91–100 of 110 posts
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.
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…
Is there any website publishing these forecasts? I imagine NWS/NOAA isn’t doing anything different yet on their public websites.
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Is there any website publishing these forecasts? I imagine NWS/NOAA isn’t doing anything different yet on their public websites.
Yes. AIFS directly by ECMWF and AIGEFS by NOAA. Every vibecoded weather app these days has them. Google those terms you’ll find them.
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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.
Keep in mind, DeepMind has a very well documented history of releasing enormously hyped up PR pieces with grandiose claims that are never backed up in real world usage, or are simply lies.
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…
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...
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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.
on one side, deepmind makes a lot of advancement in science related application. but, on the commercial side, they struggle to compete with other major LLM providers.
And this is why GDM has to go. It's crazy that when Google is struggling so badly that efforts like this that have no path to revenue at all were funded. GDM management really thought that they were some kind of charity. UNREAL.
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I can assure you that anyone who touches numerical simulations of any kind (physicists, engineers, chemists, biophysicts...etc) has tried their hand at ML based surrogate models in the last 5 years, so it's not like they aren't being tested. From my experience, they aren't very robust. Weather modeling is actually one of the very few areas where it seems to work half decently.
Why does it work for weather at all? Is there something that the mathematical models are over-simulating? Is weather easier to predict than we thought? Just curious what the intuition is to regarding the success of ML weather modelling...
And general weather forecasts are not that hard - we have semi useful forecasts for more than 50 years. It’s when you want to do something special: long range, nowcasting of convective storm, other extreme weather etc. that is hard. And even then it’s as much a problem of input data accuracy than the models themselves.
And this is why GDM has to go. It's crazy that when Google is struggling so badly that efforts like this that have no path to revenue at all were funded. GDM management really thought that they were some kind of charity. UNREAL.
Are you being sarcastic? Even if “Google is struggling so badly” (which it really is not - the narrative will flip again at some point), these efforts will have a lasting impact on the world. Not everything good is about bringing in revenue.