We're hiring a Research Engineer based in San Fran or MTV, California, to join our sustainability & weather teams at GDM. Seeking strong engineers at the interface of ML, sustainability, weather, dynamical systems, and/or remote sensing: boards.greenhouse.io/deepmind/job...

📸: Our researcher Kate Musgrave presenting on AI weather predictions #AMS2025 | @ametsoc.bsky.social

I'll be presenting GenCast, recently published in Nature, tomorrow Tuesday 8h45AM at #AMS2025 in room 339. GenCast is a diffusion model that outperforms ENS, the top operational ensemble forecast, giving skillful probabilistic forecasts up to 15 days ahead. ams.confex.com/ams/105ANNUA...

Ferran's GenCast talk on Tuesday morning at #AMS2025 is not one to miss! ams.confex.com/ams/105ANNUA...

I'll be at #AMS2025 next week alongside some other Google DeepMind colleagues behind GenCast/GraphCast. Excited to meet people, discuss ML for weather, and learn!

Can everyone come over from LinkedIn now 😅 There’s still more of the ML/Earth sciences community active on there than BlueSky I feel

I love how William Shatner from Star Trek went to space and realised how horrible it is in contrast to our beautiful home planet. My life goal used to be to help get humans to Mars. I’m so glad I realised how special Earth is and now work on better living here rather than leaving 🌍

Can incorporating AI improve precipitation in global weather and climate models? Yes! In the latest NeuralGCM paper, we show that training on satellite-based precipitation results in significant improvements over traditional atmospheric models: arxiv.org/abs/2412.11973

Interested in AI weather/climate modeling at #AGU24? I'll be giving an overview talk on NeuralGCM at 11:30am Wed at the Google booth, and an talk on modeling precipitation with NeuralGCM at 4:25pm Wed in the session A34A.

So excited to share our Google DeepMind team's new Nature paper on GenCast, an ML-based probabilistic weather forecasting model: www.nature.com/articles/s41... It represents a substantial step forward in how we predict weather and assess the risk of extreme events. 🌪️🧵

Quite happy with IceNet getting its 200th citation a little after its 3rd birthday ❄️🎂💻 IceNet began around the time when applying ML to Earth sciences was the stuff of hushed conversations in corridors. A few years later and its potential to revolutionise the field is indisputable. Lots more to do!

Beautiful introduction to transformers in this lecture by 3blue1brown / Grant Sanderson: youtu.be/KJtZARuO3JY?...

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