alt Hacker NewsI can already picture the faces of national security directors everywhere.
"The attacks described in these two papers are the strongest attacks we have found to date. We are sharing them after a period of consultation with US government and industry leaders. But as we develop increasingly powerful cryptanalytic results, it would be prudent to consider how researchers should react if a language model were to discover vulnerabilities in cryptosystems where attacks do have an immediate real-world impact. We believe answering this question will require input from academia, government, and industry. We hope that our work here will help launch these conversations."
And a veiled pitch to real cryptanalysis researchers: "Researchers at Anthropic then spent several hundred hours learning enough cryptography research to validate the model’s claim"
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It would be shocking if they haven't been pulling on these threads for as long as they've had access to these models.
> And a veiled pitch to real cryptanalysis researchers: "Researchers at Anthropic then spent several hundred hours learning enough cryptography research to validate the model’s claim"
Many of those researchers, particularly the primary researchers and the individual(s) driving the prompts behind these big stories, have very advanced math degrees and experience. What this shows more than anything is how ML can augment expertise, the searching of solution spaces, and the connecting of dots between existing almost-there research.
But also what's left out is all the time wasted pursuing dead-ends. There's an obvious publication bias at play here, though we can't know how extreme without transparency.