[EDIT: Thanks for the questions everyone! Just noting that I'm mostly done answering questions, and there were a few that came in Tuesday night or later that I probably won't get to.]
Hi everyone! I’m Ajeya, and I’ll be doing an Ask Me Anything here. I’ll plan to start answering questions Monday Feb 1 at 10 AM Pacific. I will be blocking off much of Monday and Tuesday for question-answering, and may continue to answer a few more questions through the week if there are ones left, though I might not get to everything.
About me: I’m a Senior Research Analyst at Open Philanthropy, where I focus on cause prioritization and AI. 80,000 Hours released a podcast episode with me last week discussing some of my work, and last September I put out a draft report on AI timelines which is discussed in the podcast. Currently, I’m trying to think about AI threat models and how much x-risk reduction we could expect the “last long-termist dollar” to buy. I joined Open Phil in the summer of 2016, and before that I was a student at UC Berkeley, where I studied computer science, co-ran the Effective Altruists of Berkeley student group, and taught a student-run course on EA.
I’m most excited about answering questions related to AI timelines, AI risk more broadly, and cause prioritization, but feel free to ask me anything!
Hi Ajeya! :) What do you think about open source projects like https://www.eleuther.ai/ that replicate cutting-edge projects like GPT-3 or Alphafold? Speaking as an outsider, I imagine that a lot of AI progress comes from "random" tinkering, and so I wondered if "Discord groups tinkering along" are relevant actors in your strategic landscape.
(I really enjoyed listening to the recent interview!)
I'm not very familiar with these open source implementations; they seem interesting! So far, I haven't explicitly broken out different possible sources of algorithmic progress in my model, since I'm thinking about in a very zoomed-out way (extrapolating big-picture quantitative trends in algorithmic progress). I'm not sure how much of the progress captured in these trends comes from traditional industry/academia sources vs open source projects like these.