Some thoughts about Anthropic's new cryptanalysis results

ssupermatou about 4 hours ago 36 commentsRead Article on blog.cryptographyengineering.com

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Discussion (36 Comments)Read Original on HackerNews

simonw•about 2 hours ago

This is good:

> If you’re under the impression that these models are “glorified autocomplete” or that progress is slowing down, I need to urge you: stop thinking that. The models are very intelligent and capable, they are getting better at a fast clip. I can cite measurable and impressive progress over just the past five months on specific types of problem I’ve asked them to look at. [...]

> On the other hand: if you think that models are super-intelligent or that AGI is already here, you should also stop thinking that. Working with these tools is like swimming in a pond where the ground drops off sharply. One minute you’re wading comfortably and there’s support under your feet. Then suddenly you cross a specific line, and you’re back to swimming on your own.

dboreham•about 2 hours ago

I'm also getting irritated with the “glorified autocomplete” comments. Since nobody can post such comments and also use the tools I'm using, I'm wondering if the phenomenon is due to people only having experience with the free version of whatever it is they're trying to use?

dgellow•about 2 hours ago

The “glorified autocomplete” framing isn’t to take literally. It’s a way to remove the mystic and whole anthropomorphization of AI. It’s saying they aren’t sentient or entities we are interacting with, even if that’s how the output presents itself. Instead they are “just” stochastic models

simonw•about 2 hours ago

Some people use it to demystify, but a whole lot of people seem to be using it to dismiss the technology entirely.

Personally I like to remind people that these things are next-token predictors, but then emphasize how truly astonishing the results we can get out of sufficiently advanced next-token predictors are.

argee•about 1 hour ago

Exactly. They ARE "glorified autocomplete" in an ontological sense. That says nothing about capability or outcome. The people who come out swinging against that characterization usually ignore the whole ontological argument (which is...the entire point) and go after an outcome-based strawman.

cyanydeez•5 minutes ago

I like glorified copy/paste frankensteined with find/replace.

mostlylurks•32 minutes ago

The models themselves are indeed glorified autocomplete in terms of what they actually do (with things like agentic coding harnesses being required as a wrapper around them to make that internal autocomplete something more useful). Many people use this fact to critique LLMs, but many other common instances of people pointing out LLMs' apparent lack of intelligence actually come from people not understanding that the model is a glorified autocomplete underneath whatever interface people access them through, and the interface isn't providing the underlying model all the information they assume it would, making it seem less intelligent than it actually is.

simonw•about 2 hours ago

> both outputs of Claude Mythos, their (still) unreleased advanced model

That sentence gives the impression that Mythos might be released in the future. That's clearly not going to happen - it's already "released" in as much as selected, trusted partners can access it, and the rest of us get it in the form of Fable - which is Mythos but with filters that downgrade you if you try to use it for anything even remotely related to cybersecurity or biology.

(The other day Fable 5 downgraded me to Opus after I asked it to explain the difference between tusks and teeth.)

free_bip•about 2 hours ago

Genuine question here, why would you ask Fable to explain the difference between tusks and teeth? That's a task that can probably be handled by Haiku.

simonw•about 2 hours ago

It's the default when I pop open the Claude iPhone app, I usually don't bother to switch it.

john_strinlai•about 2 hours ago

>They [anthropic] appear to have just told it to get some results and then strapped its nose to the grindstone until it found some.

it is fun how well this works.

i cant find the link immediately (will look and edit with it), but somewhere in the "hello there the jacobian conjecture is false thanx" thread, someone brought up a different conjecture breakthrough where the prompts were basically just repeated "no, keep going" until a result was found.

edit: https://chatgpt.com/share/6a60b2eb-0b64-83ee-9c76-7931ca1de0...

i especially like "you should do a breakthrough". each prompt is less than ~20 words. makes me really question the whole "prompt engineering" stuff.

throwup238•about 2 hours ago

> i especially like "you should do a breakthrough". each prompt is less than ~20 words. makes me really question the whole "prompt engineering" stuff.

This is well past prompt engineering and into process engineering like six sigma. Just like in an early industrial revolution factory, we’re all still figuring out what works in the process of making stuff except this is so early that even simple things like “make this screw standardized” (or “no, keep going” in this case) is really high impact.

The degrees of freedom an LLM has is so large that we're going to be exploring their capabilities for decades, especially if they continue to get better. This is why IMO experts are always going to be better at LLMs in their field because they can force them LLM into processes (think prompt engineering -> CC dynamic workflows) that follow their work processes and get much better results out of them than “keep going.”

adamzenith•about 2 hours ago

In response to your edit, you should check out Terry tao's chat gpt logs about the recent Jacobian result. The models are smart enough to brute force some things, but can cut to the meat much faster with good prompting

john_strinlai•about 2 hours ago

i read his, too. his replies are indeed more directed, but also quite short, unstructured, and natural sounding. if i recall, maybe 1 or 2 of his prompts exceeded 50(ish) words.

in my head, the comparison is the multi-paragraph prompts (borderline essays) i would read in various communities on reddit and similar forums, that people (often self-proclaimed "prompt engineers") said were "required" to get good output. or some of the prompts ive read in various logs that are like a thousand words of setup.

even looking back at the first prompts i was sending when i started to use chatgpt were (in hindsight) crazy long and full of unnecessary guidance/caveats/"ignore xyz"/etc.

dist-epoch•about 2 hours ago

That second person stated that for many years they tried that particular graph problem on various AI models, starting with o1 and o3.

Its quite likely they now found the counterexample with a more serious prompt, and then for virality re-tried a few times with meme-prompts like "you should do a breakthrough", knowing that the model is capable of solving this particular one. Worst case the meme-prompts don't work and they share the real one they initially used.

john_strinlai•about 1 hour ago

>Its quite likely they now found the counterexample with a more serious prompt, and then for virality re-tried a few times with meme-prompts

i am not sure why this is "quite likely". it'd be pretty silly to get a mathematical breakthrough and then hide it for an undisclosed amount of time to get a few more likes on a tweet, when the impressive part is the breakthrough.

not saying your theory is impossible, but i think the simple answer is that the model is just smarter than o1 and o3.

and, in any case, the model ended up getting the result with the meme prompt and "keep going", which was what i find fun. just like how the crypto results were from prompts of, more or less, "keep going", and that's pretty damn cool.

dist-epoch•about 1 hour ago

You can open 10 tabs and prompt 10 times. We are talking about a few hours delay.

I agree with you that obviously no prompt engineering was needed just "solve this problem", but imagine it was you doing this problem with every model, wouldn't you have tested a new model with the best prompt you had from previous iterations, maybe with some partial previous results in it, exactly to maximize your probability for a mathematical breakthrough?

mkagenius•about 3 hours ago

I also just finished writing a note - https://mkagenius.substack.com/p/notes-on-mythos-breaking-ae...

https://news.ycombinator.com/item?id=49099977

throawayonthe•about 2 hours ago

> I asked Claude for its thoughts, and it doesn’t mince words: “what makes this genuinely interesting — and, frankly, a little embarrassing for the field — is that none of the ingredients are exotic.” The TL;DR is that someone just did a much more thorough job applying all of our known tools. In short: the sort of things that attack AIs are wonderful at.

did i just read two summaries/TLDRs (in a row) of the already-two-sentence summary right above?

Ar-Curunir•about 1 hour ago

There a constructive way to leave feedback you know