Videos de Ciencia
Videos sobre avances científicos y descubrimientos.
Ciencia 255 videos
Who Decides What's True? | Tucker Carlson & Sam Altman
ChatGPT answers billions of questions every day. But who decides what answers are allowed? In this conversation, Sam Altman discusses the moral framework behind ChatGPT, how AI systems are trained, who influences their behavior, and the difficult decisions involved in building technology used by hundreds of millions of people. The discussion explores questions about truth, morality, free speech, censorship, privacy, AI influence, religion, and the future impact of artificial intelligence on society. Topics covered: • ChatGPT and moral decision-making • Who decides AI behavior • AI and free speech • Sam Altman on morality • Artificial intelligence and religion • AI influence on society • Privacy and surveillance • The future of AI systems • Unknown risks of artificial intelligence This video is intended for educational and commentary purposes. who decides AI morality, Sam Altman ChatGPT, AI ethics explained, ChatGPT moral framework, OpenAI decision making, AI censorship debate, artificial intelligence future, AI religion discussion, AI and society, ChatGPT bias explained, AI truth and morality, Sam Altman interview AI, OpenAI ethics, future of artificial intelligence, AI influence on society #SamAltman #ChatGPT #tuckercarlson
Why AI Suddenly Got So Smart
Description Before ChatGPT, before GPT-4, and before the AI boom, there was one breakthrough that changed everything. In 2012, a neural network called AlexNet achieved something nobody expected and completely transformed the future of artificial intelligence. This single breakthrough reignited AI research, sparked the deep learning revolution, and laid the foundation for the systems that power ChatGPT and modern AI today. In this video, we'll explore: • Why AI struggled for decades • What made AlexNet so different • How it shocked the tech world • Why 2012 became the turning point for AI • How AlexNet ultimately led to ChatGPT The story of modern AI starts here. If you enjoy AI, technology, and fascinating tech history, make sure to subscribe for more videos. #ArtificialIntelligence #AI #ChatGPT #AlexNet #DeepLearning #MachineLearning --- Hashtags #AI #ArtificialIntelligence #ChatGPT #AlexNet #DeepLearning #MachineLearning #NeuralNetworks #AITimeline #Technology #TechHistory #OpenAI #GPT4 #FutureTech #ComputerScience #Innovation --- Search Tags alexnet, alexnet explained, what happened in 2012 ai, ai breakthrough, chatgpt origin, history of ai, deep learning revolution, neural networks explained, artificial intelligence documentary, ai history, machine learning, chatgpt explained, openai, gpt, transformers, modern ai, technology documentary, ai evolution, deep learning explained, alexnet 2012, why 2012 changed ai forever, breakthrough that made chatgpt possible, computer science, future of ai, tech explained, ai revolution, neural network history, ai breakthrough 2012, chatgpt history, artificial intelligence history
Aprenda Visão Computacional: A Habilidade Mais Valiosa da IA
🚀 Aprenda Visão Computacional: A Habilidade Mais Valiosa da IA Você já imaginou ensinar um computador a enxergar, reconhecer pessoas, identificar objetos e tomar decisões automaticamente? Neste vídeo eu apresento o treinamento completo de Visão Computacional da Sara Educação e mostro por dentro da plataforma tudo o que você vai aprender para dominar uma das áreas que mais crescem no mundo da Inteligência Artificial. Você vai conhecer: ✅ Como funciona a plataforma de ensino ✅ Os módulos do treinamento ✅ As tecnologias utilizadas ✅ Projetos práticos desenvolvidos durante as aulas ✅ Reconhecimento facial ✅ Detecção de objetos ✅ Rastreamento de pessoas e veículos ✅ Processamento de imagens em tempo real ✅ Inteligência Artificial aplicada à visão computacional A Visão Computacional está presente em: 🚗 Carros autônomos 🏭 Indústria 4.0 📹 Sistemas de monitoramento inteligente 🤖 Robótica 🛒 Varejo inteligente 🏥 Área médica 📦 Logística automatizada Se você trabalha com eletrônica, programação, automação, robótica ou inteligência artificial, esta pode ser uma das habilidades mais valiosas para os próximos anos. 