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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

#72
post #59

Earlier quoted context omitted.

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.

> You can board up a helluva lot more stuff in a week than in two days TFA says they might be able to predict one extra day ahead (three days instead of two). No prediction system will ever give you a week's notice on a typhoon.

30% more time to know exactly where to board up etc. seems very significant

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#73

Earlier quoted context omitted.

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.

Indeed, you can imagine this as some sort of advanced physics-based interpolation of various measurements (land stations, satellite data, ...) to fill in every cell in a latitude-longitude grid. This is not only used for ERA5 (training data for the models), but also to determine the initial conditions for every grid cell which are used to roll out the forecast. So AI weather models depend greatly on the NWP/physics u…

Yeah. I can’t remember names off the top of my head, but there are a few companies, and I think many researchers, working on AI “data assimilation” for this.

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#74
post #4

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

Google has the early warning system that gives people maybe 20-30s to e.g. turn off gas, stop vehicles, get under something solid. There was a lot of news recently about how this saved many thousands of lives in Venezuela I think it was. But hey let's all keep shitting on Google because their coding agent is slightly worse than SOTA.

And it's been built into every Android phone for years, for free. While Apple is still completely Missing In Action.

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#76
post #22

Earlier quoted context omitted.

Are Sol and Fable lucrative? I suspect they also are valuable (to clients) but not lucrative (yet).

I think both have value, but in opposite ways. While WeatherNext prevents costs, models like fable or sol "create profit". I can think of 10 examples how one could make money with fable. With WeatherNext? Only 10 examples of preventing costs. Taking this, maybe naive, thought further, profits have no upper limit (except resources) while costs can only save so much?

Yes of course. My comment was facetious.

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#77

Earlier quoted context omitted.

> You can board up a helluva lot more stuff in a week than in two days TFA says they might be able to predict one extra day ahead (three days instead of two). No prediction system will ever give you a week's notice on a typhoon.

30% more time to know exactly where to board up etc. seems very significant

[deleted]

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#78

Earlier quoted context omitted.

> You can board up a helluva lot more stuff in a week than in two days TFA says they might be able to predict one extra day ahead (three days instead of two). No prediction system will ever give you a week's notice on a typhoon.

30% more time to know exactly where to board up etc. seems very significant

Wouldn't it be 50% more time?

Re: DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

#79

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…

everything in AI is not focused on LLM, if you think so then that's because you are in LLM bubble. The big idea with LLM is that it's generative AI, the generative could be anything! Not just large languages, we have seen break through in image generation, video, audio, but guess what. Anything that you have enough data and given data you can predict what comes next can have gen AI applied, so we are seeing it with physical actions so robots get trained to generate the next move, and I think the same thing applies to weather forecast. It's predictable too given enough data
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