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Google says AI weather model masters 15-day forecast

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Re: Google says AI weather model masters 15-day forecast

#181
I don’t really understand why Google and other companies making similar models are able to train on existing modelled or reanalysis data sets and then claim further accuracy than the originals. Sure, stacks of convolutions with multimodal attention blocks should be able to tease apart all the of idiosyncratic correlations that the original models may not have seen. But it’s unclear to me that better models is the direction to go in as opposed to better data.

Re: Google says AI weather model masters 15-day forecast

#183
post #163

Turns out the Google AI's 15-day forecasts are for the weather in Mountain View. Which I can forecast 15 days out, too.

Yes, most people can predict weather in the dessert. But why do you claim this is what happened here? Or was it a joke? Because people took it serious. Neither the article, nor the linked paper state that. But they have all the details on precision and condition. https://www.nature.com/articles/s41586-024-08252-9

It was a joke about how silly valley based companies will claim the moon and back and then design a car that doesn’t know dumping snow in the boot is bad.

Re: Google says AI weather model masters 15-day forecast

#186

Turns out the Google AI's 15-day forecasts are for the weather in Mountain View. Which I can forecast 15 days out, too.

haha, one of the few times my gut reaction to something on HN was dead on. "The easiest job in the world is the weatherperson in San Diego... And now, Ryan, what's the weather going to be like today?' 'uh, nice. back to you!'"

[deleted]

Re: Google says AI weather model masters 15-day forecast

#188

Earlier quoted context omitted.

This whole article smells like marketing and a way to monetize their weather model. I hope its leaps and bounds beyond current capability but I have very strong doubts about its efficacy in the real world.

Looks like it will be free and open > We’ll be releasing our model’s code, weights, and forecasts, to support the wider weather forecasting community. https://deepmind.google/discover/blog/gencast-predicts-weath...

> "We'll soon be releasing real-time and historical forecasts from GenCast, and previous models, which will enable anyone to integrate these weather inputs into their own models and research workflows."

They will give you the weights and code not the forecast - your quote is incomplete.

Its either a temporary gift to the community until its adopted then charge for it OR they know most orgs can integrate that into their products therefore requiring to buy google products IF it works as they say it does.

Re: Google says AI weather model masters 15-day forecast

#189
post #24

I really wonder if, like the weather, we should see new financial prediction models, understanding that there is randomness but also patterns.

I see a fundamental issue issue from systems theory here, but do note that I'm by no means an expert at that, just had a bachelor course covering it together with control theory. The issue is that you would train a model on historical data, then you would use the model's predictions to make financial decisions. But, the moment you are using those predictions, you modified the system the model learned to predict. Now, maybe we can argue that, if you only invest a little money, you aren't really influencing the stock market. But I think the case would be very different if we're talking about big investors.

Re: Google says AI weather model masters 15-day forecast

#190

I don’t really understand why Google and other companies making similar models are able to train on existing modelled or reanalysis data sets and then claim further accuracy than the originals. Sure, stacks of convolutions with multimodal attention blocks should be able to tease apart all the of idiosyncratic correlations that the original models may not have seen. But it’s unclear to me that better models is the dir…

> The model was trained on four decades of temperature, wind speed and air pressure data from 1979 to 2018 and can produce a 15-day forecast in just eight minutes—compared to the hours it currently takes.

Basically, they trained the model on old observations, not old predictions.

IE, imagine someone created a giant spreadsheet of every temperature observation, windspeed observation, precipitation observation, ect, and then told the computer to learn how to predict a column.

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