Videos de artificial intelligence
Videos etiquetados con "artificial intelligence"
artificial intelligence 41 videos
The Math Behind Deepfakes (GANs Explained)
Discover the math behind deepfakes and how Generative Adversarial Networks (GANs) changed AI forever. Before 2014, teaching a machine to create highly realistic data from scratch involved incredibly slow and complex probabilistic calculations. That all changed when Ian Goodfellow and his team introduced a completely new paradigm. By pitting two neural networks against each other in a continuous Minimax game, they bypassed the heavy calculus and unlocked the modern era of generative AI. In this video, we break down the exact mechanics of GANs. You will learn how the Generator acts as a counterfeiter trying to create perfect fakes, while the Discriminator acts as the police trying to catch them. We also dive into the training loop, the significance of the Jensen-Shannon divergence, and the mathematical proof that guarantees these models can perfectly mimic reality. 00:00 - The dense math of early generative models 00:58 - Re-framing generation as an adversarial game 02:27 - The Counterfeiter and the Police analogy 03:11 - The Minimax game and training loop steps 04:24 - Visualizing the push and pull of data distribution 05:58 - Proving the perfect fake mathematically 06:40 - The Jensen-Shannon divergence explained 07:31 - Why GANs matter for modern AI and deepfakes 🔗 Stay Connected 👉 Subscribe on YouTube: https://www.youtube.com/@insightforge_9 👉 Read the Blog (AI, Chatbots & Automation): https://insightforge-ai.blogspot.com/ 👉 Connect on LinkedIn: https://www.linkedin.com/in/mohit-rathod-7991241b5/ 👉 Join the Newsletter: https://www.linkedin.com/newsletters/7330620395449937920/ 👉 Follow on Instagram: https://www.instagram.com/insightforge.ai/ #GenerativeAI #MachineLearning #Deepfakes
No AI Job Apocalypse? New Study Says Automation Hasn't Replaced Workers At Scale Yet | N18G
A new study suggests there is currently no clear evidence that artificial intelligence has triggered widespread job losses, despite growing concerns about automation replacing human workers. Researchers say AI's impact on employment is more nuanced, with many jobs evolving rather than disappearing entirely. As businesses increasingly adopt AI technologies, experts believe the future of work will involve changing job roles, new skill requirements, and human-AI collaboration instead of a large-scale employment crisis. Watch the latest insights into AI, automation, the job market, and the future of work. #AI #ArtificialIntelligence #Automation #Jobs #FutureOfWork #TechNews #AIJobs #Employment #BreakingNews #Technology #JobMarket #LatestNews #Innovation #Workforce #newsupdate n18oc_world CNN-News18 is your trusted source for breaking news, updates, and in-depth analysis from around the world. CNN-News18 is dedicated to bringing you the latest news, trends, and insights, helping you stay informed and up-to-date. Subscribe Now and join our community of informed and engaged viewers. 24X7 LIVE TV: https://www.youtube.com/watch?v=rfDx1HMvXbQ Follow us on Google: news18.co/cn18g Follow CNN News18 on X: https://x.com/CNNnews18 Follow CNN News18 on Instagram: https://www.instagram.com/cnnnews18/ Follow CNN News18 on Facebook: facebook.com/cnnnews18 #GetCloserToTheNews with latest headlines on politics, sports and entertainment on news18.com News18 Mobile App - https://onelink.to/desc-youtube
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
The Simple Truth Behind How AI Works : How Does AI Work? | Complete Beginner Friendly Breakdown
The Simple Truth Behind How AI Works : How Does AI Work? | Complete Beginner Friendly Breakdown Curious about AI but overwhelmed by all the hype? In this video, I break down exactly how artificial intelligence actually works — using simple, everyday language. You'll learn what AI really is, how it learns, why it can chat, create images, and drive cars, all without any confusing tech jargon. Perfect for complete beginners! ai explained, how ai works, artificial intelligence, ai for beginners, what is ai, machine learning explained, how does ai work, ai simple explanation, chatgpt explained, artificial intelligence tutorial, ai technology, neural networks simple, deep learning for beginners, ai 2026, how ai learns, ai demystified
