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DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

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Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#51
post #4

They should try to forecast earthquakes, that would really be a breakthrough If anything better than random comes out

Forecasting earthquakes via ML should be possible but is very strongly limited by data. We have ~50 years of reasonably good seismological catalogs for most of the world. The seismic cycle (the sequence of major earthquake, reloading, major earthquake on a single section of fault) is generally thousands of years except at the fastest-slipping faults. There are very few sections of faults where we have seismological observations of multiple events, and for >90% of faults, we don't even know when the last earthquake was. There are geologic methods to help with this, but they are labor intensive and often yield error bars of hundreds to thousands of years, because the earthquakes don't produce radiocarbon signatures directly; the geologists use e.g. charcoal older and younger layers as available to bracket the timing, and many faults do not have suitable geologic sites to preserve the earthquake deformation and bracket the timing.

I do think it's possible that thorough exploration of the data that do exist can yield broader patterns that apply to many regions, but earthquake behavior has a lot of complexities and different fault systems may behave differently.

A lot of the hope is for coupling physical simulators to ML and the existing datasets to better understand the physics and then work from there, but this is typically cutting-edge HPC work, which limits the pace of research and the number of researchers.

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#52

Maybe was this that was the last drop for Sundar. Demis: "I have a new amazing breakthrough" Sundar: "Great! We really need a answer to Sol and Fable" Demis: "They are completely owned in typhoon forecasting"

Ironically typhoon forecasting, at this moment, is more valuable. These predictions are matters of life, death, and billions of dollars in damage.

How does predicting a typhoon prevent billions in damage?

It could save thousands of lives because people can be evacuated if you can predict a few hours or a day further ahead, or the path more accurately. You can save some damage by moving ships and vehicles.

But you can't evacuate buildings or infrastructure.

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#54
post #41

Earlier quoted context omitted.

You say this as if you don't need he MWP models to train the AI models? The accuracy of the AI Prediction depends entirely on the quality of the training dataset...

I would imagine this would be trained on actual historical weather data instead?

Pretty much all of the AI weather prediction models are trained on ECMWF ERA5, which is kinda like a numerical weather prediction model run to forecast at t=0. ERA5 is historical weather data, but it’s a “reanalysis” of it.

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#55

Earlier quoted context omitted.

Ironically typhoon forecasting, at this moment, is more valuable. These predictions are matters of life, death, and billions of dollars in damage.

I know this is uncharitable and I am wrong but I am having trouble coming up with concrete scenarios where you die with 2 days notice but survive with 3. I am nonethless a believer that more accurate forecasting has value.

You live on a chain of small islands and travel by boat.

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#56

Predicting big weather events is not that hard even with 50 year old technology. What's hard is predicting details, like exactly where it will rain, what the slope of the beach is today (many people don't even know this changes drastically daily and why it is important), wave height, ocean depth today where people swim, water temperature, shorebreak, and knowing with certainty when rain becomes ice/sleet/snow and wha…

> what the slope of the beach is today (many people don't even know this changes drastically daily and why it is important

So why is it important? As far as I know the slope changes AFTER the weather not before as a prediction mechanism but happy to learn

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#57

Earlier quoted context omitted.

Ironically typhoon forecasting, at this moment, is more valuable. These predictions are matters of life, death, and billions of dollars in damage.

Valuable, agreed. But lucrative?

Trade agricultural futures based on it maybe?

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#59

Earlier quoted context omitted.

Ironically typhoon forecasting, at this moment, is more valuable. These predictions are matters of life, death, and billions of dollars in damage.

How does predicting a typhoon prevent billions in damage? It could save thousands of lives because people can be evacuated if you can predict a few hours or a day further ahead, or the path more accurately. You can save some damage by moving ships and vehicles. But you can't evacuate buildings or infrastructure.

You can board up a helluva lot more stuff in a week than in two days. Crucially, you can move more of the most expensive stuff out of the storm surge zone, which is where the biggest damage happens and try to flood proof more of the things which can’t be moved.

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#60

Everything in AI seems to be focused on LLMs lately. But in my opinion, powerful problem-specific models like this are even more interesting. The SOTA AI models used in weather forecasting are already outperforming the classic NWP models while being orders of magnitude more efficient (inference). Most are based on multi scale (hierarchical) Graph Neural Networks, an architecture which is not often talked about. The o…

Rumor is that part of the disruption at GDM these past few months also involved people not wanting to be bound to strictly LLM research.
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