AI Weekly Malaysia

Biotech startup Vivodyne argues AI drug discovery is bottlenecked by a lack of causal biological data from living human tissue, not compute or model architecture. Its HIVE robotic labs grow 20 kinds of human tissue and autonomously dose and monitor them to generate the data that current models lack. The article also notes that AlphaFold has yet to produce a new drug, Isomorphic Labs' first trials are delayed to end of 2026, and even Anthropic's Dario Amodei now calls AI-cures-cancer claims 'more cliche than credible.'

Why: For AI/ML builders and founders, this is a concrete reminder that model capability is often gated by training data quality and availability, not scale — the same pattern applies outside biotech. If you're building AI products, ask whether your bottleneck is actually data you don't have, and whether you need to build infrastructure to generate it rather than throwing more compute at the problem.