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johndhi 9 hours ago

I'd be curious to see whether these models can create new forms of unbreakable encryption themselves!

LPisGood 9 hours ago | parent | next [-]

Private key cryptography is essentially unbroken by these models.

kragen 7 hours ago | parent | next [-]

Normally "private-key cryptography" is the antonym of "public-key cryptography", which is to say, conventional symmetric-key cryptography such as AES or Enigma. That's what "private-key cryptography" redirects to on Wikipedia. This article is about Astra breaking a message encrypted with a private-key cryptographic algorithm, but one that was already known to be weak. I'm guessing that if you had messages encrypted with weak public-key algorithms it could break those too.

dgellow 9 hours ago | parent | prev [-]

But they said new forms, I think that implied not the ones humans already discovered/designed

LPisGood 9 hours ago | parent [-]

I see what you’re saying. It is generally harder to build a crypto system than to break one so I would find it hard to see potential from the design end before progress on the attack end.

trixn86 7 hours ago | parent | next [-]

> It is generally harder to build a crypto system than to break one

It was harder to design Symmetric Encryption using e.g. AES-256 than to break it? As far as I know it's design is pretty straight-forward but there is no known way to break it even with all compute of the planet at your disposal (excluding trivial ways like exposing the key).

LPisGood 6 hours ago | parent [-]

Yes, it was. An attack only needs to work one way, but an encryption standard must resist all attacks.

There are many examples of would be crypto algorithms that died on the vine because an attack was found. It is often recommended for beginners to study breaking cryptographic algorithms long before they attempt to create them.

trixn86 2 hours ago | parent [-]

It didn't take 25 years to come up with Symmetric Encryption and AES but even though people try extensively to break it for the last 25 years no-one has come even close to anything that is not brute force (which is practically impossible even assuming very generous computing resources). So at least in that case coming up with the encryption seems to be a very solvable problem but breaking it seems close to impossible.

ijustlovemath 8 hours ago | parent | prev | next [-]

Building a crypto system has so many footguns, I'd be amazed if it could build one that stands up to attack

dgellow 7 hours ago | parent [-]

I think it’s all about the harness. If someone can find a way to create an iterative loop, with a good validator, I wouldn’t be too surprised if an LLM can end up with a solution. So far that’s how pretty much all problems have been solved by LLMs. That’s a very big if though!

darkwater 8 hours ago | parent | prev [-]

Isn't the other way round? It does not mean that breaking one is easy, but it does mean that writing one that's unbreakable it's very, very, very difficult.

LPisGood 8 hours ago | parent [-]

Yes it is; that’s what I was thinking when I started to comment but somehow I ended up reversing course. Comment is appropriately edited now.

joelthelion 9 hours ago | parent | prev | next [-]

They seem to be better at solving concrete problems than designing new things (at least for now)

yrjrjjrjjtjjr 9 hours ago | parent | next [-]

It's easier to evaluate certainly. Did it solve the problem? Yes/No

When you design a new thing it will have a dozen drawbacks and a dozen and one benefits. If people then have a bias that everything ai is bad, the signal won't be strong enough to convince.

dgellow 9 hours ago | parent | prev | next [-]

I believe an LLM can solve pretty much any problem for which we can define a fast iterative loop and for which we have reliable tools to automatically verify the correctness of a result. That’s how they are able to solve some math problems, and how they are able to generate working code. Then it’s a question of how much you have to pay for the model to explore the space of solutions in a reasonable timeframe

_superposition_ 9 hours ago | parent | prev | next [-]

They are only good at brute forcing stastically likely solutions.

api 9 hours ago | parent | prev [-]

In math a lot of the spectacular results have been made by finding a counterexample or worming their way toward a proof that is very well defined.

There's some debate over to what degree current generation AI can be creative at all, or whether it can only crawl around its latent space and explore within constraints. One might ask: were all the solutions to all the math problems AIs have solved already "there" latent in the training data and just hadn't been spotted by humans and put together?

But then... isn't everything latent in our training data if training data is "all observations made about the universe?"

But then... what even is creativity? That gets into philosophy and metaphysics. Creativity, like consciousness and sentience and self-awareness, is not a rigorously well defined concept. So to a degree we don't even know how to ask the question of whether these things are creative.

This gets interesting.

One of the things I love about AI is the glittering Pandora's box of philosophical questions it poses.

Another one I love: if LLMs and their relatives are not, in fact, sentient or self-aware or alive in any way whatsoever (which I suspect is true given how they work), then it means intelligence and consciousness are unrelated phenomena. I'm pretty sure every animal and maybe even every living things has consciousness in some form, but my pet bunny rabbits definitely can't write code. LLMs can write code, but I don't think they experience existence or have volition.

IMO we have always implicitly just assumed some kind of connection between intelligence and consciousness because we have both. It was just an assumption. It's probably a false one.

I suspect (a hypothesis) that consciousness is a property of life and is probably emergent from life's intimate relationship to thermodynamics and the arrow of time. Life has also evolved intelligence because it's useful to satisfy its implicit survival goal function, but the two are unrelated. Intelligence is just an adaptation.

pixl97 8 hours ago | parent | next [-]

Yea, when you start digging into intelligence/learning/creativity/language you realize that you're talking about more information on these topics than a human could ever learn in their lifetime, and you learn just how much we don't know about ourselves and these processes.

Whenever I hear "AI can never" I know I can disregard them as an unserious person when it comes to anything around AI, learning, or philosophy.

BubbleRings 7 hours ago | parent | prev [-]

I think of the extent of human knowledge as a circle or cloud shape, and true expert thinking happens just inside the edge. And creative thinking that leads to knowledge breakthroughs happen when you are thinking in that edge area, but also make a connection way around the circle to some other location. And my guess is there’s absolutely no reason why AI can’t learn to do that too.

xnx 9 hours ago | parent | prev [-]

Careful what you wish for. The swarm will probably use it to communicate.

sfn42 7 hours ago | parent [-]

We already have a plethora of cryptographic algorithms that literally anyone can use to send messages nobody can read with current technology, unless of course they have the key. You're using at least one of them right now to read this website.