Videos de Ciencia
Videos sobre avances científicos y descubrimientos.
Ciencia 255 videos
Acabaram as Vagas Júnior em Visão Computacional (e o que fazer agora)
As vagas júnior em Visão Computacional estão desaparecendo — e a culpa é dos grandes modelos de IA. Nesse corte da nossa live, o Hallison responde uma dúvida real do inscrito Bruno: vale a pena investir em Visão Computacional se estágio é quase impossível de achar e o mercado parece exigir mestrado logo de cara? A resposta honesta: sim, as vagas júnior em áreas especializadas como CV e ciência de dados estão caindo. Mas isso não significa que não há espaço — significa que o mercado está mudando de perfil. ✅ O que você vai aprender nesse vídeo: – Por que as vagas júnior em Visão Computacional estão diminuindo – O que é o "Engenheiro de IA" e por que esse perfil está crescendo – Quando faz sentido fazer mestrado (e quando não faz) – Como se posicionar no mercado de IA sem ser especialista em pesquisa – Quais nichos (como imagens médicas) ainda têm espaço para especialistas no Brasil 🔗 Vídeos sobre Visão Computacional no canal: Pesquise "visão computacional Programação Dinâmica" no YouTube 📌 Sobre o canal: Programação Dinâmica é o canal do Hallison e da Kizzy para quem quer aprender Inteligência Artificial além do Hype, estudando e discutindo tópicos como Machine Learning, Ciência de Dados, programação, Matemática, impacto de novas tecnologias na sociedade... — com profundidade e sem enrolação. 📚 Livro para estudar Bancos de Dados - https://amzn.to/3Hjjusc 📚 Livros recomendados de Data Science: https://amzn.to/2XZyxUr 📚 Livros de Algoritmos e Estruturas de Dados: https://amzn.to/3d5wK4m SetUp - Equipamentos: https://amzn.to/37Cg3N2 🟣 Canal na Twitch para lives: https://www.twitch.tv/pgdinamica 🟦 Canal do Telegram para receber todos os vídeos: https://t.me/pgdinamica 🥰 Se você gosta do nosso trabalho e acha relevante a nossa atuação no Youtube, considere nos apoiar se tornando membro do canal: https://www.youtube.com/programacaodinamica/join ✉️ E-mails: – Propostas comerciais: pgdinamica@brunch.ag – Demais assuntos: contato@programacaodinamica.com.br 👩🏾💻👨🏾💻 Confira mais conteúdo em nosso blog: https://medium.com/programacaodinamica TikTok: @pgdinamica 📸 Nos siga no Instagram: https://instagram.com/pgdinamica 📸 @kizzy_terra @hallpaz 🐦 Nos siga no Twitter: https://twitter.com/pgdinamica 🐦 @kizzy_terra @hallpaz * Curta a Programação Dinâmica no facebook: fb.com/pgdinamica * Nosso repositório no Github: github.com/programacaodinamica * Confira os artigos no Python Café: pythoncafe.com.br
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
5 Robots que Parecen Humanos y Ya Limpian tu Casa en 2026
En 2026 los robots humanoides para el hogar ya no son ciencia ficción. Hoy te presento los 5 más avanzados diseñados específicamente para trabajo doméstico — desde el más barato a $5,900 hasta el más sofisticado a $20,000. Te explico qué puede hacer cada uno, qué no puede hacer todavía, y cuál tiene más probabilidades de llegar primero a tu casa. 📌 Fuentes: — Apptronik Apollo: anuncio oficial de financiamiento febrero 2026, apptronik.com — Tesla Optimus Gen 3: declaraciones de Elon Musk en Davos enero 2026, tesla.com — Unitree R1: lanzamiento oficial abril 2026, unitree.com — Figure 03: anuncio oficial octubre 2025, figure.ai — portada Time Magazine mejores inventos 2025 — 1X Neo: lanzamiento oficial octubre 2025 con preórdenes reales, 1x.tech 👍 Déjame tu opinión en los comentarios. 🔔 Suscríbete a Frontera Tech para no perderte lo que viene. #RobotsHogar #RobotsHumanoides2026 #FronteraTech #TeslaOptimus #1XNeo Timeline: 0:00 — Hook 0:50 — Robot 5: Apptronik Apollo 3:00 — Robot 4: Tesla Optimus 5:00 — Robot 3: Unitree R1 7:00 — Robot 2: Figure 03 9:30 — Robot 1: 1X Neo 11:30 — Cierre
MOYA, el nuevo robot con IA de China que se siente demasiado real (92% humano)
¿Listos para alucinar con los avances más locos en robots humanoides? Desde Moya, el robot de piel tibia que incomodó a internet, hasta Atlas levantando pesas y robots jugando ping pong, te contamos TODO. No te pierdas este recorrido por lo último en inteligencia artificial y tecnología. Suscríbete y cuéntanos en los comentarios qué robot te sorprendió más. #robots #tecnología #IA #innovación #futuro 👉 Este canal es realizado en colaboración con https://www.youtube.com/@airevolutionx 0:02 - Introducción y avances recientes en robots humanoides 0:36 - Moya: el humanoide de DroidUp y su impacto 5:05 - Atlas de Boston Dynamics: logros y proyecciones 7:58 - Agibot: robot jugando tenis de mesa autónomamente 9:34 - Cody: robot amigable para niños de Mind Children 11:20 - Qwen Robot de Alibaba y el futuro de IA robótica 13:56 - Conclusiones y perspectivas futuras ¡Ya estamos disponibles en Spotify! Escúchalo ahora https://open.spotify.com/show/1Hq2S58AkMMzrl0qiQhoD2
