Videos de Educación
Videos educativos y de formación.
Educación 184 videos
How AI Steals? Borrow? Creates? Images From Text
Ever wondered how typed words instantly turn into stunning AI images? 🤖✨ In this video, we break down the mind-blowing science behind text-to-image AI (like Midjourney, DALL-E, and Stable Diffusion) in simple terms anyone can understand! From decoding your text prompts to understanding how "Diffusion Models" actually paint pixels out of random static noise, we pull back the curtain on how artificial intelligence "thinks" in pictures. No coding experience required! If this video helped you understand AI a bit better, smash that LIKE button and SUBSCRIBE for more simple tech breakdowns! 🔔What’s the craziest prompt you’ve ever given an AI? Drop it in the comments below! 👇
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
How AI Turns Random Noise Into Stunning Images (Diffusion Explained)
Ever wondered how AI image generators like Midjourney, DALL·E, and Stable Diffusion create stunning images from just a text prompt? In this video, you'll learn how diffusion models work in a simple, beginner-friendly way. We'll break down the process step by step, from random noise to a fully detailed AI-generated image. You'll learn: What diffusion models are Why AI starts with random noise How text prompts guide image generation Why AI isn't simply copying images How modern AI image generators actually work Whether you're curious about artificial intelligence, machine learning, or AI art, this video will help you understand one of the most important technologies behind today's AI revolution. 👍 If you enjoyed this explanation, consider subscribing for more AI concepts explained in just 5 minutes. #AI #ArtificialIntelligence #StableDiffusion #Midjourney #Dalle #MachineLearning #AITools #GenerativeAI #Tech #Explained
Como criar Avatar com Inteligência Artificial Grátis (TUTORIAL COMPLETO)
Aprenda a criar avatar com ia da maneira correta. Links: https://chatgpt.com/ https://static.wixstatic.com/media/cd4d4a_36b078921b2845ce8af6de1d1e812ab1~mv2.png/v1/fill/w_980,h_1123,al_c,q_90,usm_0.66_1.00_0.01,enc_auto/cd4d4a_36b078921b2845ce8af6de1d1e812ab1~mv2.png https://www.reddit.com/media?url=https%3A%2F%2Fpreview.redd.it%2Fcartoon-network-studios-was-founded-29-years-ago-today-v0-6oxvi1p92nvb1.png%3Fauto%3Dwebp%26s%3D6a194db7c56c8165669232264e594fdab087b2df 👉Meu curso completo sobre Inteligências Artificiais com foco em renda extra e viver de internet: https://pay.kiwify.com.br/OUx0Hgb ✅Playlist de cursos gratuitos: https://youtube.com/playlist?list=PLNQBpbIienGEf4oI5z3wFOd_qexy0UrUe&si=oAqDO7cqeYPFB6X6 Editor: designersalvatore@gmail.com Neste canal, abordamos o que é a inteligência artificial e como ela está sendo aplicada em diferentes áreas, como tecnologia. Discutimos tipos de IA, como aprendizado profundo e racional, e os desafios e oportunidades que ela traz. O objetivo aqui é apresentar ferramentas de IA que facilitem o trabalho cotidiano das pessoas e como elas podem se preparar para o futuro com ela. Inscreva-se neste canal se quiser facilmente encontrar maneiras de trabalhar de forma independente, usando ferramentas como Midjourney, Stable diffusion, DALL·E 2, ChatGPT, etc. #midjourney #Stablediffusion #promptformidjourney #midjourneyai #chatgpt
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
Diffusion: AI Mental Model #7
======================================================= 📓 Free visual lecture notes for this episode: https://vizuaraai.github.io/great-mental-models-of-ai/lecture-07-reverse-the-corruption.html ======================================================= To create something, first learn how to destroy it. This is Lecture 7 of The Great Mental Models of Artificial Intelligence. In this episode, we explore Reverse the Corruption: the idea behind diffusion models, where generation is learned by slowly corrupting real data into noise, then training a model to reverse that corruption one tiny step at a time. In this lecture, we look at: (1) Why diffusion begins by destroying data (2) The forward process: adding noise step by