discovery science
Beyond Market Intelligence keeps discovery science in one place: 3 stories so far. The section currently leads with “Explore Data Innovation at the Discovery Science Conference in Mainz”, “Why open data, not moats, will let AI engineer better medicine”, and “Explore how synthetic query probing makes embedding models truly comparable”. A small conference with a clear focus on applied data work, the Discovery Science Conference in Mainz is worth a look if you're tired of theory-heavy talks. Vijay Pande walked away from managing $4 billion at a16z to bet smaller, and that restraint is exactly the point. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every discovery science story on Beyond Market Intelligence, newest first.
Explore Data Innovation at the Discovery Science Conference in Mainz
A small conference with a clear focus on applied data work, the Discovery Science Conference in Mainz is worth a look if you're tired of theory-heavy talks. From October 5-9, the agenda leans into practical outcomes, which feels refreshing for anyone who wants to see how data innovation actually lands in the real world. I'm presenting my paper there and would be glad to connect with fellow attendees. If you're on the fence about going, this is the kind of event where exploration meets execution.
Why open data, not moats, will let AI engineer better medicine
Vijay Pande walked away from managing $4 billion at a16z to bet smaller, and that restraint is exactly the point. His new firm, VZVC, leans into AI-native investing because he sees biology shifting from discovery to engineering. Clinical trials remain brutally expensive, and he argues open, shared datasets will matter more than proprietary walls. That conviction feels right. For a deeper look at how AI handles messy real-world data, our piece on real-world computer vision deployments is worth reading.
Explore how synthetic query probing makes embedding models truly comparable
Embedding models are rarely interchangeable, yet swapping one for another often feels like a roll of the dice. Synthetic Query Probing tackles this head-on by comparing similarity spaces instead of raw vectors. The results show Titan's scores relate across dimensions, but Titan versus Ada is nonlinear with different ranges. That is a practical insight for setting retrieval thresholds. For a deeper look at how clean data shapes model behavior, our piece on catching AI slop before it skews your model pairs well with this research.