5 items
A podcast about machine learning and data science hosted by Katie Malone and Ben Jaffe. Approachable explanations of ML concepts without dumbing them down.
Back with new episodes on Substack. Also available on Spotify.
Why scaling up multi-agent AI systems doesn't deliver proportional benefits — collaboration turns out to be a distinct capability, and adding agents to sequential tasks often makes things worse.
Loved the exploration of coordination cost — the idea that agents communicating and handing off work isn't free, and that overhead often swamps any gains from parallelism.
Temperament matters more than talent in AI research — a meditation on the daily practice of reading and building, and why equanimity is the real prerequisite.
The Zen framing isn't just a metaphor — he quotes Suzuki directly, structures the piece like numbered koans, and the equanimity point is genuinely it: sit with failure the same way you sit with success, neither attached to the outcome.