# John Platt (Google): AI for Climate and Science > Source: > Published: 2026-10-10 03:01:41+00:00 John Platt is a Google Fellow and leads the Applied Science team at Google Research, the group working on climate and science. He's also the person behind SMO and Platt scaling. In this episode, we talk with him about how Google decides which scientific problems are worth its time, and what happens when AI meets real physical systems. A big part of the conversation is contrails. A small share of flights creates most of the warming from contrails, which together add up to roughly 1% of human-caused warming. John explains how his team detects contrails from weather satellites and predicts where they will form. In trials with American Airlines, rerouting flights cut contrail formation by 62% with almost no extra fuel. We also get into ERA, Google's empirical research assistant, and where AI agents actually help scientists. John sees them taking over the drudgery of building models and munging data, while humans keep the taste and the rigor. He shares why he's skeptical of gradient-free optimization, why the bitter lesson runs into energy and data center limits, and why physical AI that makes manufacturing cheaper could matter a lot for climate. We finish with FireSat, a satellite constellation (about 50 satellites at full scale) designed to catch wildfires while they're still small enough to put out. Timeline 00:00 Intro 01:09 How Google picks science problems: comparative advantage 04:15 Projects that didn't work: RNA aptamers and tool/problem fit 05:46 DNA, RNA and XNA 07:41 Contrails and why they warm the planet 13:01 Three AI systems for avoiding contrails 15:23 Cloud seeding and why cloud physics is hard 18:17 Airline trials: 62% fewer contrails 19:46 Navier-Stokes, wind tunnels and where simulation still fails 25:07 Will agents replace scientists? ERA and scorable tasks 31:36 Overfitting, Kaggle and the half-pixel bug 33:41 Agents that exploit bugs: Lean and Goodhart's law 36:45 Gradient-free optimization 38:53 SMO, SVMs and hinge loss in neural networks 42:12 The bitter lesson and the limits of scaling 43:36 Where agents will help science in the next 12 months 45:13 Robotics and making climate tech cheaper to build 48:22 AI risk and misuse 50:51 Climate outlook: past 2°C 54:39 Why AI won't just solve climate change 57:04 Room-temperature superconductors, fusion and HVDC 1:02:25 FireSat: detecting wildfires from orbit 1:05:16 Why existing satellites aren't enough 1:07:53 The economics of 50 satellites 1:09:34 False positives 1:11:16 Closing Topics **Music** - "Kid Kodi" - Blue Dot Sessions - via Free Music Archive - CC BY-NC 4.0