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
What Is a Large Language Model? (LLMs Explained From Zero)
Try it yourself — the full written explainer and an interactive next-word predictor are here: https://unrote.com/ai/what-is-an-llm/ A large language model sounds mysterious, but underneath it's one simple idea: a giant math function that, given some text, predicts the most likely next chunk of text — then feeds its own guess back in and does it again. That loop, repeated, is the whole engine. This is a build-from-zero explainer. No jargon assumed. We start with the autocomplete on your phone, watch a model generate a sentence one word at a time with real probabilities, and end up understanding why it can sound brilliant and still be confidently wrong. What we cover: - Why an LLM is really just autocomplete, scaled up enormously - Predict, append, repeat — how it writes one token at a time - Why it works in tokens (chunks), not whole words - Where the skill comes from: training on a huge pile of text - Why "Large" matters — billions of parameters - Why it doesn't actually "know" anything, and why that causes hallucinations - Why doing one simple thing well, at scale, ends up looking like intelligence Chapters: 0:00 What a large language model is 0:26 The whole thing in one sentence 0:44 Read the name backwards: L, L, M 1:03 It's autocomplete you already use 1:42 Watch it predict, word by word 2:36 It works in tokens, not words 2:59 Where the skill comes from: training 3:45 Why "Large" matters 4:10 It doesn't know — it predicts 4:33 So why does it feel intelligent? 4:58 Where this goes next 5:21 Recap This is the first video in an AI series on Unrote — modern AI explained from zero, one idea per page. Up next: What Are Tokens? Unrote. Understand it, don't memorize it.
Math for Machine Learning 11: Vector Calculus Explained | Gradients & Optimization #mathforml
Mathematics is the backbone of Machine Learning, Artificial Intelligence, Data Science, Deep Learning, Computer Vision, Robotics, and modern computational technologies. Among the most important mathematical concepts used in AI and Machine Learning is Vector Calculus, which forms the foundation of optimization algorithms, gradient-based learning, neural networks, and advanced machine learning models. In this video, we provide a detailed explanation of Vector Calculus for Machine Learning as part of the Math for ML series. This session focuses on gradients, partial derivatives, directional derivatives, Jacobians, Hessians, vector fields, optimization techniques, and their practical applications in Artificial Intelligence and Machine Learning. Whether you are a beginner in Machine Learning, a Data Science student, an Artificial Intelligence enthusiast, a Computer Science learner, or a professional seeking a stronger mathematical foundation, this lecture will help you understand one of the most powerful tools used in modern AI systems. 📚 Topics Covered in This Video ✅ Vector Calculus Fundamentals ✅ Gradients and Gradient Vectors ✅ Partial Derivatives ✅ Directional Derivatives ✅ Jacobian Matrix ✅ Hessian Matrix ✅ Vector Fields ✅ Scalar Fields ✅ Optimization Techniques ✅ Machine Learning Mathematics ✅ AI Mathematical Foundations ✅ Deep Learning Mathematics ✅ Neural Network Optimization ✅ Data Science Mathematics ✅ Mathematical Modeling 📖 Why Vector Calculus is Important in Machine Learning Vector Calculus helps us: • Understand optimization problems • Train machine learning models efficiently • Improve neural network performance • Analyze multidimensional functions • Perform gradient-based learning • Optimize loss functions • Build intelligent AI systems • Solve complex computational problems Almost every modern Machine Learning algorithm relies on concepts from Vector Calculus. 🎯 Applications of Vector Calculus in AI & Machine Learning Vector Calculus is widely used in: ✔ Machine Learning Algorithms ✔ Artificial Intelligence Systems ✔ Deep Learning Models ✔ Neural Networks ✔ Computer Vision ✔ Natural Language Processing ✔ Robotics ✔ Recommendation Systems ✔ Predictive Analytics ✔ Reinforcement Learning ✔ Scientific Computing ✔ Financial Modeling A strong understanding of Vector Calculus enables students to understand advanced Machine Learning architectures and optimization techniques. 