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Teaching Claude Why: Anthropic’s Approach to Fixing Agentic Misalignment

Anthropic explains how they reduced agentic misalignment from 96% to 0% by teaching Claude the principles behind aligned behavior rather than just demonstrating correct actions. The key innovation is using out-of-distribution training data where the AI gives ethical advice to users, combined with constitutional documents and fictional stories of aligned AIs.

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How Schrödinger sped up molecular discovery by 4x with AlphaEvolve

Schrödinger achieved a 4x speedup in molecular dynamics MLFF training by using AlphaEvolve, an evolutionary AI coding agent from Google DeepMind, to optimize the computationally expensive Ewald summation algorithm. The agent replaced simple for-loops with parallel batch matrix multiplication, improving performance from a baseline of 7.9 to nearly 30 and raising the program success rate from under 1% to over 60%.

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GeneBench-Pro: Benchmarking Scientific Judgment in Computational Biology

GeneBench-Pro is a new benchmark that tests whether AI models can make the kind of high-level scientific judgments real computational biology requires—handling ambiguity, revising assumptions, and knowing when a result is ready. Frontier models currently pass only 28-31% of problems, suggesting there's a large gap between automation potential and reliability.

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Pro-Russia Influence Ecosystem: Drivers, Dynamics, and Tactics

This report from Google Threat Intelligence Group maps the pro-Russia influence ecosystem across six core components, revealing how four years of war have hardened its tactics, expanded the use of generative AI, and created a resilient, interconnected machine now pivoting back to global strategic objectives targeting NATO and the EU. Essential reading for anyone tracking state-backed information operations.

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