Practical AI: Machine Learning, Data Science
Technology
Chris and Daniel take a step back to look at how generative AI fits into the wider landscape of ML/AI and data science. They talk through the differences in how one approaches “traditional” supervised learning and how practitioners are approaching generative AI based solutions (such as those using Midjourney or GPT family models). Finally, they talk through the risk and compliance implications of generative AI, which was in the news this week in the EU.
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Timestamps:
(00:00) - Welcome to Practical AI
(00:43) - Fully Connected
(02:38) - What is AI today?
(05:54) - A big AI misconception
(14:18) - Generative AI
(16:48) - Foundation models
(18:22) - Generative models
(26:20) - Sponsor: Changelog News
(27:45) - AI and the destruction of mankind
(33:26) - AI pilots
(41:42) - Fundamentally transforming humans
(45:54) - Outro
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
Advent of GenAI Hackathon recap
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