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Discovering Cryptographic Weaknesses with Claude

anthropic.com

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Re: Discovering Cryptographic Weaknesses with Claude

#191

Post by ameliaquining »

vrighter wrote: post #189
ameliaquining wrote: post #184

Earlier quoted context omitted.

Are you saying we shouldn't trust cryptographers, because there'll be more demand for their services if we need to urgently migrate to post-quantum algorithms? That seems a very radically-skeptic perspective that makes it hard to know anything, and I doubt any serious engineer applies it in the general case. Or were you talking about someone else? In any rate, nobody (or at least none of the people I've heard from) i…

i don't trust google

The above post cites a number of people and organizations other than Google.

Re: Discovering Cryptographic Weaknesses with Claude

#192

Post by AndrewOMartin »

kmoser wrote: post #53
mmaunder wrote: post #15

“Each of the results cost roughly $100,000 in API cost to develop.” And “Over the course of a week, one Anthropic researcher worked together with Claude to develop the HAWK attack, and another researcher built a scaffold4 that allowed Claude to fully autonomously discover the AES attack.” Spending $100k in tokens in a week is an impressive feat even with massive parallelization. I suspect the TPS their internal folks…

Today's state-of-the-art AI systems are the equivalent of late 1970s personal computers: bulky and expensive, but wildly more powerful than what came before. And look what happened: tech improved by orders of magnitude, and eventually computers were tiny and cheap. I predict the same will happen with AI: certainly the latest and greatest will still command a steep price (yes, supercomputers are still a thing) but for…

1970s personal computers were "controlled" by the likes of Richard Stallman. 2020s AI systems are controlled by the likes of Sam Altman.

See the difference?

This is intentionally a wild and crude oversimplification, but I hope to raise at least one point against the notion that AI will be similarly democratized.

Re: Discovering Cryptographic Weaknesses with Claude

#193

Post by kmoser »

AndrewOMartin wrote: post #192
kmoser wrote: post #53

Earlier quoted context omitted.

Today's state-of-the-art AI systems are the equivalent of late 1970s personal computers: bulky and expensive, but wildly more powerful than what came before. And look what happened: tech improved by orders of magnitude, and eventually computers were tiny and cheap. I predict the same will happen with AI: certainly the latest and greatest will still command a steep price (yes, supercomputers are still a thing) but for…

1970s personal computers were "controlled" by the likes of Richard Stallman. 2020s AI systems are controlled by the likes of Sam Altman. See the difference? This is intentionally a wild and crude oversimplification, but I hope to raise at least one point against the notion that AI will be similarly democratized.

> 1970s personal computers were "controlled" by the likes of Richard Stallman.

Who are you talking about? Richard Stallman is all about allowing anybody to freely run their own software on their own hardware.

Re: Discovering Cryptographic Weaknesses with Claude

#194

Post by tedbradley »

petra wrote: post #152
tedbradley wrote: post #132

Earlier quoted context omitted.

With smarter models, Anthropic recommends laying off on giving it too much precise hand-holding, too. Early r/promptengineering had a bunch of the craziest prompts that usually did almost nothing or nothing at all. The subreddit turned into a place where every post was trying to sell some vibe-coded website "product." Context management is still important, though. If you get to a certain amount of context, things sta…

They probably took our skills and reuse them. That's why skills do not matter anymore.

Skills have use. They're just prepackaged prompts with a trigger condition. I was talking more like prompts that list 50 steps to follow while using GPT-4 or Opus 4.6 to program.

The way I see it, if you give too strict a sequence of steps to reach goal X, that's a double-edged sword. If your steps are actually a fantastic list of things to do to reach X, it likely won't hurt, and it might even help. HOWEVER, let's say you don't know every tiny detail about your codebase. The steps strategy might be like trying to force a square peg into a circle hole. If your steps are a really suboptimal strategy or even a failing one, that's going to derail the LLM. In most cases, unless you really know what you are doing and/or what you want, let the LLM have the power to try out strategies baked into it. It might surprise you with an algorithm or technique you don't even know about!

Re: Discovering Cryptographic Weaknesses with Claude

#195

Post by tedbradley »

matltc wrote: post #147
tedbradley wrote: post #132

Earlier quoted context omitted.

With smarter models, Anthropic recommends laying off on giving it too much precise hand-holding, too. Early r/promptengineering had a bunch of the craziest prompts that usually did almost nothing or nothing at all. The subreddit turned into a place where every post was trying to sell some vibe-coded website "product." Context management is still important, though. If you get to a certain amount of context, things sta…

Prompt engineering was deprecated around the time Opus-/Codex-class models dropped imo. Replaced by skills up until about opus 4.5/6 dropped. Pinned model to Opus 4.6 slug in ENV.ANTHROPIC_MODEL, disabled the adaptive thinking thing, and saw my skills start causing degradation Only ones I use today are for very specific quirks (eg wiredtiger/mongodb 8+ incompatible with ext4/Linux 6.19+ specifically causing segfaults…

Interesting. So you're using Sonnet 5 on low effort as the workhorse for most parts of your plan, unless perhaps there is a part of the plan you deem too complex for it? Then, maybe throw Opus 5 or even Fable 5 at it?

