mistercow

I suspect they used an underpowered model, or did it a while back. I would be surprised to see 6.1 Sol or Astra produce those bugs, even one-shotting. Instead, I'd just expect it to have broader product issues rather than out and out bugs.

I've wondered for a long time why ear clipping + optimizations has won on triangulation over stuff like Seidel's trapezoidal method, which has O(nlog*n) time complexity and handles holes naturally. I know big-O isn't everything, but that's essentially linear versus quadratic, and it seems like we care about triangulating more and more complex polygons as time goes on.

Is it just a triangle quality thing? Does Seidel lead to too many hard to deal with slivers?

I think it's basically an alignment problem. LLMs tend to think it's better to just do something small and bespoke than to just pull a mature library and use it correctly, which, to be clear, they are perfectly capable of doing.

And this is in part a reflection of our own bad preferences. This is what always annoyed me most about the left-pad Discourse a decade (oh god, a Decade™) ago; "why do you need a library for something so simple in the first place!?" people would scoff. And of course the answer is that even the reference class of left-pad-like problems includes a bunch of examples where the problem has bizarre and sticky edge cases you'd never consider, so in general, "just pop in a popular and well tested library" is actually a pretty good policy (assuming your package repository doesn't allow anything really silly like deleting entire packages and breaking everything downstream).

Of course charting is more obviously complicated, but again, it might seem fairly simple if all you're thinking about is one kind of chart in one style with limited settings. The difference is that for a human coder, "just whip up some chart code" is enough of a pain in the ass that they'll reach for a library by default, whereas a coding agent can just spit something out which mostly works in a few seconds.

> when it can't be derived from the training data

This sounds like a goalpost on wheels. Can you define clearly where your stake in the ground is?

It's not a dichotomy, though. I loved coding for the sake of it. I found it relaxing, meditative, and I was very good at it. I also like building things where coding is a necessary step.

And while I don't go all in on the notion of revealed preferences, a few facts stand out to me:

1. Nothing is actually stopping me from writing code by hand for fun, but I don't

2. There is no practical reason to manually write homebrew SNES games in assembly language, but some people do

3. I still have no deficit of fun problems to dig into, to sit and ponder, and then experiment with. They just aren't coding problems, and I have far more powerful tools to help me navigate prior art, test out hypotheses, and so on.

I think this is really selling the severity of "SHA-1 is a Shambles" short. The author distinguishes between second preimage and collisions, but Shambles is a chosen-prefix collision, so it's sort of in between the two ends of the spectrum he explains.

The difference here is between me being able to send you a benign file and then swap out a safe file (the scenario the author describes) and me being able to swap out your own familiar, benign file except this time it has malicious content at the end (along with a bunch of garbage).

That second scenario is obviously much more dangerous from the perspective of human review and noticing that something is wrong. If you have a large, rarely changing file already, then content silently smuggled onto the end of it could stay undetected for a long time.

(In practice, it's not that simple; you'd have to actually figure out how to make multiple pieces line up with chosen prefix collisions, and I haven't worked through how you would do it. Maybe it's impossible without further weaknesses. But that guarantee is feeling pretty threadbare.)

Anyway, this doesn't matter because git switched to sha-1dc back in 2017, and afaik, this addresses the shattered/shambles problems. I find it odd that this isn't the point the author focuses on; instead, the only mention of sha-1dc is in a footnote saying that it could be replaced with his proposal.

And sure, maybe that's true, but why isn't that the entire argument of the article then?

Feynman for sure could have. In fact, I think he sort of did, although I'm not sure he meant to. Multiple generations of nerds now have taken books of his anecdotes varying in plausibility and obvious exaggeration as some sort of weird physics cult of personality gospel. But I don't think he was really setting out to curate his legacy so much as he was a good storyteller and he liked to entertain.

But could he have conned people on purpose? Absolutely.

I think it was on qwen 3.5 9B or thereabouts that I saw a ~30% decode rate improvement on my M2 Mac vs MLX. That’s probably the best I’ve gotten.

Keep in mind though that this is also sometimes use case dependent. Off the shelf implementations are generally pretty good overall, but can have pathological behavior on specific workload shapes you care about. So do this as a somewhat later optimization, and particularly when you see performance characteristics that don’t seem to make any sense.

It's been pretty ad hoc, but my prompts are nothing special. Things I generally do:

1. Top end model on high/xhigh thinking (last time I did it it was Sol xhigh I think)

2. Make sure it creates some representative fixtures of different sizes and sets up a good testing, profiling and benchmarking loop that doesn't require my input.

3. Make sure it has access to reference implementation code

Edit: Oh and one obvious pitfall that for some reason I still have to remind even smart models of from time to time: make sure it knows not to try to parallelize its benchmark runs. I've occasionally had an agent struggle to figure out absolutely nonsensical data because it tried to run multiple tests on the same compute hardware simultaneously.

On the SDK front, you tried just having an agent reimplement the model you're interested in and just use the weights? I've taken to treating off the shelf implementations as reference implementations anyway, because I can often squeeze out significantly better performance for my configuration and use case by having Codex hammer at it for a few hours.

I’m not sure how you can really make either statement work anymore. Now that smaller models are actually broadly usable, “behindness” is no longer a scalar and at the tails, where no open lab seems to be trying to compete at the >10T scale and no closed lab seems to care about <400B anymore, it’s just apples to oranges. It’s like talking about whether Qualcomm is “behind” Nvidia.

Tom7 doesn’t know the meaning of the phrase “low effort”.

> I'm fairly certain this will defeat 99.9% of malicious users, many of whom won't even know it exists until someone points out it's missing.

Everyone realizing that photos don't prove anything would defeat 100% of malicious users. I don't understand what people incorrectly trusting photos is supposed to achieve at this point, in your view.

Aside from the fact that this was obviously never viable and the entire problem is clearly unsolvable if you sit down and really probe it for fifteen minutes, what I find most frustrating about this is that the false promise of preserving photos as reliable evidence is actively harmful.

You will not build a perfect system, or even something near perfect. The best you're going to do is make it so that it's hard to casually present AI photos as real, leaving only the cases where it really matters. In the "best" case, you've just made the public more trusting of photos in general, so that when there's actual money or power on the line that makes jumping through the hoops to fake authenticity worth it, the public is more susceptible.

The best outcome at this point is for everyone to get on the same page that photos have roughly the same probative value now as drawings. Poorly thought out snake oil efforts to prove authenticity are only going to delay that.

Most old books that are rare and unpreserved are so because their value is marginal, so nobody has bothered to collect and preserve them.

But where did you hear that they’re buying “all copies”? And to what end?