step (3) The reverse process: learning to undo one tiny corruption (4) How images emerge from pure noise (5) Why diffusion works by chaining many easy steps (6) How Stable Diffusion, Midjourney, DALL·E, and Imagen use denoising (7) How diffusion can be applied to language (8) Why diffusion language models can generate tokens in parallel (9) How the same trick appears in video, audio, and molecule generation (10) Why creation can be understood as destruction played backward The core idea is simple: When creation is too hard to do in one shot, define a gradual corruption process and learn to reverse it. #ArtificialIntelligence #MachineLearning #DeepLearning #DiffusionModels #StableDiffusion #GenerativeAI #Denoising #LLM #Vizuara
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
COMO CRIAR VÍDEOS QUE VENDEM SEU PRODUTO COM IA (GUIA COMPLETO)
Tutorial para criação de vídeos de anúncio com IA Links: https://cutt.ly/kt4AqdvX 👉Meu curso completo sobre Inteligências Artificiais com foco em renda extra e viver de internet: https://pay.kiwify.com.br/OUx0Hgb ✅Playlist de cursos gratuitos: https://youtube.com/playlist?list=PLNQBpbIienGEf4oI5z3wFOd_qexy0UrUe&si=oAqDO7cqeYPFB6X6 Editor: designersalvatore@gmail.com Neste canal, abordamos o que é a inteligência artificial e como ela está sendo aplicada em diferentes áreas, como tecnologia. Discutimos tipos de IA, como aprendizado profundo e racional, e os desafios e oportunidades que ela traz. O objetivo aqui é apresentar ferramentas de IA que facilitem o trabalho cotidiano das pessoas e como elas podem se preparar para o futuro com ela. Inscreva-se neste canal se quiser facilmente encontrar maneiras de trabalhar de forma independente, usando ferramentas como Midjourney, Stable diffusion, DALL·E 2, ChatGPT, etc. #PolloAI #PhotoToVideoAds #VideoAds #UGCVideo #AIForMarketing
Machine Learning Algorithms & Models Explained | Complete 2026 Guide
Master the core machine learning algorithms and models. This guide covers supervised learning, unsupervised learning, ensemble methods and neural networks. After this video, you will be able to distinguish between classification and regression, understand how boosting and bagging models function and identify the correct neural network architecture for your data tasks. We break down complex concepts into practical frameworks for IT professionals. Join our WhatsApp community for more IT resources and updates. Chapters: 00:00 Intro 01:05 Machine Learning 01:09 Supervised Learning - Supervised Learning 01:31 Classification 01:42 Regression - Linear Regression 01:47 Regression - Polynomial Regression 01:50 Regression - Lasso 01:54 Regression - Ridge 01:56 Unsupervised Learning - Unsupervised Learning 02:20 Clustering 02:30 Pattern Search - Apriori 02:32 Pattern Search - ECLAT 02:37 Pattern Search - FP-Growth 02:41 Dimensionality Reduction 02:51 Dimensionality Reduction (cont.) 02:55 Statistical Inference 03:00 Ensemble Models - Ensemble Models 03:18 Ensemble Models - Boosting 03:33 Ensemble Models - Bagging 03:46 Reinforcement Learning 03:57 Neural Networks - Neural Networks (part 1) 04:15 Neural Networks - Neural Networks (part 2) 04:26 Neural Networks - Recurrent Neural Networks (RNN) 04:36 Machine Learning Algorithms & Models Overview - Machine Learning (part 1) 04:50 Machine Learning Algorithms & Models Overview - Machine Learning (part 2) 🎓 Join this channel to get access to perks: 🔗 https://www.youtube.com/channel/UCG5i5RvlRtUf2XJUzHw6pyg/join 🖥️ Join on Whatsapp: https://bit.ly/whatsapp-learnitguide 🚀 Boost Your Tech Skills with Our Full Course Playlists: 📦 Kubernetes Full Course: https://bit.ly/kubernetes-full-tutorial-videos 🛠️ DevOps Tutorial & Training: https://bit.ly/devops-full-tutorial-videos ▶️ Terraform Tutorial & Training: https://bit.ly/terraform-full-tutorial-videos 🎭 Puppet Tutorial & Training: https://bit.ly/puppet-full-tutorial-videos 📜 Ansible Tutorial & Training: https://bit.ly/ansible-full-tutorial-videos 🐳 Docker Tutorial & Training: https://bit.ly/docker-full-tutorial-videos 🔧 Jenkins Tutorial & Training: https://bit.ly/jenkins-full-tutorial-videos 🐍 Python