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Claude is good at assembling blocks, but still falls apart at creating them

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Re: Claude is good at assembling blocks, but still falls apart at creating them

#241

Post by utopiah »

utopiah wrote: post #240
computerex wrote: post #233

Earlier quoted context omitted.

How does it not address what you wrote?

If I understood correctly you are giving an example of a "success" of using the technology. So that's addressing that the technology is useful or not, powerful or not, but it does not address what it actually does (maybe somebody in ChatGPT is a gnome that solved it, I'm just being provocative here to make the point) or more important that it does something it couldn't do a year ago or 5 years ago because how it is d…

Also something that makes the whole process very hard to verify is what I tried to address in a much older comment : whenever LLMs are used (regardless of the input dataset) by someone who is an expert in the domain (rather than an novice) how can one evaluate what's been done by whom or what? Sure again there can be a positive result, e.g a solution to a problem until now unsolved, what does it say about the tool itself versus a user who is, by definition if they are an expert, up to date on the state of thew art?

Re: Claude is good at assembling blocks, but still falls apart at creating them

#242

Post by utopiah »

utopiah wrote: post #240
computerex wrote: post #233

Earlier quoted context omitted.

How does it not address what you wrote?

If I understood correctly you are giving an example of a "success" of using the technology. So that's addressing that the technology is useful or not, powerful or not, but it does not address what it actually does (maybe somebody in ChatGPT is a gnome that solved it, I'm just being provocative here to make the point) or more important that it does something it couldn't do a year ago or 5 years ago because how it is d…

Also the very fact that https://github.com/teorth/erdosproblems/wiki/AI-contribution... exist totally change the landscape. Because it's public it's safe to assume it's part of the input dataset so from now on, how does one evaluate the pace of progress, in particular for non open source models?

Re: Claude is good at assembling blocks, but still falls apart at creating them

#243

Post by utopiah »

bakkoting wrote: post #229
patagurbon wrote: post #192

Earlier quoted context omitted.

That Erdos problem solution is believed by quite a few to be a previous result found in the literature, just used in a slightly different way. It also seems not a lack of progress but simply no one cared to give it a go. That’s a really fantastic capability, but not super surprising.

You're thinking of a previous report from a month ago, #897 or #481, or the one from two weeks ago, #728. There's a new one from a week ago, #205, which is genuinely novel, although it is still a relatively "shallow" result. Terence Tao maintains a list [1] of AI attempts (successful and otherwise). #205 is currently the only success in section 1, the "full solution for which subsequent literature review did not find…

Thanks for the wiki link, very interesting, in particular

- the long tail aspect of the problem space ; 'a "long tail" of under-explored problems at the other, many of which are "low hanging fruit" that are very suitable for being attacked by current AI tools'

- the expertise requirement, literature review but also 'Do I understand what the key ideas of the solution are, and how the hypotheses are utilized to reach the conclusion?' so basically one must already be an expert (or able to become one) to actually use this kind of tooling

and finally the outcomes which taking into consider the previous 2 points makes it very different from what most people would assume as "AI contributions".

Re: Claude is good at assembling blocks, but still falls apart at creating them

#244

Post by Havoc »

HarHarVeryFunny wrote: post #239
Havoc wrote: post #230

Earlier quoted context omitted.

Certainly there is space for designs a LLM can't come up with, but lets be real senior developers are not cranking out never seen before novel architectures routinely any more than physicists are coming up with never thought of theories that work weekly. It's largely the same patterns & principles applied in a tailored manner to the problem at hand, which LLMs can...with mixed success...do. >human parity Impact is no…

> Certainly there is space for designs a LLM can't come up with, but lets be real senior developers are not cranking out never seen before novel architectures routinely any more than physicists are coming up with never thought of theories that work weekly. True, but I didn't mean to focus on creativity, just the nature of what can be learned when all you have to learn from is artifacts of reasoning (code), not the un…

re reasoning traces - not sure frankly. I get what you're saying in that there is only so much advanced thinking you can learn from just scraping github code, and it certainly seems to be the latest craze in getting a couple extra % on benchmarks but I'm not entirely convinced it is necessary per se. Feels like an human-emulation crutch to me rather than a necessary ingredient to machines performing a task well.

For example I could see some sort of self-play style RL working. Which architecture? Try them all in a sandbox and see. Humans need to trial & error learning as you say. So why not here too? Seems to have worked for alphago which arguably also contains components of abstract high level strategy.

>Jevons paradox

I can see it for tokens and possibly software too, but rather skeptical of it in job market context. It doesn't seem to have happened for the knowledge work AI already killed (e.g. translation or say copy writing). More (slop) stuff is being produced but it didn't translate into a hiring frenzy of copy writers. Possible that SWE is somehow different via network effects or something but I've not heard a strong argument for it yet.

