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HappyIndividual- t1_j290na4 wrote

This will be awesome a year or two down the line, knowing exactly the weather in the short, medium, and long term would be immensely useful when planning trips.

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Kaarssteun t1_j292qsy wrote

Weather forecasting is one of those fields where I expected advances to be negligible due to two things: Sheer amount of time already spent on it, and the butterfly effect. Happy to see Deepmind doing their thing and proving me wrong again.

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Umbristopheles t1_j2937l3 wrote

Oh man. The next few years are going to be insane. We can't even imagine.

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Utoko t1_j29abaq wrote

That is exactly the field where machine learning shines when you have too many variables to account for every small one everywhere.

and we have already very good data as input for it.

Weatherforcast has a giant network of clean data which was just waiting to be used.

For FSD training for example it is different they are slowly building good data.

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Dreddnaught619 t1_j29dipf wrote

If it can accurately predict the weather in the South of England I'll eat my hat.

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lennarn t1_j29sm34 wrote

It is nice to see new research on graph neural nets, but I don't quite understand how they work. Is the propagation of data between the nodes analogous to convolution?

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Martholomeow t1_j29xjae wrote

outperforming the current system isn’t saying much. the weather forecast is always wrong.

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nyc_brand t1_j29yq3s wrote

Deep neural nets are shaping up to be the most important invention this century. Mind blowing.

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RobLocksta t1_j2a4klu wrote

I've been on this sub for a while but I still struggle to understand the terminology regarding the specific approaches to AI (neural nets, machine learning, transformers, etc.) Would you mind expanding your answer on deep neural nets and their importance? Or maybe recommend a good online resource? I'd love to learn more about them.

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RobLocksta t1_j2adr2j wrote

Thank you! I thoroughly enjoyed that! Need to watch that a couple of times. But I'm a sql developer so the idea of parameters and functions isn't new to me. I'm going to check out some more of that YouTube channel.

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visarga t1_j2awwsp wrote

No, the GP was right, neural nets are not especially suited for this kind of data, it's too large and random. That's why they use graph neural nets, to sparsify the input.

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sideways t1_j2azfiw wrote

Really interesting how DeepMind is approaching applied AI compared to OpenAI.

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5ur3540t t1_j2b6ng6 wrote

I’ll take a direct feed of data from that please

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RodgerRodger90 t1_j2bjh4c wrote

“Amazing. Absolutely amazing. Too bad the Post Office isn’t as efficient as the Weather Service.”

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No_Ninja3309_NoNoYes t1_j2d0gho wrote

Yes, that is amazing, but why did they only use one type of hardware? Or am I missing something?

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benefitsofdoubt t1_j2db96a wrote

Strongly recommend fast.ai- it’s a very accessible course for machine learning and it’s completely free- and in the process they dive into this stuff. It’s mostly made up of videos that anyone with some technical background will be able to understand

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Numb_Nut t1_j2egflb wrote

Is there a demo of graphcast so we can see its forecast wonders? Has Google any weather service that I don't know about?

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