Practical AI: Machine Learning, Data Science
Technology
As a technologist, coder, and lawyer, few people are better equipped to discuss the legal and practical consequences of generative AI than Damien Riehl. He demonstrated this a couple years ago by generating and copyrighting every possible musical melody. Damien joins us to answer our many questions about generated content, copyright, dataset licensing/usage, and the future of knowledge work.
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Timestamps:
(00:07) - Welcome to Practical AI
(00:43) - Damien Riehl
(01:36) - Regulations on AI
(03:52) - All the music
(07:21) - Human vs AI output
(11:30) - Working alongside AI
(14:51) - Finding the gray area
(20:47) - Ai is not copyright-able
(24:19) - Where is the line drawn?
(27:42) - Snake eating its own tail
(30:08) - Can I use these models?
(31:15) - Lessening value of IP
(34:05) - No more patents
(35:55) - 4 Worlds
(38:27) - Scarcity or abundance?
(39:36) - Outrunning the tsunami
(41:26) - Goodbye
(42:05) - 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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