3 ms·

> This reeks of real yin-yangery that extends to the roots of computing somehow. It’s not just me hallucinating patterns where there are none. Me thinks the au

> This reeks of real yin-yangery that extends to the roots of computing somehow. It’s not just me hallucinating patterns where there are none. Me thinks the author doth protest too much... > Unifying AI and crypto at a foundational level smells like a problem on par with unifying relativity and quantum mechanics in physics. Give me a break. This tenuous link between fads I made up is as important as understanding the nature of the universe! What kind of brain worm makes people think and write like this?

thrown1212 4y ago
Over-weighting over-fitting pattern matches because you believe you’re quite clever. It’s a soft case of what happens when you’re stoned.
- hinkley 4y ago
  > Over-weighting over-fitting pattern matches No wonder he's so comfortable with AI...
hinkley 4y ago
The bipolar disorder spectrum, that's what.
sdwr 4y ago
Really? AI and crypto together is the nuts. That's how it begins to not just affect the real world but participate in it. If anything, the idea of an ungoverned financial arena made of code fits too well with AI. Sounds like the launchpad for skynet.
astrange 4y ago
> What kind of brain worm makes people think and write like this? He's a post-rationalist so probably the macrodose of LSD and piracetam he wrote the post on.
through_17 4y ago
Tension between machine learning and cryptography has been studied since at least the late 80's. Example classical result: Kearns and Valiant, "Cryptographic Limitations on Learning Boolean Formula and Finite Automata." Roughly, they show that efficient learning algorithms for Boolean formulae could break RSA --- so probably such learning algorithms do not exist. Recent breakthroughs are quite exciting: see page 4 of "On One-way Functions and Kolmogorov Complexity" which, for the first time, bases the security of private-key crypto on a natural and fundamentally computational problem instead of something from number theory. They get a solid connection to universal extrapolation via Impagliazzo, Levin '90. Currently, these results operate for overly-restrictive learning models. I hope we will slowly improve them to obtain win/win conditions: depending on the setup either strong cryptography or strong learning is possible, but not both. My point is: these are not fads. We have been working very hard on fundamental mathematical connections between learning and crypto for decades. Progress is slow, but meaningful. Those papers are theoretical, but modern crypto emerged from a purely theoretical and embryonic "computational number theory". I am also not a fan of the article. It would have been better if the author had chosen to define, for example, "one way functions" and the "PAC learning model" and explain why these theoretical constructions are not quite a match for large language models and blockchain-based protocols. However, I believe that bringing computational learning theory --- which is inextricably linked to cryptography --- closer and closer to LLMs is a promising direction for future research. Links to Cited Papers: https://www.cis.upenn.edu/~mkearns/papers/crypto.pdf https://www.cis.upenn.edu/~mkearns/papers/crypto.pdf https://eccc.weizmann.ac.il/report/2020/052/ https://eccc.weizmann.ac.il/report/2020/052/
- semiquaver 4y ago
  Thanks very much for the substantive response with citations. My use of “fad” was primarily referring to the author’s reference to “crypto”, unfortunately these days more often short for “cryptocurrency” than “cryptography”. In context that is very clearly the case here: > Blockchains are the right way for software to eat money I think the link between cryptography and ML is fascinating, but cryptocurrency is absolutely a faddish cesspool of speculation and fraud.
ShredKazoo 4y ago
>This tenuous link between fads I made up is as important as understanding the nature of the universe! Maybe he told ChatGPT to give him a galaxy-brained Venkat take. Is the "seems like it's going somewhere interesting but never actually gets there" style one that's easy for AIs? (If Venkat can dunk on David Brooks then I can dunk on Venkat!)

thrown1212 4y ago

Over-weighting over-fitting pattern matches because you believe you’re quite clever. It’s a soft case of what happens when you’re stoned.

hinkley 4y ago
> Over-weighting over-fitting pattern matches No wonder he's so comfortable with AI...

hinkley 4y ago

The bipolar disorder spectrum, that's what.

sdwr 4y ago

Really? AI and crypto together is the nuts. That's how it begins to not just affect the real world but participate in it. If anything, the idea of an ungoverned financial arena made of code fits too well with AI. Sounds like the launchpad for skynet.

astrange 4y ago

> What kind of brain worm makes people think and write like this? He's a post-rationalist so probably the macrodose of LSD and piracetam he wrote the post on.

through_17 4y ago

Tension between machine learning and cryptography has been studied since at least the late 80's. Example classical result: Kearns and Valiant, "Cryptographic Limitations on Learning Boolean Formula and Finite Automata." Roughly, they show that efficient learning algorithms for Boolean formulae could break RSA --- so probably such learning algorithms do not exist. Recent breakthroughs are quite exciting: see page 4 of "On One-way Functions and Kolmogorov Complexity" which, for the first time, bases the security of private-key crypto on a natural and fundamentally computational problem instead of something from number theory. They get a solid connection to universal extrapolation via Impagliazzo, Levin '90. Currently, these results operate for overly-restrictive learning models. I hope we will slowly improve them to obtain win/win conditions: depending on the setup either strong cryptography or strong learning is possible, but not both. My point is: these are not fads. We have been working very hard on fundamental mathematical connections between learning and crypto for decades. Progress is slow, but meaningful. Those papers are theoretical, but modern crypto emerged from a purely theoretical and embryonic "computational number theory". I am also not a fan of the article. It would have been better if the author had chosen to define, for example, "one way functions" and the "PAC learning model" and explain why these theoretical constructions are not quite a match for large language models and blockchain-based protocols. However, I believe that bringing computational learning theory --- which is inextricably linked to cryptography --- closer and closer to LLMs is a promising direction for future research. Links to Cited Papers: https://www.cis.upenn.edu/~mkearns/papers/crypto.pdf https://www.cis.upenn.edu/~mkearns/papers/crypto.pdf https://eccc.weizmann.ac.il/report/2020/052/ https://eccc.weizmann.ac.il/report/2020/052/

semiquaver 4y ago
Thanks very much for the substantive response with citations. My use of “fad” was primarily referring to the author’s reference to “crypto”, unfortunately these days more often short for “cryptocurrency” than “cryptography”. In context that is very clearly the case here: > Blockchains are the right way for software to eat money I think the link between cryptography and ML is fascinating, but cryptocurrency is absolutely a faddish cesspool of speculation and fraud.

ShredKazoo 4y ago

>This tenuous link between fads I made up is as important as understanding the nature of the universe! Maybe he told ChatGPT to give him a galaxy-brained Venkat take. Is the "seems like it's going somewhere interesting but never actually gets there" style one that's easy for AIs? (If Venkat can dunk on David Brooks then I can dunk on Venkat!)