Programming Tutorial & Training: https://bit.ly/python-full-tutorial-videos ☁️ Cloud Computing Tutorial & Training: https://bit.ly/cloud-computing-full-tutorial-videos 🌐 Openstack Tutorial & Training: https://bit.ly/openstack-full-tutorial-videos 🖧 Clustering Tutorial & Training: https://bit.ly/clustering-full-tutorial-videos 📡 VCS Cluster Tutorial & Training: https://bit.ly/vcs-clustering-full-tutorial-videos 🐧 Ubuntu Linux Tutorial & Training: https://bit.ly/ubuntu-full-tutorial-videos 🎓 RHCSA and RHCE Tutorial & Training: https://bit.ly/rhce-linux-full-tutorial-videos 🖥️ Linux Tutorial & Training: https://bit.ly/linux-full-training-videos ☕ Support My Work: ☕ Buy me a Coffee: https://buymeacoffee.com/learnitguide 📌 Subscribe for More DevOps & Cloud Tutorials We have uploaded free tutorials on Git, Docker, Jenkins, Kubernetes, Terraform, OpenStack and more. 🔔 Subscribe to our channel @Learnitguide for more updates & hit the 🔔 bell icon! 📺 YouTube: https://bit.ly/learnitguide 📘 Facebook: http://www.facebook.com/learnitguide 🐦 Twitter: http://www.twitter.com/learnitguide 💬 Telegram: https://t.me/learnitguidetutorials 📱 Whatsapp: https://bit.ly/whatsapp-learnitguide 🔗 LinkedIn: https://bit.ly/linkedin-learnitguide 🌐 Website: https://www.learnitguide.net 🔔 Subscribe for AI, career strategy, future tech & skill roadmaps. #MachineLearning #Algorithms #NeuralNetworks #SupervisedLearning #DataScience #AI #LearnITGuide #techtutorial how machine learning models work step-by-step overview step-by-step 2026 overview machine learning algorithms machine learning models supervised learning unsupervised learning neural networks ensemble models reinforcement learning classification vs regression learnitguide machine learning ai it professional machine learning tutorial 2026 machine learning explained supervised learning tutorial unsupervised learning explained neural networks explained
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
045 | TAO Performance Network (SN65): LLM Compression on Bittensor TAO
🔴 LIVE — In this livestream, we sit down with Mentor, co-founder of TAO Performance Network (SN65), to discuss one of the most significant pivots in the Bittensor ecosystem. Originally focused on decentralized VPN infrastructure, TPN is now evolving into Bittensor’s LLM compression and optimization engine—helping make powerful AI models smaller, faster, cheaper, and accessible on everyday hardware. We dive into the massive challenge facing the AI industry today: frontier models are becoming increasingly expensive to run, often requiring specialized hardware and millions of dollars in cloud infrastructure. TPN aims to solve this by creating a decentralized competition where miners race to compress, quantize, prune, distill, and optimize large language models while preserving as much intelligence and performance as possible. We explore how the subnet works, how users can submit optimization requests tailored to specific hardware constraints, and why a distributed network of competing miners may outperform traditional centralized AI teams when it comes to model optimization. We also discuss the growing demand for local AI, private inference, AI agents, edge computing, and why efficient models may become just as important as the models themselves. This conversation covers the future of AI infrastructure, the economics of model compression, and how TPN is positioning itself as a critical piece of the Bittensor ecosystem by making advanced AI usable everywhere. ⚡ Like, Comment, and Subscribe to stay updated on the latest in crypto trends, market updates, and investment opportunities. Don’t forget to hit the bell icon 🔔 so you won’t miss any future updates! Disclaimer: This video is for informational purposes only and should not be taken as financial advice. Always do your own research before making any investment decisions. #bittensor #tao #bittensortao #sn65 #taoperformancenetwork #llmcompression #aicompression #contextcompression #artificialintelligence #decentralizedai #cryptoai #machinelearning #aimodels #opensourceai #aiblockchain #taosubnets #bittensorsubnet