TechTakes

fuck yeah! congrats!

Felicitations!

("A job," Blake thinks. "I need to find one of those.")

"posting from the slop hole" is probably the best description possible for this, brb stealing

yeah it's bad

otoh awareness I think is spreading

swedish public broadcasting has regular "spot the fake" pieces on their website

I think giving a sensationalist bit of news 6 hours to "mature" is a good idea before amplifying.

There's only one thing that's advertised as not-waterproof that I'll risk using underwater and that's Casio wristwatches. "Water resist" is a huge understatement for them the things are indestructable.

(This comment sponsored by Casio)

What a fool. A proper scientist would test for a bigger N. Drop your phone in the pool again Why.

how… what… how… why… why would you think…

Usually, you wake up on a lifeless beach that’s adorned with some sort of abandoned marble temple. It’s supposed to be beautiful, but instead it’s really sad. Almost unbearably sad. So much so that you want to get away from it. So you crawl downward into these vents going below the horrible temple, and suddenly it’s like you’re moving through the innards of an incomprehensible machine that’s thudding away, thud, thud, thud. And as you get deeper, the metal sidings are carved with scrawled ominous curses and slurs directed toward you, and you hear the voices, louder than before, and you somehow know these people are in pain because of you. It keeps getting colder. Color drains from the world. And you see the crowd through the slats of the vents: pale and emaciated men, women, and children from centuries to come, all of them pressed together for warmth in some sort of unending cavern. What clothes they have are torn and ragged. Before you know it, their dirty hands and dirty fingernails lurch through the grates, and they’re reaching for you, tearing at your shirt, moaning terrible things about their suffering and how you made it happen, you made it, and you need to stop this now, now, now. And next they’re ripping you apart, limb from limb, and you are joining them in the gray dimness forever.

yeah, the current situation in Europe is like: "As EU citizens, we should break free of our dependency on US Big Tech like the Torment Nexus. That's why my company is advancing our fully sovereign solution, the Agony Core! Europe-owned, GDPR-compliant, Frontex-approved scalable Torment-as-a-Service, at competitive prices with TN-based deployments!"

Baldur Bjarnason's essay remains evergreen.

Consider homeopathy. You might hear a friend talk about “water memory”, citing all sorts of scientific-sounding evidence. So, the next time you have a cold you try it.

And you feel better. It even feels like you got better faster, although you can’t prove it because you generally don’t document these things down to the hour.

“Maybe there is something to it.”

Something seemingly working is not evidence of it working.

• Were you doing something else at the time which might have helped your body fight the cold?

• Would your recovery have been any different had you not taken the homeopathic “remedy”?

• Did your choosing of homeopathy over established medicine expose you to risks you weren’t aware of?

Even when looking at Knuth's account of what happened, you can already tell that the AI is receiving far more credit than what it actually did. There is something about a nondeterministic slot machine that makes it feel far more miraculous when it succeeds, while reliable tools that always do their job are boring and stupid. The downsides of the slot machine never register in comparison to the rewards.

I feel like math research is particularly susceptible to this, because it is the default that almost all of one's attempts do not succeed. So what if most of the AI's attempts do not succeed? But if it is to be evaluated as a tool, we have to check if the benefits outweigh the costs. Did it give me more productive ideas, or did it actually waste more of my time leading me down blind alleys? More importantly, is the cognitive decline caused by relying on slot machines going to destroy my progress in the long term? I don't think anyone is going to do proper experiments for this in math research, but we have already seen this story play out in software. So many people were impressed by superficial performances, and now we are seeing the dumpster fire of bloat, bugs, and security holes. No, I don't think I want that.

And then there is the narrative of not evaluating AI as an objective tool based on what it can actually do, but instead as a tidal wave of Unending Progress that will one day sweep away those elitists with actual skills. This is where the AI hype comes from, and why people avoid, say, comparing AI with Mathematica. To them I say good luck. We have dumped hundreds of billions of dollars into this, and there are only so many more hundreds of billions of dollars left. Were these small positive results (and significant negatives in places like software) worth hundreds of billions of dollars, or perhaps were there better things that these resources could have been used for?

Even in Knuth's account it sounds like the LLM contribution was less in solving the problem and more in throwing out random BS that looked vaguely like different techniques were being applied until it spat out something that Knuth and his collaborator were able to recognize as a promising avenue for actual work.

His bud Filip Stappers rolled in to help solve an open digraph problem Knuth was working on. Stappers fed the decomposition problem to Claude Opus 4.6 cold. Claude ran 31 explorations over about an hour: brute force (too slow), serpentine patterns, fiber decompositions, simulated annealing. At exploration 25 it told itself “SA can find solutions but cannot give a general construction. Need pure math.” At exploration 30 it noticed a structural pattern in an earlier solution. Exploration 31 produced a working construction.

I am not a mathematician or computer scientist and so will not claim to know exactly what this is describing and how it compares to the normal process for investigating this kind of problem. However, the fact that it produced 4 approaches over 31 attempts seems more consistent with randomly throwing out something that looks like a solution rather than actually thinking through the process of each one. In a creative exploration like this where you expect most approaches to be dead ends rather than produce a working structure maybe the LLM is providing something valuable by generating vaguely work-shaped outputs that can inspire an actual mind to create the actual answer.

Filip had to restart the session after random errors, had to keep reminding Claude to document its progress. The solution only covers one type of solution, when Claude tried to continue another way, it “seemed to get stuck” and eventually couldn’t run its own programs correctly.

The idea that it's ultimately spitting out random answer-shaped nonsense also follows from the amount of babysitting that was required from Filip to keep it actually producing anything useful. I don't doubt that it's more efficient than I would be at producing random sequences of work-shaped slop and redirecting or retrying in response to a new "please actually do this" prompt, but of the two of us only one is demonstrating actual intelligence and moving towards being able to work independently. Compared to an undergrad or myself I don't doubt that Claude has a faster iteration time for each of those attempts, but that's not even in the same zip code as actually thinking through the problem, and if anything serves as a strong counterexample to the doomer critihype about the expanding capabilities of these systems. This kind of high-level academic work may be a case where this kind of random slop is actually useful, but that's an incredibly niche area and does not do nearly as much as Knuth seems to think it does in terms of justifying the incredible cost of these systems. If anything the narrative that "AI solved the problem" is giving Anthropic credit for the work that Knuth and Stapprrs were putting into actually sifting through the stream of slop identifying anything useful. Maybe babysitting the slop sluice is more satisfying or faster than going down every blind alley on your own, but you're still the one sitting in the river with a pan, and pretending the river is somehow pulling the gold out of itself is just damn foolish.

ooh gooods nooo now all the Claude slurpers are going to refer to this forever as definitive proof of how legitimately useful LLMs have got, it "solved" a math problem for Donald Knuth! :<

oh hey I remember reading that Donald Knuth paper earlier today

We really need to work harder at poisoning the training data for math problems.

If you found this post helpful, follow me for more content like this.

So they expect more cases of data being lost like this?

Class action lawsuits by employees against employers that mandate AI tools when?