Why Release a Large Language Model?

In episode 22 of The Gradient Podcast, we talk to Connor Leahy, an AI researcher focused on AI alignment and a co-founder of EleutherAI.

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Connor is an AI researcher working on understanding large ML models and aligning them to human values, and a cofounder of EleutherAI, a decentralized grassroots collective of volunteer researchers, engineers, and developers focused on AI alignment, scaling, and open source AI research. The organization's flagship project is the GPT-Neo family of models designed to match those developed by OpenAI as GPT-3.

Sections:

(00:00:00) Intro(00:01:20) Start in AI(00:08:00) Being excited about GPT-2 (00:18:00) Discovering AI safety and alignment(00:21:10) Replicating GPT-2 (00:27:30) Deciding whether to relese GPT-2 weights(00:36:15) Life after GPT-2 (00:40:05) GPT-3 and Start of Eleuther AI(00:44:40) Early days of Eleuther AI(00:47:30) Creating the Pile, GPT-Neo, Hacker Culture(00:55:10) Growth of Eleuther AI, Cultivating Community(01:02:22) Why release a large language model(01:08:50) AI Risk and Alignment(01:21:30) Worrying (or not) about Superhuman AI(01:25:20) AI alignment and releasing powerful models(01:32:08) AI risk and research norms(01:37:10) Work on GPT-3 replication, GPT-NeoX(01:38:48) Joining Eleuther AI(01:43:28) Personal interests / hobbies(01:47:20) Outro

Links to things discussed:

* Replicating GPT2–1.5B , GPT2, Counting Consciousness and the Curious Hacker

* The Hacker Learns to Trust

* The Pile

* GPT-Neo

* GPT-J

* Why Release a Large Language Model?

* What A Long, Strange Trip It's Been: EleutherAI One Year Retrospective

* GPT-NeoX