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Launch HN: Silurian (YC S24) – Simulate the Earth

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11–20 of 156 posts

Re: Launch HN: Silurian (YC S24) – Simulate the Earth

#11
Can we help you? We build the equivalent for land, as a non-profit. It's basically a geo Transformer MAE model (plus DINO, plus matrioska, plus ...), but largest and most trained (35 trillion pixels roughly). Most importantly fully open source and open license. I'd love to help you replace land masks with land embeddings, they should significantly help downscale the local effects (e.g. forest versus city) that afaik most weather forecast simplify with static land cover classes at most. https://github.com/Clay-foundation/model

Re: Launch HN: Silurian (YC S24) – Simulate the Earth

#12

> Astonishingly, this approach, done correctly, produces better forecasts than traditional simulations of the physics of our atmosphere. It seems like this is another instance of The Bitter Lesson, no?

I'm not sure I buy The Bitter Lesson, tbh.

Deep Blue wasn't a brute-force search. It did rely on heuristics and human knowledge of the domain to prune search paths. We've always known we could brute-force search the entire space but weren't satisfied with waiting until the heat death of the universe for the chance at an answer.

The advances in machine learning do use various heuristics and techniques to solve particular engineering challenges in order to solve more general problems. It hasn't all come down to Moore's Law.. which stopped bearing large fruit some time ago.

However that still comes at a cost. It requires a lot of GPUs, land, energy, and fresh water, and Freon for cooling. We'd prefer to use less of these resources if possible while still getting answers in a reasonable amount of time.

Re: Launch HN: Silurian (YC S24) – Simulate the Earth

#14

> Astonishingly, this approach, done correctly, produces better forecasts than traditional simulations of the physics of our atmosphere. It seems like this is another instance of The Bitter Lesson, no?

Yes, it seems like it. Although I would imagine the features and architecture of the model still take some physics into account. You can't just feed weather data into an LLM, after all.

Re: Launch HN: Silurian (YC S24) – Simulate the Earth

#17

This is awesome - how does this compare to the model that Google released last year, GraphCast?

Hi, Nikhil here. We haven't done a head-to-head comparison of GFT vs GraphCast, but our internal metrics show GFT improves on Aurora and published metrics show Aurora improves on GraphCast. You can see some technical details in section 6 of the Aurora paper (https://arxiv.org/pdf/2405.13063)

Re: Launch HN: Silurian (YC S24) – Simulate the Earth

#19

This really, really looks like a nullschool clone ( https://earth.nullschool.net/ ). Is it not?

Hi, it totally is. That's one of our favorite weather visualization projects. We're using Cameron Beccario's open source version of nullschool for our forecasts. We cited him above in the blurb and also on our about page (https://hurricanes2024.silurian.ai/about.html)

Re: Launch HN: Silurian (YC S24) – Simulate the Earth

#20

This really, really looks like a nullschool clone ( https://earth.nullschool.net/ ). Is it not?

> We visualize these using [cambecc/earth] (https://github.com/cambecc/earth), one of our favorite open source weather visualization tools

From the post.

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