Bio & Science

Anthropic's Model Hardware Standard says agents' safety limits will be "enforced," but never says whether that means clamped in code or written in a sentence a model has to honor. The distinction reaches Europe first: the manufacturers on Anthropic's own vendor list will need conformity assessments under an EU regulation that starts covering AI-based safety functions in January 2027.

Dario Amodei is right that capability-tiered testing isn't regulatory capture, it's a tax on being biggest. But investor David Sacks has a real counter: that same tax only holds if smaller labs actually clear the queue faster, and neither Amodei nor Gavin Baker is asking whether any lab can prove its safety claims at all.

Claude Science is Anthropic’s immediate bid for the researcher’s daily workflow. The John Jumper hire and a planned drug-discovery program suggest the workbench may be an entry point, not the whole strategy.

Cadence raised $1.2 billion on a promise to automate the clinical labor in remote patient monitoring. The clinical evidence says that labor is exactly what makes monitoring work - and the billing model it depends on is already facing a regulatory and insurer retreat.

The viral claim that one AI email drinks a bottle of water, and Sam Altman's teaspoon, are both misleading. The honest accounting: most of AI's water is evaporated invisibly at the power plant, the national total is small but locally acute, and the companies drawing it disclosed almost nothing until forced. A definitive look at what AI actually costs the tap.

OpenAI and Ginkgo Bioworks have shown that a language model can autonomously design, execute, and learn from tens of thousands of biological experiments - cutting protein production costs by 40% in six months. The science is remarkable. The governance gap it reveals is more urgent.

The wetware computing industry is betting billions that living neurons can outperform silicon. A new organism called the neurobot, which grew its own nervous system from scratch with no evolutionary history and no instruction, may be the most radical proof of concept yet, and it raises questions that AI researchers cannot ignore.

Isomorphic Labs has a Nobel Prize-winning platform, $600 million in fresh capital, and partnerships worth up to $3 billion with Eli Lilly and Novartis. Its first AI-designed drug was supposed to enter human clinical trials by end of 2025. It didn't. What the delay reveals about the gap between computational elegance and biological proof.