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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.
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Ferran Alet
203 posts
Ferran Alet
@FerranAlet
Research Scientist @GoogleDeepMind: AI for Science & Sustainability PhD from @MIT_CSAIL BlueSky: https://t.co/yDhvxgMMHq
London, UK Katılım Mayıs 2011
453 Takip Edilen1.7K Takipçiler
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/deepmind/jobs/…
GIF
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Ferran Alet retweetledi
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 🧵
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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/weathe…
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Excited to announce WeatherNext 2 is live! Blog: t.co/0DJCJWbMDF
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!
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Excited to join a live Q&A tonight with Bryan Norcross to talk about our experimental AI cyclone model @GoogleDeepMind !
Bryan Norcross@bryannorcrosstv
LIVE Q&A TODAY at 4 PM ET. I'll be joined by Senior Research Scientist at Google DeepMind Ferran Alet. We'll talk about the new amazing and surprising Google DeepMind AI hurricane model. We'll be LIVE on YouTube, Facebook, TikTok, X, Instagram, and LinkIn. Looking forward to your questions!!
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Ferran Alet retweetledi
SCIENCE! 🔬🌎
Can we take a moment to appreciate this fact:
✅ A powerful hurricane is spinning just 200mi offshore of Florida.
✅ And yet, we haven't had the least bit of concern, because science told us all along that #Erin would turn north.
That is the power of meteorology, satellite observations, & NWP/AI models working together. Instead of panic, we can rely on data, physics, & decades of research.🌪️📡
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@Weathernerds @AndyHazelton GenCast (GENC) is "corrected" as in, debiased, and should be better than vanilla GenCast intensities.
FNV3 is not quite an intensity "correction". We use ML to learn to predict intensities and wind radii directly.
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@AndyHazelton FNV3 is their latest experimental version that includes the intensity "correction"
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Alright, Google Deep Mind tracks are live. Ingest code is still pretty raw so bear with me if there are issues. Also, I switched to an "Ensembles" drop menu now. Thanks to the GDM team for their phenomenal work!!!
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@danrothenberg @GoogleDeepMind @NHC_Atlantic Interesting!
Possibly relevant, we find that EPS sometimes shows disturbances weaker than those categorized by the NHC. So it's possible that our model only deems the disturbance strong enough later in the development.
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The @GoogleDeepMind WeatherLab demo (deepmind.google.com/science/weathe…) will get one hell of a workout with this @NHC_Atlantic's Disturbance 1. Fascinating forecast - and very curious that the EPS ensemble locks onto development much earlier than the MLWP suite...
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Ferran Alet retweetledi
We're looking for people to join us to work on Gemini Diffusion and help revolutionize language modeling!
Details below:
job-boards.greenhouse.io/deepmind/jobs/…
Brendan O'Donoghue@bodonoghue85
Excited to share what my team has been working on lately - Gemini diffusion! We bring diffusion to language modeling, yielding more power and blazing speeds! 🚀🚀🚀 Gemini diffusion is especially strong at coding. In this example the model generates at 2000 tokens/sec, including overheads like tokenization, prefill, safety filters etc.
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Ferran Alet retweetledi
Accurate weather prediction is extremely important for keeping people safe, particularly when it comes to dangerous cyclones. Exciting to see this new initiative from @GoogleDeepMind & @GoogleResearch in partnership with @NWSNHC.
Google DeepMind@GoogleDeepMind
We’re using AI to improve cyclone prediction. 🌀 Introducing Weather Lab: a new interactive platform developed with @GoogleResearch, hosting our experimental AI weather model which can predict a cyclone’s track, intensity, size and structure. Here’s how it works. 🧵
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Ferran Alet retweetledi
Excited to see this work out in public!
This is based on our new model, FGN, described in our paper storage.googleapis.com/deepmind-media…
Check it out 🌀⛈️
Google DeepMind@GoogleDeepMind
We’re using AI to improve cyclone prediction. 🌀 Introducing Weather Lab: a new interactive platform developed with @GoogleResearch, hosting our experimental AI weather model which can predict a cyclone’s track, intensity, size and structure. Here’s how it works. 🧵
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Finally, we're announcing Weatherlab deepmind.google.com/science/weathe… a public preview where we share the predictions from our AI models.
Here you can see a live prediction of a cyclone in China, where our model in blue shows more confident predictions than a leading physics-based model.
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This season, forecasters at @NHC_Atlantic are going to see live predictions from our models, and we hope to enhance their predictions this cyclone season.
Interacting with experts at NHC, Colorado State, and other agencies has been one of the most rewarding parts of the project.
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Excited to announce our new experimental cyclone model and a partnership with @NHC_Atlantic!
Traditionally, it's been hard for a model to predict tracks & intensities: one requires a global view, the other very high resolution. Our AI model achieves strong performance on both.
Google DeepMind@GoogleDeepMind
We’re using AI to improve cyclone prediction. 🌀 Introducing Weather Lab: a new interactive platform developed with @GoogleResearch, hosting our experimental AI weather model which can predict a cyclone’s track, intensity, size and structure. Here’s how it works. 🧵
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Ferran Alet retweetledi
In the 'Instant edit' tab of our demo, users can ask Gemini diffusion to edit some text with an instruction. This works similarly to images where the model is initialized with the text to be edited and then does some diffusion to satisfy the instruction. If the edits are small it can be very fast!
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Ferran Alet retweetledi
Excited to share what my team has been working on lately - Gemini diffusion! We bring diffusion to language modeling, yielding more power and blazing speeds!
🚀🚀🚀
Gemini diffusion is especially strong at coding. In this example the model generates at 2000 tokens/sec, including overheads like tokenization, prefill, safety filters etc.
Google DeepMind@GoogleDeepMind
We’ve developed Gemini Diffusion: our state-of-the-art text diffusion model. Instead of predicting text directly, it learns to generate outputs by refining noise, step-by-step. This helps it excel at coding and math, where it can iterate over solutions quickly. #GoogleIO
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Beautiful visualizations of optimization in high dimensions and why local minima became less of a concern as networks scaled: youtube.com/watch?v=NrO20J…
IIRC this realization started around 2014-15, but the concern over local minima took multiple years to gradually fade away in the community as theoretical & empirical evidence mounted.
In my case, the conversion happened with:
1) Kenji Kawaguchi's (my labmate at the time) "Deep Learning without Poor Local Minima" 2016 paper and
2) empirically finding gradient descent highly effective for a very non-smooth problem (modular meta-learning) in 2018.
YouTube
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Ferran Alet retweetledi
We're hiring a Research Engineer in AI for Sustainability @GoogleDeepMind (San Francisco / Mountain View).
Seeking strong engineers at the interface of machine learning, environmental sustainability, weather, dynamical systems, and/or remote sensing: boards.greenhouse.io/deepmind/jobs/…
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+1! It's particularly valuable advice for PhD students: AI for Science&Sustainability offers great research topics. It's far less saturated than NLP or vision, doesn't require internet-scale pre-training, and discovering the right inductive biases gives you substantial leverage.
raia hadsell@RaiaHadsell
hot take - it's not all about language. Beyond chatbots, AI has a profound ability to model more complex - and mysterious - systems, from the human body and global weather to Earth in its entirety. I shared my views on the @TEDAIVienna stage: ted.com/talks/raia_had…
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