Practical AI: Machine Learning, Data Science
Technology:Software How-To
Daniel had the chance to sit down with @swyx and Alessio from the Latent Space pod in SF to talk about current AI trends and to highlight some key learnings from past episodes. The discussion covers open access LLMs, smol models, model controls, prompt engineering, and LLMOps. This mashup is magical. Don’t miss it!
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Timestamps:
(00:00) - Welcome to Practical AI
(01:16) - Latent Space Podcast
(04:00) - Practical AI Podcast
(06:20) - Prediction Guard
(08:05) - Daniel's favorite episodes
(10:21) - Alessio's favorite episode
(10:54) - Swyx's favorite episode
(12:44) - Listener favorites
(15:14) - LLMOps
(17:06) - Reza Shabani
(19:06) - Benchmarks 101
(20:06) - Roboflow
(21:38) - Mode collapse
(26:21) - Rajiv Shah
(28:01) - Staying on top of things
(33:11) - Kirsten Lum
(34:31) - datadan.io
(38:48) - Prompt engineering
(40:38) - Unique challenges engineers face
(42:51) - AI-UX
(45:31) - NLP data sets
(50:49) - Unlabeled data sets
(55:07) - Lightning round!
(55:20) - What's already happened in AI?
(56:27) - Unsolved questions in AI
(58:01) - Get hands on
(58:53) - Outro
Rise of the AI PC & local LLMs
AI in the U.S. Congress
First impressions of GPT-4o
Full-stack approach for effective AI agents
Autonomous fighter jets?!
Private, open source chat UIs
Mamba & Jamba
Udio & the age of multi-modal AI
RAG continues to rise
Should kids still learn to code?
AI vs software devs
Prompting the future
Generating the future of art & entertainment
YOLOv9: Computer vision is alive and well
Representation Engineering (Activation Hacking)
Leading the charge on AI in National Security
Gemini vs OpenAI
Data synthesis for SOTA LLMs
Large Action Models (LAMs) & Rabbits 🐇
Collaboration & evaluation for LLM apps
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