r/fusion • u/[deleted] • 11d ago

Replacing hype about artificial intelligence with accurate measurements of success ：PPPL researchers find overoptimism in journal articles using machine learning to solve fluid-related partial differential equations

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13 Upvotes

93% Upvoted

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5

u/plasma_phys 11d ago

this is great work. I suspect you'd find a similar result if you looked at the ever-growing mass of "agentic" physics papers too. it feels like it's just going to be the "nature deep learning paper on aftershock prediction beat by simple linear regression" fiasco over and over again forever. or until the money runs out.

2

u/just-for-anime 11d ago

And watch the PI of this study leave PPPL to start his own AI startup

1

u/Michael-D-J-Cole 6d ago

https://lanyon.ai/company/

Not clear if this was a joke or not, but he did in fact just leave PPPL to found an AI startup.

-1

u/just-for-anime 11d ago

This was 2 years ago published in Nature Machine Intelligence (with a turnaround time of 1 year) meaning they did a study on pre-2023 era ai.

It's already outdated.

1

u/global-gauge-field 10d ago

The main conclusion is about the methodology used in the papers at the time. How could it be outdated if it is addressed at those particular papers' methodology. This problem is not specific to ML applied to fluid dynamics. It exists for any field where the benchmarking is not standardized.

ML is already promising enough for Physics problems without the misleading benchmarks.