AI is everywhere, from coding assistants to chatbots, but what's really happening under the hood? It often feels like a "black box," but it doesn't have to be.
In this episode, Allen sits down with Manning author and AI expert Emmanuel Maggiori to demystify the core concepts behind Large Language Models (LLMs). Emmanuel, author of "The AI Pocket Book," breaks down the entire pipeline - from the moment you type a prompt to the second you get a response. He explains complex topics like tokens, embeddings, context windows, and the controversial training methods that make these powerful tools possible.
IN THIS EPISODE
00:00 - Welcome & Why "The AI Pocket Book" is a Must-Read
15:20 - The Basic LLM Pipeline Explained
8:05 - What Are Tokens?
21:30 - Understanding the Context Window
25:50 - How Embeddings Represent Meaning
35:45 - Controlling Creativity with Temperature
39:30 - How LLMs Learn From Internet Data
45:25 - Fine-Tuning with Human Feedback (RLHF)
51:15 - Why AI Hallucinates
56:45 - When Not to Use
📘 GET THE BOOK!
Dive deeper into the concepts discussed in this episode with Emmanuel's book, "The AI Pocket Book".
Get 45% off with code FHWFmaggiori at checkout.
🔗 https://hubs.ly/Q03VL7R10
CONNECT
🎙️ Guest: Emmanuel Maggiori
https://emaggiori.com/
👨💻 Host: Allen Wyma
X/Twitter: https://x.com/allenwyma
🚀 Flying High with Flutter
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#AI #ArtificialIntelligence #LLM #MachineLearning #DeepLearning #ChatGPT #Developer #Programming #TechPodcast #SoftwareDevelopment #AITraining #Embeddings #Tokens
