Founder / ML researcher / ML engineer
Working (6-15 years of experience)

I'm a future ex-Apple ML engineer ;)  with some research and entrepreneurial background. I've been following AI technical alignment research, but am also interested in the bigger problem which I call Human alignment. I'm starting a new project, which aims at tackling one aspect of this bigger problem. I'm a long term member of the Czech EA and LW community, attended CFAR workshop.

How others can help me

I'm looking for a cofounder / ML researcher / ML engineer for my new FTX-funded project! See the role description:


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Topic Contributions


Continuity Assumptions

The problem is that sometimes you can see a process is actually continuous only ex post. I think I saw this argument in Yudkowski's writing that sometimes you just don't know what variable to observe, so then a discontinuous event surprises you and only after that you realize you should have been observing X, which would make it seem continuous.

Who's hiring? (May-September 2022)

I'm looking for a cofounder / ML researcher / ML engineer for a new FTX-funded project related to prediction markets and large language models!

The long term vision is to improve our decision making as a humanity. We aim to do that by improving how prediction markets work by employing AI. See the full role description:

Little bit about me.

FLI launches Worldbuilding Contest with $100,000 in prizes

That something is very unlikely doesn't mean it's unimaginable. The goal of imagining and exploring such unlikely scenarios is that with a positive vision we can at least attempt to make it more likely. Without a positive vision there are only catastrophic scenarios left. That's I think the main motivation for FLI to organize this contest.

I agree, though, that the base assumptions stated in the contest make it hard to come up with a realistic image.

Consider trying the ELK contest (I am)

During the 2 hours of reading and skimming through the relevant blog posts I was able to come up with 2 strategies (and no counter-examples so far). They seem to me as quite intuitive and easy to come up with, so I'm wondering what I got wrong about the ELK problem or the contest...

Due to the low confidence in my understanding I don't feel comfortable submitting these strategies, as I don't want to waste the ARC's team time.

My background: ML engineer (~7 years of experience), some previous exposure to AGI and AIS research and computer security.

Comments for shorter Cold Takes pieces

Thank you for a thought provoking post! I enjoyed it a lot.

I also find the "innovation as mining" hypothesis intuitive. I'd just add that innovation gets harder for humans, but we don't know whether it holds in general (think AI). Our mental capacity has been roughly constant since ancient Greece, but there is more and more previous work to understand before one can come up with something new.  This might not be true for AI, if their capacity scales.

On the other hand there is a combinatorial explosion of facts that you can combine to come up with an innovation and I don't know what fraction of the combinations will actually be useful and judged as innovation. So overall, the difficulty might increase, stay roughly the same, or decrease, depending on how the number of useful combination scales with the number of all combinations.

I also suspect that subjective rankings of past accomplishments just tend, for whatever reason, to look overly favorably on the past.

One explanation of this would be that innovation needs time to collect its impact. Old innovations are well integrated into the society, so they have already collected most of its impact, while new innovations have most of their impact still in the future, so we don't perceive them as transformative yet.

Why don't governments seem to mind that companies are explicitly trying to make AGIs?

I think governments are not aware of the stop button problem and they think in case of emergency they can just shut down the company / servers running the AGI using force. That's what happened in the past with digital currencies (which Jackson Wagner mentions here as a plausible member of the same reference class as AGI for governments) before bitcoin - they either failed on their own, or if successful, were shut down by government ( 

Who are your role models?

Daniel Schmachtenberger. Look up some of his youtube interviews. I like especially the one with Lex Fridman ( He's a very thoughtful, yet humble person. His approach is very multi-disciplinary, systems-level, holistic. For me he is a role model for how he combines the world-knowledge and self-knowledge, and how clearly he is able to articulate his ideas, which I think are very EA-compatible (he mentions EA from time to time, but I haven't heard any endorsement from him). Yet he goes further than what is discussed within EA eg. on the topics of personal development and meaning making.

Daniel's website:

A project he is a part of:

Also very relevant to EA: Psychological Pitfalls of Engaging With X-Risks & Civilization Redesign w/ Daniel Schmachtenberger:

What we learned from a year incubating longtermist entrepreneurship

Very interesting read, thanks for publishing this!

I am curious what qualified as "having longtermist experience" for you?

Matt Levine on the Archegos failure

a meaningful retrospective is much easier to come by than for, say, the Covid pandemic.

Agreed, but we have this rare example of Dominic Cummings, the chief adviser to Boris Johnson during the pandemic, being thoroughly interviewed about the UK's response to the pandemic. For me it was extremely interesting to peek under the hood of UK government departments and see their failure modes. If you enjoyed the CS report, you might enjoy this one, too.

Founder / ML researcher / ML engineer
Working (6-15 years of experience)