ai-for-science
2 items · chronological order
The AI Revolution in Math Has Arrived
AlphaEvolve found hypercube structures in permutation groups that mathematicians hadn't noticed in 50 years: not by answering the question posed, but by surfacing a pattern nobody thought to look for. The real capability shift isn't AI proving things faster; it's AI scanning combinatorial spaces too large for human intuition and returning structures that reframe entire research programs. Discovery is being commoditized; the scarce resource is now verification infrastructure and the human judgment to recognize which discoveries matter.
Why It's Crucial We Understand How A.I. 'Thinks'
Interpretability's real breakthrough isn't cracking the black box: it's using imperfect understanding to extract hypotheses humans missed. Goodfire and Prima Mente's Alzheimer's biomarker discovery reframes the field from safety obligation to discovery engine. The commercial signal matters more than the methodology debates: $1.25B for a standalone interpretability lab means enterprises will pay for explanation scoped to specific use cases, not universal model transparency.