Research Scientist @GoogleDeepMind: AI for Science & Sustainability PhD from @MIT_CSAIL BlueSky: https://nitter.gq/t.co/yDhvxgMMHq
London, UK
Joined May 2011
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Life update: Maria @BauzaVillalonga and I have graduated, moved to London and joined @DeepMind! We are looking forward to starting exciting research projects with fantastic teams.
Our work @GoogleDeepMind on AI cyclone forecasting is on today's @Nature cover! 🌪️
The art merges:
- @NHC_Atlantic-inspired warning colors
- Mesh & grid computations from the underlying weather model
- Probabilistic "spaghetti" tracks
Paper: nature.com/articles/s41586-0…
Ferran Alet retweeted
Today, @GoogleDeepMind and @GoogleResearch are introducing WeatherNext 3, our most advanced and accurate global weather AI model to date. It uses real-time satellite data to generate hourly high-resolution forecasts, precise precipitation forecasting, and clean energy variables.
Most AI weather models are trained on data from numerical weather prediction (NWP) models, which come with a six-hour data lag. But by training on real-world observations, WeatherNext 3 is able to bypass these traditional constraints — meaning more people can get more accurate predictions to help them plan ahead.
Starting today, WeatherNext 3 will power forecasts within Search, @GeminiApp, @GoogleMaps, Google Maps Platform Weather API and Google Earth Engine.
Ferran Alet retweeted
Today we are announcing WeatherNext 3! 🌦️ Better rain forecasts, higher spatial and temporal resolution, and a new state-of-the-art in medium range weather forecasting 🏆
Paper: storage.googleapis.com/deepm…
Brightband's "Operational WeatherBench": owb.brightband.com/
Excited to share WeatherNext 3 from @GoogleDeepMind and @GoogleResearch!
High-res temperature and precipitation forecasting using the latest satellite observations 🛰️
It's also the best global weather model according to Brightband's live leaderboard!
owb.brightband.com/
Excited to share WeatherNext 3 from @GoogleDeepMind and @GoogleResearch!
High-res temperature and precipitation forecasting using the latest satellite observations 🛰️
It's also the best global weather model according to Brightband's live leaderboard!
owb.brightband.com/
We have also seen improvements on tropical cyclones on top of the 24 hour leap we recently published @NaturePortfolio
We're partnering with @NHC_Atlantic and other agencies to help them safely deploy WN 3 to protect their communities.
Check it out at deepmind.google.com/science/…
Ferran Alet retweeted
Our new Nature paper describing our WeatherNext cyclones model is out!
A decade’s worth of progress in track and intensity forecasting. And it’s fully open source, Including a mini version which runs in a free colab (and is still really good!)
Very excited to share our @Nature paper today! 🌀
WeatherNext Cyclones predicts cyclone track, intensity & wind structure with 24+ extra hours of lead time over previous state-of-the-art, on average.
This leap is equivalent to a decade of progress in the weather community🚀
Ferran Alet retweeted
Predicting cyclones accurately can help save lives - and every hour of lead time counts.
Published in @Nature, our AI model WeatherNext achieves state-of-the-art accuracy in forecasting a storm’s track and intensity, giving us a critical extra 24 hours to prepare on average. 🧵
Very excited to share our @Nature paper today! 🌀
WeatherNext Cyclones predicts cyclone track, intensity & wind structure with 24+ extra hours of lead time over previous state-of-the-art, on average.
This leap is equivalent to a decade of progress in the weather community🚀
The work merges two ideas:
1) Co-training end-to-end on global atmospheric data (20TB) + a tabular database of 5000 cyclones to model extremes
2) Functional Generative Networks: SotA weather forecasting via training on probabilistic marginals with stochastic weight perturbations
We made code, weights & a mini version you can run for free in Colab, all open source!
📄 nature.com/articles/s41586-0…
💻 github.com/google-deepmind/w…
📓 colab.research.google.com/gi…
Thanks to fellow corresponding authors @tom_r_andersson, @IlanPrice, @stratosmarkou & the whole team!
Very impressive to see the recent pace of innovation in robotic dexterity! Contact and deformable objects are notoriously hard to model, yet VLAs like Gemini Robotics 2 are rapidly unlocking what’s possible here.
Ferran Alet retweeted
After years of working on precise dexterous manipulation, I am thrilled to share our latest milestone in robotic dexterity! 🤖🗑️
Gemini Robotics 2 achieves advanced spatial awareness, precise control & robust VLA capabilities in multi-finger hand control.
Great team success🦾💡
I'm hiring a Research Scientist in AI for extreme weather forecasting at @GoogleDeepMind London!
We're finding ML to be surprisingly effective at predicting extreme events like hurricanes, and we're starting to help forecasters save lives.
We're looking for researchers in multimodal ML, large scale deep learning and/or ML4PDEs who have a genuine motivation to work in Science and Sustainability.
Apply here: job-boards.greenhouse.io/dee…
Ferran Alet retweeted
Weather affects everything and everyone. Our latest AI model developed with @GoogleResearch is helping us better predict it. ⛅
WeatherNext 2 is our most advanced system yet, able to generate more accurate and higher-resolution global forecasts. Here’s what it can do - and why it matters 🧵
Excited to announce WeatherNext 2 is live! Blog: goo.gle/4pi1pB3
It leverages FGN (arxiv.org/abs/2506.10772), which surpasses our previous diffusion-based model while making predictions single-shot.
Surprisingly, optimizing only a marginal (per-pixel) loss we get skillful global forecasts!
Functional Generative Networks inject noise within the function for aleatoric uncertainty with structured variability, and sample different networks for epistemic uncertainty.
They're also the core of our cyclone model running live on deepmind.google.com/science/…
Excited to join a live Q&A tonight with Bryan Norcross to talk about our experimental AI cyclone model @GoogleDeepMind !