>It's also possible that human-replacement AGI is harder to achieve than widely thought.

Yeah I think the current paradigm isn't gonna get us there at all. Even if you 10x GPT5 it still seems to miss some sort of spark that a 5 year old has but GPT doesn't. It can do PHD level work but qualitatively there is something missing there about that "intelligence".

Interesting times ahead for better or worse

Re: Claude is good at assembling blocks, but still falls apart at creating them

#245

Post by lordnacho »

imiric wrote: post #73
lordnacho wrote: post #64

By and large, I agree with the article. Claude is great and fast at doing low level dev work. Getting the syntax right in some complicated mechanism, executing an edit-execute-readlog loop, making multi file edits. This is exactly why I love it. It's smart enough to do my donkey work. I've revisited the idea that typing speed doesn't matter for programmers. I think it's still an odd thing to judge a candidate on, but…

> Being able to type quickly and accurately reduces LLMs can generate code quickly. But there's no guarantee that it's syntactically, let alone semantically, accurate. > I feel that I'm learning faster because I'm not tripping over silly little things. I'm curious: what have you actually learned from using LLMs to generate code for you? My experience is completely the opposite. I learn nothing from running generated…

> I'm curious: what have you actually learned from using LLMs to generate code for you?

I learn whether my design works. Some of the things I plan would take hours to type out and test. Now I can just ask the LLM, it throws out a working, compiling solution, and I can test that without spending my waking hours on silly things. I can just glance at the code and see that it's right or wrong.

If there are internal contradictions in the design, I find that out as well.

Re: Claude is good at assembling blocks, but still falls apart at creating them

#246

Post by nosianu »

TeMPOraL wrote: post #188
nosianu wrote: post #187

Earlier quoted context omitted.

Humans are trained on the real world. With real world sensors and the ability to act on their world. A baby starts with training hearing, touching (lots of that), smelling, tasting, etc. Abstract stuff comes waaayyyyy later. LLMs are trained on our intercepted communication - and even then only the formal part that uses words. When a human forms sentences it is from a deep model of the real world. Okay, people are al…

All true, but note I didn't make any claims on internal mechanics of LLMs here - only on the observable, external ones, and the nature of the training process. Do consider however that even the "formal part that uses words" of human communication, i.e. language, is strongly correlated with our experience of the real world. Things people write aren't arbitrary. Languages aren't arbitrary. The words we use, their struc…

> but note I didn't make any claims on internal mechanics of LLMs here

Great - neither did I!

Not a single word about any internals anywhere in sight in my comment!!

Re: Claude is good at assembling blocks, but still falls apart at creating them

#247

Post by johnfn »

filoeleven wrote: post #147
nextaccountic wrote: post #131

Earlier quoted context omitted.

Then you apply LLMs in domains where things can be checked Indeed I expect to see a huge push into formally verified software just because sound mathematical proofs provide an excellent verifier to put into a LLM hardness. Just see how Aristotle has been successful at math, and it could be applied to coding too Maybe Lean will become the new Python https://harmonic.fun/news#blog-post-verina-bench-sota

"LLMs reliably fail at abstraction." "This limitation will go away soon." "Hallucinations haven't." "I found a workaround for that." "That doesn't work for most things." "Then don't use LLMs for most things."

    "Autocomplete is great!"
    "It doesn't work in bash"
    "Then don't use it in bash."
I don't see what's wrong with this argument, and I certainly don't see it as a proof that the particular technology is actually useless, as you seem to be suggesting.

Re: Claude is good at assembling blocks, but still falls apart at creating them

#248

Post by joshcsimmons »

eleventen wrote: post #149
joshcsimmons wrote: post #57

IDK I've been using opus 4.5 to create a UI library and it's been doing pretty well: https://simsies.xyz/ (still early days) Granted it was building ontop of tailwind (shifting over to radix after the layoff news). Begs the question? What is a lego?

FYI the cursor animation runs before the font loads if the font isn’t ready yet.

Thank you - I’ve been working on this since you commented it. It’s cached so I never saw it on my end

Re: Claude is good at assembling blocks, but still falls apart at creating them

#249

Post by joshcsimmons »

dehugger wrote: post #63
joshcsimmons wrote: post #57

IDK I've been using opus 4.5 to create a UI library and it's been doing pretty well: https://simsies.xyz/ (still early days) Granted it was building ontop of tailwind (shifting over to radix after the layoff news). Begs the question? What is a lego?

your github repo was highly entertaining. thanks for make my day a bit brighter:)

Thanks dude
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