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

Ep 11: Stanford Professor Tatsu Hashimoto on AI Biases and Improving LLM Performance 50:16 Share

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