11 related articles

OpenAI releases its next-gen Astra model, claiming ten major breakthroughs in math and theoretical CS. We analyze AI's shift from answer engine to research collaborator and how Lean verification ensures credibility.

Deep dive into the L2 reduction algorithm, its quadratic complexity advantage over classical LLL, and a Python implementation covering floating-point error control and lazy size reduction.

In-depth analysis of NIST post-quantum standards ML-KEM, ML-DSA, and SLH-DSA, examining quantum threats to RSA/ECC and providing enterprise encryption migration guidance.

An in-depth look at ten major advances in mathematics and theoretical computer science, covering complexity theory, combinatorics, and derandomization, and how they impact cryptography, AI training, and quantum computing.

Deep analysis of Anthropic's cryptanalysis research, examining LLM capabilities in code-breaking tasks, dual implications for AI safety, and methodological value as a reasoning ability benchmark.

Anthropic's Claude Mythos Preview model reportedly discovered improved cryptographic attack methods. This article analyzes the realistic boundaries of AI cryptanalysis capabilities and implications.

Anthropic's Claude Mythos Preview model reportedly discovered improved cryptographic attack methods. This article analyzes the real capability boundaries of AI cryptanalysis and its implications.

Anthropic publishes a practical key-recovery attack on HAWK-256, exposing vulnerabilities in post-quantum signature schemes and implications for PQC standardization.
CUDA 13.3 Adds Carryless Multiplicatio…
CUDA 13.3 introduces native carryless multiplication support, closing a 15-year GPU gap in AES-GCM, CRC, and cryptographic acceleration. Here's what it means.

Can quantum computers really break symmetric encryption like AES? This article analyzes Grover's algorithm's real limits, its key difference from Shor's algorithm, and why AES-256 is quantum-resistant.

NIST has officially standardized the ML-KEM (CRYSTALS-Kyber) post-quantum algorithm. This article covers ML-KEM principles, Python ecosystem implementation, hybrid deployment strategies, and critical challenges like constant-time execution and memory safety.