Have you considered using Luna on max effort for implementation? There was that recent news that they tuned its code and balancing and maybe some other stuff, dropping costs and allowing Luna to run for 20% of the API cost it had just two weeks ago. Now here's the rub: Have people with a subscription confirmed Luna max drains their usage way slower than before? With those rolling windows and the opaque "pricing" associated with them, an 80% cut to GPT-5.6 Luna might now translate into an 80% cut to using GPT-5.6 Luna with a sub.

Anway, with that news, I was curious if you've tried little Luna for implementation. On https://artificialanalysis.ai/, for its level of "intelligence," it is cheaper than even DeepSeek. I think they want people to switch over for that alluring price cut while also giving far more usage than Anthropic. Once people stay on their plan, they make most of their profits from those same users pulling out Sol.

Re: Discovering Cryptographic Weaknesses with Claude

#196

Post by tedbradley »

porridgeraisin wrote: post #33
_dwt wrote: post #22

I find that some of my friends and acquaintances have gotten obsessed with prompting style, "prompt engineering", which skills to use, which skills to build, "context engineering", and a billion other variations on "how to write smart things so the model does good". Friends, look at the prompts that Anthropic's own people are putting into the machine: > A few hours after the first message, we found that Claude was st…

To be fair > Importantly, this is just one of many (autonomous) sessions where Claude worked on discovering new ideas. Many sessions resulted in no new discoveries; other follow-up sessions improved on the insight developed in this one. This document was produced by having Claude rewrite the chain of thought to include more detail to make it easier to read.

Good point. So basically, they likely spent 1+ million USD letting Mythos run for hours upon hours, and in this one case, a query with sizable compute used, apparently US$100k at the end of it all, came up with something interesting. And that $1 million was just an example. What if they ran 40 such queries? That'd be $4 million bucks flushed down the toilet. Not exactly an amount people will pay for a 1/40 chance to see if an LLM can innovate. They'd rather pay teams of humans, say, $4 million in total, since they have a much better track record for the money spent.

Re: Discovering Cryptographic Weaknesses with Claude

#197

Post by pas »

QwenGlazer9000 wrote: post #106
pas wrote: post #95

Earlier quoted context omitted.

... what is understanding of mathematics anyway? if some AI result helps a mathematician to solve more problems I would say then that it gave them some understanding, but just as there are proofs that span hundreds of pages it's likely that soon proofs will be long Lean programs and studying them will be part of mathematics, just as studying Go played by AI. (see the open (Lean) label for Erdos problems https://maths…

https://davidbessis.substack.com/p/the-fall-of-the-theorem-e... This blog post talks in depth about what you're talking about. It may interest you. It even talks about the future where math proofs are just Lean programs, and why that won't necessarily be a good thing. It's worth a read, even if it's long AF.

I have complicated feelings regarding academia, and in general IMHO it's way past due to start focusing on quality instead of hype.

who was first to some kind of novelty? who cares. someone did something but no one can replicate it? intentionally wasting public money. fraud by any other name.

"science" wouldn't move slower if we would build more robust data generating processes.

of course, since usually it's hard to judge quality academia uses proxies. not to mention that the people who could usually are also live inside fancy glassware. and it would be a shame to rock the boat.

... but math is doubly special, because we accepted that it doesn't matter (until it does, but then it's called cryptography and logistics network optimization and high frequency trading, and machine learning), and how long a problem stays unsolved was quite a good proxy.

still, if AI solves the easy ones we can finally have fun with the hard ones!

Re: Discovering Cryptographic Weaknesses with Claude

#198

Post by porridgeraisin »

tedbradley wrote: post #196
porridgeraisin wrote: post #33

Earlier quoted context omitted.

To be fair > Importantly, this is just one of many (autonomous) sessions where Claude worked on discovering new ideas. Many sessions resulted in no new discoveries; other follow-up sessions improved on the insight developed in this one. This document was produced by having Claude rewrite the chain of thought to include more detail to make it easier to read.

Good point. So basically, they likely spent 1+ million USD letting Mythos run for hours upon hours, and in this one case, a query with sizable compute used, apparently US$100k at the end of it all, came up with something interesting. And that $1 million was just an example. What if they ran 40 such queries? That'd be $4 million bucks flushed down the toilet. Not exactly an amount people will pay for a 1/40 chance to…

Yes, see https://news.ycombinator.com/item?id=49161078

Re: Discovering Cryptographic Weaknesses with Claude

#199

Post by jhogervorst »

8note wrote: post #80
jhogervorst wrote: post #64

Earlier quoted context omitted.

> Can't you type faster than you speak? Doesn't your speaking inhibit your thinking? For me personally: no, I speak faster than I type; and speaking actually helps me get more ideas compared to typing. (Not sure if that’s due to having no typing speed barrier, or maybe because speaking activates different parts of the brain.) Once you get over the feeling of self-consciousness, it’s a great way. I even go on short wa…

do you perchance have no inner monologue? its a physical difference in how people think that would affect typing vs talking

Late reply — my Hacker News reading app doesn’t give alerts on replies.

You’re right, I don’t have an inner monologue.

Only when I think about words or text literally, like when formulating this reply, I ‘sense’ the words that I come up with. Though I don’t ‘hear’ them.

I also have aphantasia. I can’t mentally ‘see’ things when I imagine them. I can ‘sense’ them, just like the words I formulate. It’s as if I know the thing I imagine is there, but it’s behind a blackout curtain.

Interesting topics! How little we still know about our own brain. And how different our brains seem to work.

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