I'm currently researching forecasting and epistemics as part of the Quantified Uncertainty Research Institute.
"I'd love to have a call and catch up in any case! I'm curious whether you already have an opinion on whether places like DeepMind will be interested in paying for evals like the two types mentioned here (character and backdoors)."
Quickly:
1. I'll schedule a call sometime, once I understand my schedule a bit better.
2. I have incredibly little info on DeepMind right now. As you may imagine, personally I'm excited about a lot of these areas, but I can't speak for DeepMind.
"Why did Guesstimate/Squiggle as for-profit not work out?"
I've been asked this question a bunch of times before, happy to give some quick thoughts here. Most of my answer is here.
If it were the case that it seemed very easy to make these as startups, and ideally in which there were some clear cofounders who could handle the business side, I think the for-profit side would have been more promising.
In my case:
1. I realized this was a niche/small space, that getting a large market would likely mean having to pivot.
2. I wasn't sure what might take off. I think Squiggle has a lot going for it, but am not sure if the value proposition is strong enough for a large company now, especially as LLMs have been getting much more powerful (changing the trade-offs around decision tools).
3. My main goal was helping effective altruist / rationalist researchers, and I suspected that focusing much more on commercialization would have hurt that.
4. Related to (3), I just found myself much more motivated to go after altruists/nonprofits than to go after standard enterprise deals
Hi Dawn!
I'd be happy to discuss this.
Quickly (and to give context to others reading this):
Multipolar worlds will compete away >90% of net value that would otherwise be preserved
If they're halfway-reasonable, they could use smart AIs to negotiate for them. Big question is who will control these worlds.
I think it's likely humans will settle on AI solutions that lose 90% of the value vs. my optimal solution, but that's very much a values question, not a multipolar vs. unipolar question.
This seems like an very coarse take to me.
Shutting down one of these companies might cost, say, a trillion dollars and lost investor/employee value. And I think that the real risky 'frontier AI' might only be a portion of their work.
I could very much see an argument for them to stop a lot of the key frontier work and then move to more conservative engineering efforts, for instance. I think that there's a large variety of space to do around AI development and AI safety, it seems easy for me to imagine large changes in direction that could still have some market value but much less risks.
I think there was one certain failure mode of "prediction markets will somehow both be legal, and also more legal than regular sports gambling, in the US".
This combination of scenarios seemed very unlikely to me 4-6 years ago! I think this was seen universally as a tough combination, you can see this in the market prices / valuations of the related companies.
That said, there was an understanding a while back that US public prediction markets would likely be sleazy/predatory in ways similar to sports gambling. This is one reason I preferred prediction tournaments like Metaculus over financial prediction markets like Kalshi.
I'd also flag that there was, and still is, potential for real-money prediction markets to get adapted by large experienced financial authorities for more serious purposes like hedging. There are overall professionalized and useful ways to use these sorts of tools, though it is the case that much of the current market is quite miserable.
I had a bunch of unpublished drafts and notes in Google Docs. I just released them here, using Claude to help organize and summarize.
https://priors.quantifieduncertainty.org/
I imagine some here would find them interesting! Most are fairly old, starting from 2017, when I joined FHI.