📚 Important Concepts Potentially Covered ✔ Multivariable Functions ✔ Partial Differentiation ✔ Gradient Vector ✔ Directional Derivatives ✔ Jacobian Matrix ✔ Hessian Matrix ✔ Optimization Theory ✔ Neural Network Learning ✔ Loss Functions ✔ Vector Fields ✔ Scalar Fields ✔ Advanced Mathematical Modeling 🎓 Useful For • Machine Learning Students • Data Science Aspirants • Artificial Intelligence Learners • Computer Science Students • Research Scholars • Software Developers • AI Professionals 📚 Relevant Courses and Examinations This lecture is useful for: • Machine Learning Courses • Artificial Intelligence Programs • Data Science Courses • Statistics Programs • Advanced Mathematics Courses • Research Methodology Programs • AI Certification Courses • Professional Analytics Training 📝 Learning Strategy To master Vector Calculus for Machine Learning: 📌 Understand multivariable functions 📌 Practice derivatives regularly 📌 Learn gradient concepts thoroughly 📌 Study optimization methods carefully 📌 Focus on conceptual understanding 📌 Connect mathematics with AI applications 📌 Practice consistently 📚 Learning Outcomes After watching this lecture, you will be able to: ✔ Understand Vector Calculus concepts ✔ Compute gradients confidently ✔ Apply derivatives in Machine Learning ✔ Improve Machine Learning understanding ✔ Build a strong AI foundation ✔ Understand neural network optimization ✔ Prepare for advanced AI topics This lecture is part of a comprehensive Math for Machine Learning series designed to help students build strong mathematical foundations for Artificial Intelligence, Machine Learning, Data Science, Deep Learning, and modern computational fields. If you found this lecture helpful, please Like, Share, and Subscribe for more Machine Learning Mathematics lectures, AI tutorials, Data Science concepts, Vector Calculus discussions, and advanced educational content. 📞 Academic Guidance & Machine Learning Preparation Support Sourav Sir's Classes Helpline: 9836870415 Website: www.souravsirclasses.com #MachineLearning #MathForML #VectorCalculus #ArtificialIntelligence #DataScience #DeepLearning #GradientDescent #NeuralNetworks #AI #ML #ComputerScience #Mathematics #Statistics #Optimization #Jacobians #Hessians #DataAnalytics #MachineLearningCourse #AIEngineering #ComputerVision #NLP #PredictiveAnalytics #EngineeringMathematics #MathTutorial #MLTutorial #AICourse #MathematicalModeling #ResearchMethods #TechnologyEducation #Analytics
5 Next Big Careers No One Is Talking About Yet | SUNAND SHARMA @CareersTalk
There’s a lot of fear around Artificial Intelligence (AI) replacing jobs, but the reality is more nuanced. Instead of simply taking over careers, AI is reshaping the job market and making certain roles more valuable than ever. In this video, we break down 5 future-proof career paths that will actually survive AI in 2026 and beyond—where AI is not your replacement, but your most powerful tool. You’ll learn: Which jobs are most resistant to AI automation Why AI is increasing demand for certain careers Real-world salary potential and future scope How tools like AI agents, generative AI, and automation platforms (like n8n) are changing work Skills you need to stay relevant in the AI-driven job market We also explore the future of work in 2030, including how AI automation, AI agents, and tools like Claude AI and generative AI are reshaping industries across the world, especially in India and global tech markets. If you’re planning your career, switching fields, or just trying to understand where AI is heading, this video will give you a clear roadmap AI jobs, future of AI, AI careers, AI automation jobs, AI proof careers, AI proof skills, generative AI, AI agents, future of work 2030, artificial intelligence future scope in India, how to survive AI, AI job trends, n8n AI agent, n8n web scraping, Claude AI, AI tools, tech careers 2026 #AI #FutureOfWork #AICareers #AIJobs #ArtificialIntelligence #Automation #CareerAdvice #GenerativeAI #AITools #FutureJobs
AI vs Machine Learning vs Deep Learning: What’s the Difference?
