OpenAI disproves Exponential Time Hypothesis, co-proposer Impagliazzo calls it "shocking news"
OpenAI has disproved the Exponential Time Hypothesis, a longstanding conjecture that some problems would always be hard for computers to solve quickly. Co-proposer Russell Impagliazzo called the result "shocking news," the New York Times reports.
OpenAI has disproved the Exponential Time Hypothesis, and one of the hypothesis's co-proposers, Russell Impagliazzo, calls the result "shocking news," according to a New York Times report by Cade Metz published November 6, 2026.
What the report says
The Exponential Time Hypothesis held that some problems would always be hard for computers to solve quickly. Impagliazzo, who co-proposed the hypothesis, described OpenAI's disproof as "shocking news."
The Times reports that the result could one day speed up chip design and break encryption. The framing is prospective: the report says "one day," not that either application is available now.
Details not yet available
This article draws on a short summary of the Times report. Technical specifics of the disproof, including the method used and the model involved, are not covered here. Benchmark scores, model names, pricing and context window figures are likewise not part of this summary.
What this means
The Exponential Time Hypothesis is described in the report as a longstanding assumption about which problems computers can solve quickly. A disproof from OpenAI, with a hypothesis co-proposer calling it "shocking news," is a notable reaction from inside the field that originated the conjecture. According to the Times, the potential downstream applications are faster chip design and breaking encryption, though the report frames both as possible future outcomes.
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