Enrico Fermi — "I remember my friend Johnny von Neumann used to say, 'with four parameters I can…"
I remember my friend Johnny von Neumann used to say, 'with four parameters I can fit an elephant and with five I can make him wiggle his trunk.'
I remember my friend Johnny von Neumann used to say, 'with four parameters I can fit an elephant and with five I can make him wiggle his trunk.'
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"The greatest discovery of all time was made by accident."
"The history of science is full of examples of people who thought they knew everything, and then discovered that they knew very little."
"My father used to say that the only way to learn something is to make mistakes, and then learn from them."
"The future is uncertain, but it is also full of possibilities."
"Where are they? (Referring to extraterrestrial intelligence)"
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A warning against overfitting: pile enough free parameters into any mathematical model and it will match your data perfectly—without revealing anything true about the underlying system. The quote remains a cornerstone of modern machine learning and statistical modeling, reminding practitioners that a curve fitting an elephant's outline tells you nothing about elephants, only about the flexibility—and danger—of unconstrained mathematical freedom.
Fermi built his legendary reputation on radical simplicity—his famous 'Fermi estimation' technique produced astonishing accuracy from minimal inputs. He distrusted elaborate theoretical scaffolding disconnected from physical reality. As architect of the first nuclear reactor and a Manhattan Project pillar, he relied on physical intuition, not parameter-heavy fits. Quoting von Neumann here is characteristic: Fermi collected sharp insights from brilliant colleagues and wielded them as precision tools.
Fermi worked in the mid-20th century when physicists were simultaneously building the first computers and the first nuclear weapons. Von Neumann was designing early stored-program computers and mathematical game theory alongside him. Scientists were grappling with how to extract genuine physical laws from increasingly complex equations. Overfitting wasn't yet a formal statistical concept—this quip was an early, intuitive articulation of what the field wouldn't fully formalize for decades.
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