I do research around longtermism, forecasting and quantification, as well as some programming, at the Quantified Uncertainty Research Institute (QURI).
I write a Forecasting Newsletter, and have programmed Metaforecast.org, a search tool which aggregates predictions from many different platforms. I also generally enjoy winning bets against people too confident in their beliefs.
I’m also a fairly good forecaster: I started out on predicting on Good Judgment Open and CSET-Foretell, but now do most of my forecasting through Samotsvety, of which Scott Alexander writes:
Enter Samotsvety Forecasts. This is a team of some of the best superforecasters in the world. They won the CSET-Foretell forecasting competition by an absolutely obscene margin, “around twice as good as the next-best team in terms of the relative Brier score”. If the point of forecasting tournaments is to figure out who you can trust, the science has spoken, and the answer is “these guys”.
Otherwise, I like to spend my time acquiring deeper models of the world, and generally becoming more formidable. A good fraction of my research is available either on the EA Forum or backed-up on nunosempere.com, which also hosts my more casual personal blog.
I was a Future of Humanity Institute 2020 Summer Research Fellow, and then worked on a grant from the Long Term Future Fund to do “independent research on forecasting and optimal paths to improve the long-term.” After that, I joined QURI and spent some time in the Bahamas as part of the FTX EA Fellowship.
Before that, I studied Maths and Philosophy, dropped out in exasperation at the inefficiency, picked up some development economics; helped implement the European Summer Program on Rationality during 2017, 2018 and 2019, and SPARC during 2020; worked as a contractor for various forecasting and programming projects; volunteered for various Effective Altruism organizations, and carried out many independent research projects. In a past life, I also wrote a popular Spanish literature blog, and remain keenly interested in Spanish poetry.
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Thanks for pointing out that section. I agree that the section discusses the issue. But I am left unsatisfied about whether it defeats it.
In particular,
“I think this is likely to be sufficient for training a transformative model, although I am not confident. ”
“it is less clear whether model computation will dominate the computation of the environment. Nonetheless, I still believe this is likely”
don’t seem hugely confident. And that’s fine, the report is already pretty long. But then even if the report is not at fault I am kind of unsatisfied about the evolutionary anchor part being used as an actual upper bound—not sure whether people are actually doing that all that often, but Eli’s comment below seems to indicate that it might be, and I remember it being used that way on a couple of occasions.