AI vs Machine Learning vs Deep Learning: What’s the Difference? Artificial Intelligence, Machine Learning, and Deep Learning are among the most talked-about technologies today, but many people use these terms interchangeably. The reality is that Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are related but fundamentally different concepts. In this video, you’ll learn the difference between AI vs Machine Learning vs Deep Learning, how they work, where they overlap, and why understanding these technologies is essential for professionals, students, business leaders, and anyone interested in the future of technology. We’ll break down complex concepts into simple language and explore real-world examples such as ChatGPT, self-driving cars, recommendation systems, fraud detection, predictive analytics, computer vision, and generative AI. In This Video ✅ What is Artificial Intelligence (AI)? ✅ What is Machine Learning (ML)? ✅ What is Deep Learning (DL)? ✅ AI vs Machine Learning vs Deep Learning Explained ✅ Key Differences Between AI, ML, and DL ✅ Real-World Applications of AI, ML, and DL ✅ How ChatGPT Uses AI and Deep Learning ✅ Machine Learning Examples in Business ✅ Deep Learning Examples in Everyday Life ✅ The Future of Artificial Intelligence AI vs ML vs DL Explained Artificial Intelligence is the broader concept of machines performing tasks that normally require human intelligence. Machine Learning is a subset of Artificial Intelligence that enables systems to learn from data without being explicitly programmed. Deep Learning is a specialized subset of Machine Learning that uses neural networks to solve complex problems such as image recognition, speech recognition, natural language processing, and generative AI. Understanding the relationship between Artificial Intelligence, Machine Learning, and Deep Learning is critical for anyone looking to build future-ready skills in the AI era. Real-World Examples Covered * ChatGPT and Generative AI * Recommendation Engines * Self-Driving Cars * Voice Assistants * Fraud Detection Systems * Predictive Analytics * Image Recognition * Facial Recognition * Supply Chain Forecasting * Business Intelligence Systems Who Should Watch? * Working Professionals * Business Leaders * Managers * Students * MBA Aspirants * Data Analysts * Supply Chain Professionals * Operations Managers * Technology Enthusiasts * Anyone Interested in Artificial Intelligence Related Topics * Artificial Intelligence Explained * Machine Learning Explained * Deep Learning Explained * Generative AI * Large Language Models (LLMs) * ChatGPT Explained * Neural Networks * Data Science * AI in Business * AI for Professionals * AI in Supply Chain * Future of Work * AI Career Skills Hashtags #ArtificialIntelligence #MachineLearning #DeepLearning #AI #ML #DL #GenerativeAI #ChatGPT #AIExplained #MachineLearningExplained #DeepLearningExplained #Upstratica High-SEO Keywords AI vs Machine Learning vs Deep Learning, artificial intelligence vs machine learning, machine learning vs deep learning, AI vs ML vs DL, what is artificial intelligence, what is machine learning, what is deep learning, AI explained, machine learning explained, deep learning explained, artificial intelligence explained, neural networks, generative AI, ChatGPT explained, AI for professionals, machine learning for beginners, deep learning tutorial, AI applications, AI use cases, AI in business, AI in supply chain, future of AI, artificial intelligence tutorial ⸻ 🚀 Subscribe to Upstratica for practical insights on Artificial Intelligence, Supply Chain Management, Operations Excellence, Business Transformation, and the Future of Work. Suggested Chapters 00:00 Introduction 01:12 What is Artificial Intelligence (AI)? 03:40 What is Machine Learning (ML)? 06:25 What is Deep Learning (DL)? 09:15 AI vs Machine Learning vs Deep Learning 12:40 Real-World Examples 15:20 How ChatGPT Uses AI & Deep Learning 17:45 Future of AI 19:00 Key Takeaways Additional Search Queries artificial intelligence vs machine learning vs deep learning, difference between AI and machine learning, difference between machine learning and deep learning, AI vs ML explained, deep learning for beginners, machine learning for beginners, artificial intelligence for beginners, how ChatGPT works, neural networks explained, AI technology explained, AI concepts for professionals, generative AI explained, AI fundamentals, machine learning applications, deep learning applications This description is optimized around the exact-match keyword “AI vs Machine Learning vs Deep Learning” while also targeting related searches such as AI explained, Machine Learning explained, Deep Learning explained, ChatGPT explained, and Generative AI, which generally helps push VidIQ optimization into the higher range.
