AI, Machine Learning, Deep Learning and Generative AI Explained
Want to learn more about Agentic AI + Data? Register here → https://ibm.biz/BdeGLe Want to play with the technology yourself? Explore our interactive demo → https://ibm.biz/BdKSer Join Jeff Crume as he dives into the distinctions between Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Foundation Models and how these technologies have evolved over time. He also explores the latest advancements in Generative AI, including large language models, chatbots, and deepfakes - and clarifies common misconceptions, simplifies complex concepts, and discusses the impact these technologies have on various fields. AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdKSei
▶︎
The Limits of AI: Generative AI, NLP, AGI, & What’s Next?
▶︎
A Brief History of AI: From Machine Learning to Gen AI to Agentic AI
▶︎
How does AI actually work? Transformers explained
▶︎
But what is a neural network? | Deep learning chapter 1
▶︎
How AI Agents Think, Plan & Execute — IBM Breaks It Down!
▶︎
RAG vs Fine-Tuning vs Prompt Engineering: Optimizing AI Models
▶︎
Don't learn AI Agents without Learning these Fundamentals
▶︎
Ex-Google Officer: You Only Have 3 Years Left Before It Hits! - Mo Gawdat
▶︎
Generative vs Agentic AI: Shaping the Future of AI Collaboration
▶︎
11. Introduction to Machine Learning
▶︎
Large Language Models explained briefly
▶︎
7 AI Terms You Need to Know: Agents, RAG, ASI & More
▶︎
The 7 Skills You Need to Build AI Agents
▶︎
What is generative AI and how does it work? – The Turing Lectures with Mirella Lapata
▶︎
How AI agents & Claude skills work (Clearly Explained)
▶︎
Every Machine Learning Model Explained in 15 minutes
▶︎
What AI Agent Skills Are and How They Work
▶︎
RAG vs. CAG: Solving Knowledge Gaps in AI Models
▶︎
AI & Education: Generative AI & the Future of Critical Thinking
▶︎