🔥 Conheça o treinamento completo de Visão Computacional da Sara Educação: ➡ https://saraeducacao.com.br 📲 Acompanhe mais conteúdos: Instagram: https://instagram.com/sara.educacao YouTube: https://youtube.com/@Sara.Educacao WhatsApp: (54) 99245-0330 E-mail: contato@saraeducacao.com.br 🔎 PERGUNTAS FREQUENTES (SEO) 🔹 O que é Visão Computacional? 🔹 Como aprender Visão Computacional do zero? 🔹 Como funciona o reconhecimento facial? 🔹 O que é OpenCV? 🔹 Como detectar objetos usando Inteligência Artificial? 🔹 Vale a pena estudar Visão Computacional em 2026? 🔹 Como criar sistemas que reconhecem pessoas? 🔹 Como funciona a IA que identifica imagens? 🔹 Qual a diferença entre IA e Visão Computacional? 🔹 Como trabalhar com Inteligência Artificial aplicada a imagens? 🔹 Como entrar no mercado de Visão Computacional? 🔹 Quanto ganha um profissional de Visão Computacional? 🔹 Como criar projetos de reconhecimento facial? 🔹 Como desenvolver sistemas inteligentes com câmeras? 🔹 Como funciona o curso de Visão Computacional da Sara Educação? #VisaoComputacional #InteligenciaArtificial #OpenCV #IA #MachineLearning #DeepLearning #Python #Robotica #Automacao #Eletronica #SaraEducacao #Tecnologia #Industria40 #ComputerVision #ArtificialIntelligence
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
Chinese Robots in Barcelona: Shanghai is leaving Tesla behind!
While the West is waiting for the next Tesla Optimus update and watching Boston Dynamics demos in labs, humanoids from China are already out on the streets of Europe. 🤖🇪🇺 In this video, we look at the reality behind the robotics race. AGIBOT, a company founded just a few years ago, managed to secure a massive share of the global humanoid market in 2025. Now, their machines are appearing in Europe—not just as exhibition concepts, but as working assets you can actually rent. What we analyze in this episode: The European Foothold: How AGIBOT rapidly established a physical presence in Germany and Spain in early 2026 while Western competitors focused on domestic markets. The Reality of Western Tech: Where do Tesla Optimus Gen 3, Boston Dynamics Atlas, and 1X NEO actually stand regarding mass production and European deliveries? The Business Formula: The background of co-founder Peng Zhihui, backing from major tech giants, and how a "data factory" model is scaling their AI. Hardware in Action: A look at the X2 model, its algorithmic decision-making, and its real-world viability for the service sector. The Challenges Ahead: Morgan Stanley’s warnings of an industry shakeout, short battery life, and how the upcoming EU AI Act might impact Chinese suppliers. Is the West genuinely playing catch-up, or is this early market penetration just a temporary lead? Let’s look at the numbers, the tech, and the strategy behind @AGIBOT Official. #AGIBOT #HumanoidRobots #Robotics #AI #TeslaOptimus #BostonDynamics #EmbodiedAI #TechIndustry #FutureOfWork 👉For business inquiries: info.prorobots@gmail.com ✅ Instagram: https://www.instagram.com/pro_robots While the U.S. awaits Tesla Optimus, the future of robotics is already present on Barcelona's waterfront with AGI Bot robots. These artificial intelligence-powered humanoid robot units are not just for show; they're actively being rented out for commercial purposes, demonstrating advanced automation technology. AGI Bot robots have already made Guinness World Records for their capabilities, including covering long distances and performing intricate dances. This marks a significant step in the practical application of industrial robots outside of traditional settings. 🤖 #Robotics #ArtificialIntelligence #HumanoidRobot #AutomationTechnology #IndustrialRobots
What Is AI? A Plain-English Introduction for Developers | Mastering AI & ML Course M1:E1