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
Will AI Take Your Job? Here's the Real Truth
Are you worried AI might take your job? Let’s uncover the real truth behind this emerging phenomenon! In this video, I break down how AI is reshaping the workforce and transforming career options in technology. Yes, some jobs are at risk, but here’s the exciting part: AI is creating a wave of new opportunities that combine human creativity with cutting-edge technology. From AI interpreters to augmented creatives, learn about five surprising careers born from this technological revolution. Here’s what you’ll discover: - The truth about which jobs are most vulnerable to AI-driven automation. - Exciting new roles like AI trainers, AI ethicists, and implementation specialists. - Practical steps to future-proof your career and thrive in the age of AI. - Why the future of work is about human-AI collaboration, not competition. The future isn’t about being replaced; it’s about becoming irreplaceable. Whether you’re curious about space travel, technological isolation, or digital innovation, this video will help you navigate the next chapter of work with confidence. 🌟 Don’t forget to like this video and subscribe for more insights into the future of work, technology trends, and career guidance. Let’s build the future together! 🌟 #ai #future #machinelearning #artificialintelligence #softwareengineering CHAPTERS: 00:00 - The AI Job Apocalypse 01:28 - Jobs AI is Replacing: Uncomfortable Truth 05:17 - From Replaced to Irreplaceable: The Pivot 07:34 - Hidden Job Market: 5 New Careers by AI 12:57 - Your Action Plan for the Future 16:42 - Conclusion: Embracing Change
¿La Mejor Mano Robótica del Mundo? Probando la OmniHand 2025 @AGILINK-ai
Hoy vamos a probar la increíble OmniHand 2025 de AGILINK, una de las manos robóticas más avanzadas que existen actualmente para investigación, robótica humanoide e inteligencia artificial. Recientemente fue presentada durante ICRA, uno de los eventos de robótica más importantes del mundo, y ahora tendremos la oportunidad de realizar el unboxing, analizar su construcción, conocer sus especificaciones y ponerla a prueba con diferentes ejercicios de agarre, precisión, sensibilidad y manipulación de objetos. 🤖 Características destacadas: • Tamaño similar a una mano humana real • 10 motores integrados • Hasta 16 grados de libertad • Más de 300 sensores táctiles distribuidos en dedos y palma • Fuerza de agarre de hasta 5 kg • Comunicación mediante USB, RS485 y CAN-FD • Diseñada para investigación, IA y robótica humanoide • Peso aproximado de 510 gramos • Alta precisión para manipulación avanzada ¿Será realmente una de las manos robóticas más sofisticadas del mercado? 📌 Más información sobre OmniHand: https://www.agilink-ai.com/ 🔥 Suscríbete para más contenido de robótica, inteligencia artificial, prótesis biónicas y tecnología futurista. #OmniHand #AGILINK #Robotica #Robotics #ArtificialIntelligence #ICRA #Ingenieria #BioMakersAI