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Some thoughts about Anthropic's new cryptanalysis results

blog.cryptographyengineering.com

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Re: Some thoughts about Anthropic's new cryptanalysis results

#21

Post by john_strinlai »

dist-epoch wrote: post #19
john_strinlai wrote: post #3

> 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, ke…

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…

>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.

Re: Some thoughts about Anthropic's new cryptanalysis results

#22

Post by simonw »

ameliaquining wrote: post #18
simonw wrote: post #16

Earlier quoted context omitted.

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.

I'm curious, what are you hoping to convey by reminding people that LLMs are next-token predictors? They are, of course, but most people without an AI background won't fully understand what that means, so I assume you're using it at least partly as a proxy for something else.

I think understanding how this stuff works is really important. For technical people it gives them a useful starting point for understanding it all. For less technical people it's crucial to help them understand that it's not some weird new magical science-fiction AI - it's still computer programs that turn text into numbers and do stuff with the numbers and turn those back into text.

It's harder to believe something is conscious or threatening to achieve word domination once you understand that it's a machine that statistically figures out which word should come next.

Re: Some thoughts about Anthropic's new cryptanalysis results

#23

Post by dist-epoch »

john_strinlai wrote: post #21
dist-epoch wrote: post #19

Earlier quoted context omitted.

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…

> 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 thi…

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?

Re: Some thoughts about Anthropic's new cryptanalysis results

#24

Post by dgellow »

simonw wrote: post #22
ameliaquining wrote: post #18

Earlier quoted context omitted.

I'm curious, what are you hoping to convey by reminding people that LLMs are next-token predictors? They are, of course, but most people without an AI background won't fully understand what that means, so I assume you're using it at least partly as a proxy for something else.

I think understanding how this stuff works is really important. For technical people it gives them a useful starting point for understanding it all. For less technical people it's crucial to help them understand that it's not some weird new magical science-fiction AI - it's still computer programs that turn text into numbers and do stuff with the numbers and turn those back into text. It's harder to believe something…

While you’re active in this thread, I just want to say thank you for all your writing, you’re such a reliable source of sanity in that crazy new world :)

Re: Some thoughts about Anthropic's new cryptanalysis results

#25

Post by wren6991 »

simonw wrote: post #16
dgellow wrote: post #14

Earlier quoted context omitted.

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

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.

The "next-token predictor" framing is also a bit shaky. It's an accurate description of pre-training, where next-token prediction is a useful learning objective to force the model to learn higher-level representations. It's wildly misleading for a model put through an RL post-training campaign. The tokens it "predicts" aren't sampled from any naturally occurring distribution; the model's output is the result of an optimisation process that rewarded behaviour that was useful, and that's fundamentally different.

Re: Some thoughts about Anthropic's new cryptanalysis results

#26

Post by ameliaquining »

simonw wrote: post #22
ameliaquining wrote: post #18

Earlier quoted context omitted.

I'm curious, what are you hoping to convey by reminding people that LLMs are next-token predictors? They are, of course, but most people without an AI background won't fully understand what that means, so I assume you're using it at least partly as a proxy for something else.

I think understanding how this stuff works is really important. For technical people it gives them a useful starting point for understanding it all. For less technical people it's crucial to help them understand that it's not some weird new magical science-fiction AI - it's still computer programs that turn text into numbers and do stuff with the numbers and turn those back into text. It's harder to believe something…

I don't think the next-token-predictor thing should increase anyone's confidence that LLMs aren't conscious or can't escape the control of their operators. A very closely analogous argument would "prove" that humans aren't conscious or can't do [insert task here] either. (No, I'm not saying that any of this is true of today's LLMs, I'm saying this particular argument doesn't work.)

I recommend this explanation: https://www.astralcodexten.com/p/next-token-predictor-is-an-...

Re: Some thoughts about Anthropic's new cryptanalysis results

#27

Post by simonw »

wren6991 wrote: post #25
simonw wrote: post #16

Earlier quoted context omitted.

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.

The "next-token predictor" framing is also a bit shaky. It's an accurate description of pre-training, where next-token prediction is a useful learning objective to force the model to learn higher-level representations. It's wildly misleading for a model put through an RL post-training campaign. The tokens it "predicts" aren't sampled from any naturally occurring distribution; the model's output is the result of an op…

Right, but it's still useful to think of these models in terms of next-tokens because it helps explain that they look at every token that came before and use that to put out the next one.

You can get into RL as part of explaining why it's so unnervingly good at picking a next token.

Re: Some thoughts about Anthropic's new cryptanalysis results

#28

Post by argee »

dgellow wrote: post #14
dboreham wrote: post #12

Earlier quoted context omitted.

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?

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

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.

Re: Some thoughts about Anthropic's new cryptanalysis results

#29

Post by [deleted] »

simonw wrote: post #22
ameliaquining wrote: post #18

Earlier quoted context omitted.

I'm curious, what are you hoping to convey by reminding people that LLMs are next-token predictors? They are, of course, but most people without an AI background won't fully understand what that means, so I assume you're using it at least partly as a proxy for something else.

I think understanding how this stuff works is really important. For technical people it gives them a useful starting point for understanding it all. For less technical people it's crucial to help them understand that it's not some weird new magical science-fiction AI - it's still computer programs that turn text into numbers and do stuff with the numbers and turn those back into text. It's harder to believe something…

[deleted]

Re: Some thoughts about Anthropic's new cryptanalysis results

#30

Post by dgellow »

ameliaquining wrote: post #26
simonw wrote: post #22

Earlier quoted context omitted.

I think understanding how this stuff works is really important. For technical people it gives them a useful starting point for understanding it all. For less technical people it's crucial to help them understand that it's not some weird new magical science-fiction AI - it's still computer programs that turn text into numbers and do stuff with the numbers and turn those back into text. It's harder to believe something…

I don't think the next-token-predictor thing should increase anyone's confidence that LLMs aren't conscious or can't escape the control of their operators. A very closely analogous argument would "prove" that humans aren't conscious or can't do [insert task here] either. (No, I'm not saying that any of this is true of today's LLMs, I'm saying this particular argument doesn't work.) I recommend this explanation: https…

You can say that for any argument regarding consciousness, because we don’t have an actual, all encompassing definition of what consciousness is. In general I don’t think comparison with humans makes much sense, we should be able to discuss LLMs without always falling back to “but what about humans” (sorry for the caricature)
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