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The Shift

How Do You Measure an A.I. Boom?

A chart created by METR, a nonprofit A.I. organization, has become an industrywide obsession as it measures the rapid development of big A.I. systems.

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METR’s chief executive, Beth Barnes, and its president, Chris Painter, at their Berkeley, Calif., office.

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Ulysses Ortega for The New York Times

By

Kevin Roose

Reporting from Berkeley, Calif.

April 17, 2026,

11:21 a.m. ET

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Behind every technological revolution is a chart with an exponential curve.

In the 20th century, microchip pioneers like Gordon Moore, the co-founder of Intel, saw the density of components on a computer chip doubling roughly every year, and predicted they would keep doubling every year for the foreseeable future. (This observation, which became known as “Moore’s Law,” fueled the boom in personal computing and held up for more than 50 years.)

During the internet boom of the early 2000s, Mary Meeker, an influential stock analyst, moved markets with her PowerPoint presentations showing the explosive growth of e-commerce, online advertising and mobile phones, all of which contributed to a sense that underneath all of the dot-com hype, something big and important was happening.

Today’s artificial intelligence boom is awash in data showing the rapid progress of A.I. systems, and hype-filled claims about what the technology can and can’t do.

But none of it has captured the public’s attention quite like a chart made by METR, an obscure 30-person nonprofit based in Berkeley, Calif.

This chart — often referred to as the “METR time-horizon” chart — has become a

discourse-dominating obsession

among A.I. researchers, Wall Street investors and industry watchers. They have studied it with Talmudic intensity, looking for signs that the A.I. boom is tapering off, or that it is accelerating, or merely that it confirms what they already believed was happening.

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METR’s time-horizon chart that has gotten so much attention.

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METR

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