[OpenAI Announces Falsification of the Over-20-Year-Old Key Computer Science Theory: The Exponential Time Hypothesis (ETH)] BlockBeats reported on October 27th that OpenAI announced its AI model has "cracked" ETH—a piece of news that quickly sparked heated discussions in the tech and crypto communities. However, it's important to clarify that the ETH here is not the well-known cryptocurrency Ethereum, but rather a key conjecture in computer science that has existed for over two decades: the Exponential Time Hypothesis (ETH). The core question of the Exponential Time Hypothesis is: just how difficult are those problems that seem "particularly difficult to calculate"? Take the "SAT problem" (Boolean satisfiability problem), which some may have heard of, as an example. It asks: given a set of logical conditions, can you find an assignment that makes all conditions true simultaneously? When the problem size increases, the best known approach essentially requires trying every possible answer one by one, and the time cost grows exponentially with the size of the problem—the so-called "exponential time." ETH further asserts that these types of problems cannot be significantly accelerated in essence, and that there is no truly efficient algorithm in "sub-exponential time." This assumption, since its inception in 1999, has been a cornerstone of theoretical computer science. Hundreds of papers have used it to prove that "a certain problem is difficult" and "a certain algorithm is close to optimal." If ETH's assertion is overturned, it means that many problems we thought were "almost impossible to speed up" might theoretically have better solutions. OpenAI claims that its model has found a deterministic algorithm that can accurately count the number of solutions to the k-SAT problem in sub-exponential time, and has formally verified this using Lean. If this result ultimately withstands expert scrutiny, it will directly shake the exponential time assumption.