MIT
At last week’s MIT AI Conference, a panel of scientists and industry leaders gathered to tackle a deceptively simple question: how do we build artificial intelligence that clinicians can trust? More specifically, how to we get to AI precise enough to handle life-or-death decisions yet transparent enough for a
Data
Xaira just dropped X-Atlas/Orion—the largest genome-wide Perturb-seq dataset ever, covering 8 million cells. It's public, powerful, and poised to reshape how AI predicts biology. Launching a biotech startup is often about making promises. These are promises to investors, to science, to medicine. But when you start
AI
Fauna Bio is betting evolution already cracked biology’s toughest problems. Their new AI engine, Fauna Brain, turns nature’s wildest genetic secrets into therapeutic targets in minutes and costs pennies. Fauna Bio isn’t your typical Silicon Valley biotech startup. Instead of chasing incremental tweaks to familiar targets, they&
Systems
Recursion Pharma's stack is bioIT future spelled out clearly from automated labs through edge GPU compute streaming Kafka Kubernetes orchestration and cloud TPUs The architecture isn't just efficient it's inevitable. It’s almost a cliché now to say biology has become a data science
AI
BioIT isn’t starved for data. It’s choking on chaos. No shared formats. No clean metadata. No real interoperability. If we don’t fix that, AI stays blind. The scene is not particularly dramatic, unless you’re the kind of person who thinks databases can scream. We’re in
AI
If you want to see what an antibody language model trained only on humans can actually do, GLIMPSE-1 is your proof. No mouse scaffolds or synthetic libraries. And no structural hallucinations either. Just native human sequence data, paired heavy-light chains, and a model trained to learn the logic evolution already
Protein Design
Most of what passes for protein design these days is better described as substitution. You take a known backbone, swap in plausible residues based on energy or evolutionary alignment, and run it through simulation until the numbers settle into something stable. It works, in a way, but it’s more