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AI CLUSTERED EVENT · 10/14/2026

OpenAI's Internal Model Generates 722 Math Papers, Sparking Cryptographer Fears for Public Key Encryption

1 reports archived1 independent sourcesupdated 10/14/2026, 23:42:36
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OpenAI's internal model generated 722 mathematical manuscripts, prompting leading cryptographers to reassess the potential threat AI poses to modern public key encryption. Johns Hopkins professor Matthew Green estimates a 15% probability that AI could erode confidence in current elliptic curve algorithms (like X25519), which underpin most internet security, by challenging the assumption that private keys cannot be derived from public ones.

LATEST/OpenAI's internal model generated 722 mathematical manuscripts, prompting leading cryptographers to reassess the potential threat AI poses to modern public key encryption. Johns Hopkins professor Matthew Green estimates a 15% probability that AI could erode confidence in current elliptic curve algorithms (like X25519), which underpin most internet security, by challenging the assumption that private keys cannot be derived from public ones.

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Total 1 reports · Latest first
  1. Rohan Paul (@rohanpaul_ai)T2·68 pts
    • OpenAI's internal model demonstrated the ability to batch-generate high-quality mathematical research manuscripts (722 in one instance).
    • Security of mainstream encryption algorithms (e.g., X25519) relies on computational complexity assumptions, which AI breakthroughs in math may weaken.
    • Experts estimate a ~15% probability that AI will erode confidence in current public key encryption systems, highlighting the need for accelerated post-quantum cryptography deployment.
OpenAI's Internal Model Generates 722 Math Papers, Sparking Cryptographer Fears for Public Key Encryption | Today for AI