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
¿Sabes cuál es? El robot humanoide más avanzado en 2026
¿Estamos ante el año en que los robots humanoides pasan de ser ciencia ficción a ser una realidad en nuestras casas? En este capítulo de Flash Robot, analizamos los 5 mejores robots humanoides del momento, evaluando su IA, destreza, coste y, sobre todo, su disponibilidad real para el mercado. Desde la versatilidad del G1 de Unitree hasta la impresionante tecnología del nuevo Figure 03, descubre cuál de estas máquinas está liderando la revolución de la automatización en 2026. ¡El ganador te sorprenderá! En este vídeo analizamos: 00:00 Introducción: El futuro ya está aquí. 00:30 Criterios del ranking (Prestaciones, Coste, Disponibilidad). 01:19 Puesto #5: Neo de 1X (El compañero doméstico). 02:37 Puesto #4: Atlas Eléctrico de Boston Dynamics (Ingeniería de élite). 03:59 Puesto #3: Tesla Optimus (La apuesta masiva de Elon Musk). 05:27 Puesto #2: G1 de Unitree (El robot más viral y accesible). 06:44 ¿Por qué este ranking podría cambiar pronto? 07:31 Puesto #1: Figure 03 (La inteligencia artificial hecha robot). Más información y bibliografía: Accede a todos los datos técnicos, fuentes oficiales y comparativas detalladas en nuestra web: https://flashrobot.tech/episodio/el-robot-humanoide-mas-avanzado-en-2026/ ¿Te apasiona la robótica y la IA? Suscríbete a Flash Robot para no perderte ni un avance de los humanoides que están cambiando el mundo. ¡Activa la campana de notificaciones! #RobotsHumanoides #InteligenciaArtificial #FigureAI #TeslaOptimus #BostonDynamics #Unitree #FlashRobot #Tecnologia2026 #Robótica
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
Este Animal sin Cerebro de la Naturaleza Ve Mejor que la IA Militar
24 ojos. Cero cerebro. Y aun así ve mejor que un dron militar de un millón de dólares.La naturaleza lo resolvió primero. En Sab3Tudo revelamos la ingeniería biológica detrás de los animales — tecnología que la industria militar y las mayores corporaciones del mundo todavía no logran replicar. En este video vas a entender cómo la medusa caja hace visión por computadora de 360° con 24 ojos reales — algunos con córnea, lente y retina, igual que los tuyos — sin una sola neurona central de mando. Mientras DARPA quemaba millones en su programa Fast Lightweight Autonomy intentando que drones esquivaran árboles solos, este animal de gelatina ya cruzaba manglares oscuros sin tocar nada. El secreto es lo que la ingeniería llama procesamiento "en el borde": cada ojo resuelve su propia imagen antes de mandar la señal adelante. Biomimética pura, y la naturaleza lo hizo gratis. ⏱️ CAPÍTULOS 00:00 El dron de US$1 millón que falló 01:10 Cómo funcionan los 24 ojos (Dan-Eric Nilsson / Lund) 04:00 El dilema de la cámara: por qué "media cámara" no ve nada 06:45 Si lo dominásemos (DARPA, prótesis, robots de rescate) 09:10 El cierre inevitable 🔗 Más de Sab3Tudo: el pavo real que crea color sin pigmento. 👇 Suscríbete. Videos nuevos cada lunes y viernes.——— 🔑 Palabras clave (indexación semántica)ES: medusa caja, medusa avispa de mar, visión por computadora, animal sin cerebro, biomimética, biomimesis, vida marina, naturaleza, ingeniería de la naturaleza, visión 360 grados, chironex fleckeri. EN: box jellyfish, box jellyfish facts, 24 eyes, brainless animal, computer vision, biomimicry, marine life, nature engineering.PT: água-viva caixão, visão computacional, animal sem cérebro, biomimética, natureza, vida marinha. #naturalezard #biomimética #medusacaja AVISO LEGAL: Este video tiene fines educativos, informativos y de entretenimiento. Aunque se basa en investigaciones, datos científicos y teorías existentes, algunas imágenes y escenas presentadas pueden ser recreaciones artísticas o simulaciones digitales (IA/CGI) creadas con fines ilustrativos. El objetivo es facilitar la comprensión de las hipótesis planteadas.