, AI research, Future of AI, AI for students, AI technology explained, Generative AI tutorial, modern AI systems, Large Language Model architecture, NLP concepts, AI knowledge video, educational technology content
LLMs Explained in 20 Minutes | The Transformer Behind ChatGPT, Gemini & Claude
🚀 LLMs Explained in 10 Minutes | The Transformer Behind ChatGPT, Gemini & Claude Ever wondered how ChatGPT, Gemini, Claude, and other AI assistants actually work? In this video, we'll break down Large Language Models (LLMs) in the simplest way possible. You'll learn how AI evolved from traditional neural networks to the revolutionary Transformer Architecture, the breakthrough that powers modern AI. We'll also explore the Attention Mechanism, the core idea that allows LLMs to understand context, focus on important words, and generate human-like responses. What You'll Learn ✅ What is an LLM (Large Language Model)? ✅ Why RNNs struggled with long context ✅ How Transformer Architecture works ✅ What is the Attention Mechanism? ✅ Why Transformers changed AI forever ✅ How ChatGPT, Gemini, and Claude generate responses ✅ The foundation behind modern Generative AI Whether you're a student, developer, cloud engineer, AI enthusiast, or preparing for AI interviews, this video will help you understand the fundamentals of LLMs without complicated math. 🔥 If you enjoy AI, Generative AI, Agentic AI, Google Cloud, Gemini, MCP, and modern AI architectures, make sure to subscribe for more content. #LLM #ChatGPT #Gemini #Claude #Transformer #GenerativeAI #ArtificialIntelligence #MachineLearning #AIExplained #TechTrapture Playlists Google Agent Development Kit (ADK) https://www.youtube.com/playlist?list=PLLrA_pU9-Gz2HwepRUVpq1TEPuYWo_fSi Learn Airflow https://www.youtube.com/playlist?list=PLLrA_pU9-Gz3i8qw6yakrfJzx75W_vVaH Learn Google Cloud in 2025 https://youtube.com/playlist?list=PLLrA_pU9-Gz2OnBoICkewd9-Fc9Mi0nm7&si=8kkB3ct5wDHCMkoi Data Engineering Hands-on Projects https://www.youtube.com/playlist?list=PLLrA_pU9-Gz2DaQDcY5g9aYczmipBQ_Ek Looking to get in touch? Drop me a line at vishal.bulbule@techtrapture.com Linkedin https://www.linkedin.com/in/vishal-bulbule/ Medium Blog https://medium.com/@VishalBulbule Github Source Code https://github.com/vishal-bulbule