Ep 11: Stanford Professor Tatsu Hashimoto on AI Biases and Improving LLM Performance

Patrick and Jacob sit down with Tatsu Hashimoto, Professor of AI at Stanford, to discuss the incredible open source projects from his research group like Alpaca and AlpacaFarm, whether data, algorithms, fine-tuning or RLHF is most important for performance, if AI is liberal or conservative, and much more!

 

(0:00) - intro

(1:05) - journey to Stanford

(2:50) - origins of Alpaca

(6:08) - capabilities of the Alpaca model

(16:39) - the future of AI

(20:07) - AlpacaFarm

(21:37) - how to improve language models

(29:15) - do language models form opinions?

(32:15) - how to solve bias in ai

(34:18) - how does academia fit into the world of AI

(42:01) - over-hyped/under-hyped

(46:35) - questions Tatsu doesn’t have time for

 

With your co-hosts: 

@jasoncwarner - Former CTO GitHub, VP Eng Heroku & Canonical 

@ericabrescia - Former COO Github, Founder Bitnami (acq’d by VMWare) 

@patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @jacobeffron - Partner at Redpoint, Former PM Flatiron Health

@jacobeffron - Partner at Redpoint, Former PM Flatiron Health

Jacob is an AI investor at Redpoint Ventures. He's led Redpoint's investments in companies like Abridge, Physical Intelligence & Legora. Follow Jacob on Twitter (@jacobeffron).

On Unsupervised Learning we probe the sharpest minds in AI in search for the truth about what's real today, what will be real in the future and what it all means for businesses and the world. If you're a builder, researcher or investor navigating the AI world, this podcast will help you deconstruct and understand the most important breakthroughs and see a clearer picture of reality. Subscribe to this show to stay up to date on our latest episodes.