LLMs won't break symmetric crypto
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LLMs won't break symmetric crypto
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Re: LLMs won't break symmetric crypto
#2Re: LLMs won't break symmetric crypto
#3Re: LLMs won't break symmetric crypto
#4A next-word-in-the-sentence prediction engine can’t predict the factor of two insanely large prime numbers… tell me more
Re: LLMs won't break symmetric crypto
#5Re: LLMs won't break symmetric crypto
#6A next-word-in-the-sentence prediction engine can’t predict the factor of two insanely large prime numbers… tell me more
RSA is asymmetric crypto. This article is about symmetric cryptography. I expect LLMs will advance state of the art in factoring algorithms, considerably.
I guess I only know asymmetric cryptography. I should learn more about symmetric…
Anyone care to boil it down for me :)
Edit: Isn’t this just advanced static analysis of any code base?
Re: LLMs won't break symmetric crypto
#7The only convincing argument here is that these things are battle tested (literally in most cases I would guess), with tons of research that never gets published because it's unsuccessful. A whole lot of human effort has gone into trying to break these things. A lot more than went into any of the math problems AI has solved so far. It's going to take a while before LLMs can equal and surpass that amount of human effort. And they might have to surpass it by many, many times to actually break these, if it is even possible, which is not certain.
Re: LLMs won't break symmetric crypto
#8okay so silicon valley won't happen all the way
Re: LLMs won't break symmetric crypto
#9The first one is not similar to the mathematical breakthroughs LLMs are making recently. There is a loss of information in mods and integer computations making them one-way. The second one requires simply increasing bit-length to match the increased computer power.
Re: LLMs won't break symmetric crypto
#10A next-word-in-the-sentence prediction engine can’t predict the factor of two insanely large prime numbers… tell me more
LLMs are capable not just of calculating the most likely next word from a prompt according to a corpus of training text, but of doing so & feeding back into themselves, the most likely word now based not only on the corpus but on the basic prediction, a second (nth) stage of thought.
Yes it's all still token prediction, but it's predicting conversation between let's say not experts but capable speakers with all the information at hand. Undergraduates if you like. And such conversation can yield real results.