This is great from a practical standpoint (being able to predict weather), but does it actually improve our understanding of the weather, or WHY those predictions are better?<p>That is my issue with some of these AI advances. With these, we won't have actually gotten better at understanding the weather patterns, since it's all just a bunch of weights which nobody really understands.
I'm friends with a meteorologist and the 15+ day forecast is the bane of their existence because you can't accurately forecast beyond a week so I would love to know how they are measuring accuracy. The article doesn't say and I know the paper is going to go over my head.
They can say what they want, but I get rained on by surprise rain more than I ever have in my life, now that I'm practically forced to use the built-in Google weather due to them and Apple catching and killing all the good weather apps.
Is that a prediction in the form of "There's a 30% chance of light rain that day." or "Temperature will reach 22,5°C at 14:00."?
It does seem like this is one of those domains where new AI models could thrive. From my understanding, the amount and variety of data necessary to make these models work is huge. In addition to historical data, you've got constant satellite data, weather stations on the ground for data collection, weather balloons going high into the atmosphere multiple times daily per location, Doppler radars tracking precipitation, data from ships and other devices in the ocean measuring temps and other info, and who knows what else.<p>It's incredible that we are able to predict anything this far into the future, but the complexity seems like it lends itself to this kind of black box approach.<p>*This is all speculation, so I'd be grateful if someone more knowledgeable could tell if if I'm mistaken about these assumptions. It's an interesting topic.
The catch: the model is predicting the past:<p>>> But DeepMind said GenCast surpassed the precision of the center's forecasts in more than 97 percent of the 1,320 real-world scenarios from 2019 which they were both tested on.
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.
Can we extract the latent understanding it has?<p>Would be really cool to convert it's predictive model into a computer program that predicts written in like python/C/rust/whatever, and I think that would better serve our ability to understand the world.
On a related note, the company I work for is hiring a meteorologist for a commodities trading desk in NYC and London. Send me an e-mail if you would like a referral: <a href="https://mlp.eightfold.ai/careers/job?domain=mlp.com&pid=755939667061&domain=mlp.com&sort_by=relevance&job_index=84" rel="nofollow">https://mlp.eightfold.ai/careers/job?domain=mlp.com&pid=7559...</a>
"More accurate forecasts of risks of extreme weather can help officials safeguard more lives, avert damage, and save money," DeepMind said.<p>Did the DeepMind AI say this?
I recently read that the 10 day forecast now is as accurate as the 5 day forecast from 30 years ago when I was a kid.<p>This surprised me. I grew up in Ohio and now I live in the Bay Area and the forecast here seems to be accurate only 2-3 days out. It would be so helpful to have an accurate 10 day forecast.
FTA:<p>> But he said these forecasting systems are reliant on the weather prediction models that are already running, such as that operated by ECMWF.<p>et voilà.
It takes 8 minutes to produce a 15 day forecast. That's actually quite a long time for an AI model. I should probably read the paper to find out why but does anyone know? Is the model predicting the weather in 10 minutes time and just run iteratively 2000 times for a 14 day forecast?
As long as the AI in charge of weather forecasting never ever comes within the control of the AI charged with fixing climate change.<p>GOAL: Fix world’s problems.
OBSERVED CAUSE: Too many humans.
DECISION: Tell humans about impending hurricane? Yes/No
Obviously this team knows way more about this donain than me but I have to ask, wouldnt this only be able to predict weather which is in line with past weather patterns/indicators? I can imagine a weather analyst might be able to see "between the data" and recognise when some anomaly might be brewing, but an AI model would not
> A new artificial intelligence-based weather model can deliver 15-day forecasts with unrivaled accuracy and speed, a Google lab said, with potentially life-saving applications as climate change ramps up.<p>How hilariously dystopian. Instead of spending energy/power/influence to mitigate/solve/revert the problem, they’re actively making it worse to in the name of predicting how bad it’s going to be (to try and save themselves, which will ultimately fail).