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Freeman Dyson - Fermi's rejection of our work (94/157)

Web of Stories - Life Stories of Remarkable People · 257.1K views · 2016-09-06 · 6:36

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Overview

Freeman Dyson recounts how Enrico Fermi rejected his team's meson scattering model, noting that it had too many free parameters. It is the source of the quote about fitting an elephant.

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Cited in modeling and machine learning threads as the classic story on overfitting and justifying parameters.

Recommended by 2 HN people across 1 months · HN mentions 2024–2025

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EdwardCoffin · 2024-07 · Recommendation

Freeman Dyson recounts the episode [1] that inspired this paper in his web of life interviews (prepositioned to the fitting an elephant bit) [2] [1] [VIDEO] [2] [VIDEO]

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Calavar · 2024-07 · Recommendation

> > In 1953, Enrico Fermi criticized Dyson’s model by quoting Johnny von Neumann: “With four parameters I can fit an elephant, and with five I can make him wiggle his trunk.” For those who are interested, you can watch Freeman Dyson recount this conversation in his own words in an interview: [VIDEO]

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godelski · 2025-11 · Reference

I think a lot of people are really bad at evaluating world models. Feifei is right here that they are multimodal but really they must codify a physics. I don't mean "physics" but "a physics". I also think it's naïve to think this can be done through data alone. I mean just ask a physicist...[0]. But why people are really bad at evaluating them is because the details dominate. What matters here is consistency. We need invariance to some things and equivariance to others. As evaluators we tend to be hopeful so the subtle changes frame to frame are overlooked though thats kinda the most important part. It can't just be similar to the last frame, but needs be exactly the same. You need equivariance to translation, yet that's still not happening in any of these models (and it's not a limitation of attention or transformers). You're just going to have a really hard time getting all this data even though by doing that you'll look like you're progressing because you're better fitting it. But in the end the models will need to create some compact formulation representing concepts such as motion. Or in other words, a physics. And it's not like physicists aren't know for being detail oriented and nitpicky over nuances. That is breed into then with good reason [0] [VIDEO]

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