Detailed Description Artificial Intelligence is everywhere right now... but what does it actually mean? In this first episode of the Master AI & ML series, we strip away the buzzwords and explain AI in plain language for developers, technologists, creators, and curious learners. No PhD required. No math overload. Just a practical mental model that helps you understand what AI really is and why it matters. You’ll learn the fundamental difference between traditional programming and machine learning, how AI systems are trained, why modern AI feels so powerful, and where today’s tools actually fit on the spectrum between Narrow AI and AGI. This episode is designed to give you a rock-solid foundation before diving deeper into machine learning, deep learning, neural networks, and real-world AI engineering workflows. 🚀 In this episode: What AI actually is in plain English Rule-based software vs machine learning Why AI “learns” instead of following hard-coded rules Narrow AI vs AGI explained clearly How training and inference work Why 2012 changed everything in AI Real-world examples like spam filters and recommendation systems The biggest misconceptions developers have about AI Why this AI wave is genuinely different Whether you're a software engineer, product manager, founder, analyst, student, or just AI-curious, this series is built to help you understand the field from first principles and connect theory to real-world applications. 🧠 This is Episode 1 of the Master AI & ML series. 🎯 Coming Next: M1:E2 — AI vs. ML vs. Deep Learning We’ll break down the differences between these terms and explain why the distinctions actually matter when building products and systems. 👇 Drop a comment: What was the first AI system you remember using? Spam filters? Netflix recommendations? Siri? Something else entirely? 🔔 Subscribe for future episodes covering: Python for AI Machine Learning Foundations Neural Networks Deep Learning NLP & LLMs AI APIs and Product Integration AI Project Deployment Real-world AI Engineering CTA 👍 Like the video if it helped clarify AI without the hype 💬 Share your first memorable AI experience in the comments 🔔 Subscribe to follow the complete AI & ML learning journey 🚀 New episodes weekly as we build from fundamentals to production-ready AI systems Tags AI, Artificial Intelligence, What Is AI, AI Explained, Machine Learning, Deep Learning, AI for Developers, Intro to AI, Beginner AI Course, AI Tutorial, Artificial Intelligence Tutorial, AI Fundamentals, Neural Networks, AI Training, Narrow AI, AGI, AI Course, AI Engineering, AI Education, Learn AI, Generative AI, GPT, LLM, AI Concepts, AI Basics, Technology Explained, Python AI, Software Engineering, Data Science, AI and ML, AI Video Course, AI for Beginners, Developer Education, Future of AI, AI Systems Hashtags #AI #MachineLearning #DeepLearning #ArtificialIntelligence #AIForDevelopers #LearnAI #GenerativeAI #TechEducation #NeuralNetworks #DataScience
Master AI & Machine Learning — Course Overview | What You’ll Learn & Who It’s For
This is the course overview for Master AI & Machine Learning — a 35-episode, 6-module video series for developers, analysts, and technical professionals who want to go from AI-curious to AI-capable. No fluff. Real tools. Hands-on builds. This is the course overview for Master AI & Machine Learning — a 35-episode, 6-module video series for developers, analysts, and technical professionals who want to go from AI-curious to AI-capable. No fluff. Real tools. Hands-on builds. In this video you’ll learn: • Who this course is built for — and who it’s not • What you’ll be able to build and do by the end • How all 6 modules connect from foundations to strategy • A preview of the hands-on demos across the series ─── WHAT YOU’LL LEARN IN THIS SERIES ─── • Module 1 — AI Foundations: what AI is, how machines learn, myth vs. reality • Module 2 — Data Essentials: data types, cleaning, bias, building datasets • Module 3 — Core ML Algorithms: regression, classification, clustering, neural networks • Module 4 — AI Tools & Platforms: no-code AI, generative AI, workflow automation • Module 5 — Building with AI: prompt engineering, RAG, fine-tuning, chatbot builds • Module 6 — Ethics, Strategy & Future: governance, AI strategy, what’s coming next ─── WHO THIS IS FOR ─── • Developers who write code but haven’t worked with ML frameworks • Analysts and data-adjacent professionals adding AI to their toolkit • IT and tech professionals who want to demystify the AI black box Not the right fit: experienced ML engineers, or anyone looking for advanced math / architecture theory. That’s a different series. ─── ABOUT THIS SERIES ─── Master AI & Machine Learning is a Series of Thoughts production, presented by TechnovativeAI — an AI consulting firm helping businesses implement AI that actually works. This course is the distilled version of what we see working in the field. ─── LINKS & RESOURCES ─── TechnovativeAI: www.technovativeai.com Series of Thoughts: www.seriesofthoughts.com Full course playlist: AI course for beginners, machine learning tutorial, AI and ML explained, learn AI 2025, AI for developers, machine learning for beginners, deep learning basics, artificial intelligence course, AI tools tutorial, prompt engineering, RAG tutorial, AI implementation, TechnovativeAI, Series of Thoughts, AI training series, ML course YouTube, AI fundamentals, generative AI course, AI workflow automation, applied machine learning
Alinear y Memorizar: La Clave del Aprendizaje en Redes Neuronales Profundas
Este estudio explora una alternativa eficiente y biológicamente plausible a la retropropagación para entrenar redes neuronales profundas, conocida como Alineación de Retroalimentación Directa (DFA). A pesar de su éxito en modelos como los Transformers, la DFA falla notablemente en redes convolucionales, y este trabajo busca desentrañar el porqué de esta discrepancia. La investigación propone una nueva teoría que describe el aprendizaje con algoritmos de alineación de retroalimentación. Se demuestra que el aprendizaje se desarrolla en dos fases distintas: una fase inicial de 'alineación', donde el modelo ajusta sus pesos para alinear el gradiente aproximado con el gradiente real de la función de pérdida, seguida de una fase de 'memorización', en la que el modelo se centra en ajustar los datos para minimizar el error. Este proceso de 'alinear y luego memorizar' no solo explica por qué la DFA converge naturalmente a soluciones que maximizan la alineación del gradiente, sino que también ofrece una explicación para su fallo en las redes neuronales convolucionales. Los hallazgos, respaldados por experimentos numéricos, muestran cómo este mecanismo opera secuencialmente desde las capas inferiores hasta las superiores de la red, abriendo nuevas vías para entender y mejorar los algoritmos de aprendizaje profundo. Link al paper: https://arxiv.org/pdf/2011.12428 Autores del estudio: Maria Refinetti, Stéphane d'Ascoli, Ruben Ohana, Sebastian Goldt Apoyanos en https://www.patreon.com/audioarxiv Unete en https://discord.gg/vKRmFhg4YQ #Ciencia de la computación #InteligenciaArtificial #MachineLearning #RedesNeuronales #DeepLearning #FeedbackAlignment
¿Cómo Funciona ChatGPT? La Explicación Más Clara de los LLM, Transformers y Embeddings
¿Qué es un LLM? ¿Cómo funciona ChatGPT? ¿Qué son los Transformers, los Embeddings y el mecanismo de atención? En este vídeo explico de forma sencilla y visual cómo funciona la inteligencia artificial generativa detrás de ChatGPT, Claude, Gemini, Grok, DeepSeek y otros modelos de lenguaje modernos. Aprenderás: ✅ Qué es un LLM (Large Language Model) ✅ Cómo aprende un modelo de IA ✅ Qué diferencia a ChatGPT, Gemini, Claude o DeepSeek ✅ Qué son los embeddings o representaciones vectoriales ✅ Cómo funciona el mecanismo de atención (Attention) ✅ Qué son los Transformers ✅ Cómo se procesa una pregunta desde que la escribes hasta que recibes una respuesta ✅ Por qué los LLM no memorizan respuestas, sino que predicen la siguiente palabra Este vídeo está pensado para principiantes, estudiantes, profesionales y cualquier persona que quiera entender cómo funciona realmente la inteligencia artificial sin necesidad de conocimientos técnicos previos. Capítulos: 00:00 Introducción 00:45 ¿Qué es un LLM? 03:15 Qué hace diferente a un modelo de IA 06:20 Capacidades de los LLM 07:45 Qué son los Embeddings 10:30 El mecanismo de Atención 13:20 Cómo funciona un LLM paso a paso 17:00 Conclusión Si te interesa la Inteligencia Artificial, los LLM, ChatGPT, los agentes de IA, RAG, automatización, Machine Learning y el futuro de la tecnología, suscríbete al canal. #ChatGPT #InteligenciaArtificial #LLM #Transformers #Embeddings #IA #MachineLearning #DeepLearning #Gemini #Claude #DeepSeek #GenerativeAI #AI