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Cake day: May 16th, 2025

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  • After seeing this, I reminded myself that I’ve seen this type of thing happen before. Over the past half year, so many programmers enthusiastically embraced vibe coding after seeing one or two impressive results when trying it out for themselves. We all know how that is going right now. Baldur Bjarnason had some great essays (1, 2) about the dangers of relying on self-experimentation when judging something, especially if you’re already predisposed into believing it. It’s like a mark believing in a psychic after he throws out a couple dozen vague statements and the last one happens to match with something meaningful, after the mark interprets it for him.

    Edit: Accidentally hit reply too early.



  • I don’t know any quantum physics and I’ve only taken one class on quantum computing, but the part about real vs complex numbers is quite funny to me. The very first homework exercise in that class was showing that, in quantum computation, there is no difference in using real or complex amplitudes (you can simulate any pure state with complex amplitudes using real amplitudes and only one extra qubit). The real reason to use complex amplitudes is “Why not, real numbers are complex numbers anyway.” It does help that the quantum Fourier transform is far more convenient with complex amplitudes.


  • Not sure if analog turing machines provide any new capabilities that digital TMs do, but I leave that question for the smarter people in the subject of theorethical computer science

    The general idea among computer scientists is that analog TMs are not more powerful than digital TMs. The supposed advantage of an analog machine is that it can store real numbers that vary continuously while digital machines can only store discrete values, and a real number would require an infinite number of discrete values to simulate. However, each real number “stored” by an analog machine can only be measured up to a certain precision, due to noise, quantum effects, or just the fact that nothing is infinitely precise in real life. So, in any reasonable model of analog machines, a digital machine can simulate an analog value just fine by using enough precision.

    There aren’t many formal proofs that digital and analog are equivalent, since any such proof would depend on exactly how you model an analog machine. Here is one example.

    Quantum computers are in fact (believed to be) more powerful than classical digital TMs in terms of efficiency, but the reasons for why they are more powerful are not easy to explain without a fair bit of math. This causes techbros to get some interesting ideas on what they think quantum computers are capable of. I’ve seen enough nonsense about quantum machine learning for a lifetime. Also, there is the issue of when practical quantum computers will be built.



  • On one side, we have a trolley problem thought experiment involving hypothetical children tied to hypothetical train tracks and some people sending him rude emails. On the other side, we have actual dead children and actual hospitals and apartments reduced to rubble. I wonder which side is more convincing to me?

    It’s the same pattern of thought as rationalists with AI, trying to fit everything they see into their apocalypse narrative while ignoring the real harms. Rationalists talk a good game about evidence, but what I see them do in practice is very different. First, use mental masturbation (excuse me, “first principles”) to arrive at some predetermined edgy narrative, and then cherry pick and misinterpret all evidence to support it. It is very important that the narratives are edgy, otherwise what are we even writing 10,000 word blog posts for?








  • I have a lot to say about Scott, being that I used to read his blog frequently and it affected my worldview. This blog title is funny. It was quite obvious that he at least entertained, if not outright supported, rationalists for a long time.

    For me, the final break came when he defended SBF. One of his defenses was that SBF was a nerd, so he couldn’t have had bad intentions. I share a lot of background with both SBF and Scott (we all did a lot of math contests in high school), but even I knew that it’s not remotely an excuse for stealing billions of dollars.

    I feel like a lot of his worldview centers around nerds vs everyone else. There’s this archetype of nerds being awkward, but well-intentioned and smart people who can change the world. They know better than everyone else on how to improve the world, so they should be given as much power as possible. I now realize that this cultural conception of a nerd actually has very little to do with how smart or well-intentioned you really are. The rationalists aren’t very good at technical matters (experts in an area can easily spot their errors), but they pull off this culture very well.

    Recently, I watched a talk by Scott, where he mentioned an anecdote when he was at OpenAI. Ilya Sutskever asked him to come up with a formal, mathematical definition to describe if “an AI loves humanity”. That actually pissed me off. I thought, can we even define if a human loves humanity? Yeah, surely all the literature, art, and music in the world is unnecessary now, we’ve got a definition right here!

    If there’s one thing I’ve learned from all this, it’s that actions speak louder than any number of 10,000 word blog posts. Perhaps the rationalists could stop their theorycrafting for once and, you know, look at what Sam Altman and friends are actually doing.


  • I know r/singularity is like shooting fish in a barrel but it really pissed me off seeing them misinterpret the significance of a result in matrix multiplication: https://old.reddit.com/r/singularity/comments/1knem3r/i_dont_think_people_realize_just_how_insane_the/

    Yeah, the record has stood for “FIFTY-SIX YEARS” if you don’t count all the times the record has been beaten since then. Indeed, “countless brilliant mathematicians and computer scientists have worked on this problem for over half a century without success” if you don’t count all the successes that have happened since then. The really annoying part about all this is that the original announcement didn’t have to lie: if you look at just 4x4 matrices, you could say there technically hasn’t been an improvement since Strassen’s algorithm. Wow! It’s really funny how these promptfans ignore all the enormous number of human achievements in an area when they decide to comment about how AI is totally gonna beat humans there.

    How much does this actually improve upon Strassen’s algorithm? The matrix multiplication exponent given by Strassen’s algorithm is log4(49) (i.e. log2(7)), and this result would improve it to log4(48). In other words, it improves from 2.81 to 2.79. Truly revolutionary, AGI is gonna make mathematicians obsolete now. Ignore the handy dandy Wikipedia chart which shows that this exponent was … beaten in 1979.

    I know far less about how matrix multiplication is done in practice, but from what I’ve seen, even Strassen’s algorithm isn’t useful in applications because memory locality and parallelism are far more important. This AlphaEvolve result would represent a far smaller improvement (and I hope you enjoy the pain of dealing with a 4x4 block matrix instead of 2x2). If anyone does have knowledge about how this works, I’d be interested to know.