#DeepMind

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May 17Sunday

AI HOT (Curated Pool)May 17, 02:56

Eric Jang shares lessons from building AlphaGo from scratch

Eric Jang spent several months implementing AlphaGo from scratch and says that in 2026, training a strong Go AI requires only a few thousand dollars in rented compute rather than DeepMind-scale resources.

Why it matters: All three HKR axes pass: the hook is a from-scratch AlphaGo rebuild, and K has concrete claims on months of work and few-thousand-dollar compute. It stays in 78-84 because this is a social post, not a model release or full paper.

Apr 16Thursday

最佳拍档 (BestPartners)Apr 16, 07:01

Post-AGI may arrive within 50 years: Demis Hassabis on AlphaFold, three AI risk classes, and human value

Demis Hassabis said in a 1-hour interview that post-AGI scenarios can arrive within 50 years, while AGI should stay in labs for another 10-20 years. He cited concrete numbers: AlphaFold has been used by 3M+ scientists, Isomorphic Labs is running 18-19 drug programs, and the most urgent risks in the next 2-4 years are misuse and agent misalignment.

Take

Hassabis’s sharpest point is not the 50-year post-AGI timeline; it is the admission that his preferred route has lost to commercial and geopolitical speed. The numbers make the tension concrete: AlphaFold has 3M+ scientific users, Isomorphic Labs runs 18-19 drug programs, and the lab-to-product gap is now 3-6 months. When DeepMind’s CEO says AGI should spend another 10-20 years inside labs, that carries more weight than another safety paper.

I don’t buy the CERN-style global-collaboration ideal as an operating plan. OpenAI, Anthropic, and Google all invoke safety while still shipping into the same market race. His 2-4 year risk focus on misuse and agent misalignment is more serious than deepfake panic. The ugly part is simple: the people best positioned to brake are still flooring it.