PhD researcher University of Amsterdam / AMLab. Structure-aware ML for scientific systems: inference, efficient architectures, quantum AI4Science.

Amsterdam
Joined April 2010
An interlude about structure computation, SSM and attention. Myosotis: arxiv.org/abs/2509.20503 I hope to tell more in this line of work later. See poster at SPIGM workshop.
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Sharing some deeply personal and existential reflections on scientific identity, the changing culture of AI research, the erosion of intellectual autonomy, and the growing disconnect between scientific rigor, professional recognition, and what organizations actually reward. As usual, feedback and debate are welcome and actively encouraged! mariya.fyi/posts/stranger-in… – at San Francisco, CA
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Achievement unlocked: got rejected from postdoc position. On the other hand 🫡🫡🫡
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Evgenii Egorov retweeted
Ten years ago we posted the first preprint on neural quantum states. Today we're launching Ketworks, a community site on NQS. Two parts: Ketbook, a reference written by the community, and Ketboard, variational energies from the literature on exactly defined benchmarks. Link below
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Атака координат и какулюса
Mathematicians used to study Euclidean geometry. It was beautiful. But coordinates and calculus together became a more powerful tool that surpassed it. Even though they were often very ugly and involved a lot of grinding work, they made Euclidean geometry essentially obsolete.
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Evgenii Egorov retweeted
LMs can play chess, but they can't really explain their moves well (chess engines can't at all). Our new BinProp scaffold tackles this, and nearly triples LMs’ score on our chess-explanation benchmark. It works on other games too! Try it on your own games on our site-🧵👇
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I am curious what people do with their informational security? I should change/backup more as I think everything will be hacked more frequently but idk concrete meaningful steps.
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Certified Dutch Ik wil graag een koffie speaker
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Welcome to autoregressive sampling
I am enjoying the new Codex autocomplete, but I'm curious how it works. It seems to pre-prepare the same annoyed comments I would make. If the predictions are from the LLM, then surely it should have known I wasn't going to be happy with its output in the first place.
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Starting slow and then voshel v ruj
Replying to @NateSilver538
So not to go all Yudkowsky Monocause Theory. But a lot of AI company talk that *sounds smart* did come from me, or me via Bostrom or other diffusion modes. High-powered ideas like "recursive self-improvement" and "AGI" are ideas they did not invent themselves, but got off higher-quality outside thinkers. There's a big intellectual history behind me in turn, but the AI companies did not study this history independently; they got it downstream of my writing it up. I naturally spent some time trying to figure out what the positive vision for AGI and ASI would look like, back in the mid-2000s. But I considered it a lower priority to write up. And AI company executives are not at the intellectual level where they can invent coherent answers to questions like that, if they don't have my answer sheet to copy from. They can't tell you what the positive vision for AGI or ASI looks like, because I didn't prioritize writing up that part of my earlier thoughts. They can't copy it off from the same answer sheet they used to produce smart-sounding conversation like "general intelligence" or "recursive self-improvement" or "extinction risk" or "AI alignment problem". If they're not reading off my answer sheet, AI company executives are pretty ordinary as intellectuals. Being able to spend billions on GPUs does not make you a genius inventor, even if we're used to amazing inventions coming from genius rather than black-box optimization. AI company executives are not going to give you better answers about "what's the positive vision" than any other random intellectual challenged with a question beyond their wits. If you start hearing good-sounding answers from Anthropic or OpenAI, it means that Mythos or HPIM advanced to the point of learning how to sound convincing about utopia to humans. I did do an *abstract* writeup on constraints and requirements over positive ASI scenarios (see eg "31 Laws of Fun"); but that does AI companies no good, because they would need to be able to sketch a concrete AGI scenario from those abstract ideas. That again is beyond them if I have not done their homework. It is of course not in humanity's interest that I try to do this homework for the AI companies now. It would only be a lie. They have no utopia to offer.
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I still don’t understand what is arguments against? Just do… Some argument that after 100 years it would be a bit trickier with uran for them but this is manageable in a different ways.
Replying to @andyburnham
Develop nuclear power.
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Sometimes I am thinking, how can I save the world, specially academia? Clearly, it can not lost any longer without my advice. So let me help. One problem is money. But I think consider I am an investor in quantum company. Quantum company want to make me believe that they have this super duper thing quantum advantage for my favorite optimization problem. So for my investment decision it is important that somebody independent will try to simulate classically. So maybe some benefit which can be measured is academy is an independent institute of verifiers of investment decisions. 🤔 Similar line of arguments I guess is with journalists but it never work. So no advice, sorry.
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Writing my small ml papers. One is out soon 🫨
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Can we please instead of “checklists” has innovation of github sync with open review? And then submit is just a commit which last fits in time cutoff
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O! That’s my theory. Basically all multiverse is a one universe but for one person in every possible way and they interact. This tweet also shows that well Hello! Nice to meet me.
I have a theory that every person, maybe every living thing on this planet, is actually you experiencing existence from a different perspective. If that were true, every time you hurt someone, insult someone, or make another living being suffer, you are ultimately doing it to yourself. Maybe individuality is just perspective.
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I would more curios to read from mathematicians how teaching should change. Clearly, hyper specialization now is counter productive. On the other hand, for effective interaction with gpt one should have good and wide operational skills with variety of objects and domains. But how to learn them? I think our average person brain like mine is bounded by amount information I can process and internalize. Like at my peak child brain I was able to do 2+2 hours of teaching-solving. It doesn’t look sufficient.
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Recalling from Gelfand «На кафедре функционального анализа больше всего боялись не того, что Колмогоров придёт и кого-то отругает или раскритикует. Больше всего боялись, что он придёт, послушает математическую проблему, над которой кафедра безуспешно билась несколько месяцев, тут же у доски её решит — и тем самым лишит всех работы и тем для диссертаций».
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I skimmed an I understand (not really) two things: 1) Half of preprint 2) I don’t know tools from other half So essentially I think it is no way I have possibly do this. So I am not sure what I should feel. 🤔 I guess my most feeling that I want to go home which is not exists and well I am little bit numb.
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