StoryFirst seen
The claimed results would overturn a long-held belief about how fast hard logic puzzles can be solved.
Everything it touches
3 names 7 voices 10 source posts
The story’s neighborhood
Explore the graph, or choose a connection below.
Follow the evidence
This brief comes from Tech Twitter’s edited headlines. The posts below are the sources grouped with the story; statements in them belong to their authors.
Exponential Time Hypothesis (ETH), a 27-year-old conjecture in complexity theory, just fell. On Oct 16, OpenAI and Anthropic models independently solved 3-SAT with the same 2^(n/√log n) bound. Not P = NP, but faster than anyone thought possible. We live in extraordinary times.Read original on X
SITUATION DETECTED: OpenAI has announced three new discoveries in mathematics, computer science, and physics about harmonic analysis, complexity theory, and quantum field theory.Read original on X
OpenAI has announced to three new discoveries in mathematics, computer science, and physics: - Local smoothing and the Kakeya conjecture - The Exponential Time Hypothesis is false - Existence of quantum chromodynamics and completions of the Standard ModelRead original on X
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory). AI starting to help us improve our understanding of the universe!Read original on X
OpenAI seems to be experimenting with a new policy of releasing scientific findings. for physics and cs, they form external research groups. but for MATH, they just release the raw AI output for anyone to study, no external group of collaborators.Read original on X
INCREDIBLE detail from OpenAI’s latest discoveries: the two researchers who originally proposed the Exponential Time Hypothesis 25 years ago, are now leading a group to verify OpenAI’s proof that could DISPROVE their own conjecture.Read original on X
This is an incredible moment in this history of mathematics, computer science, physics & science with some of the hardest problems in human history being solved by AI over a period of weeks. Depending on your perspective, it's either a crisis, a triumph, or both. I don't think anyone knows for sure. We're all trying to make sense of it. I oscillate between fear/dread and optimism/excitement on a daily basis. The rate of progress is insane, including today's announcement from OpenAI of more problems solved. To help make sense of all of it, here's my conversation with three mathematicians about this moment. Each of them is an expert in the field of each of the biggest problems solved: Navier-Stokes, quasi-Riemann hypothesis, the unique games conjecture and complexity theory more generally.…Read original on X
This is extremely confusing, but an internal Claude research model also independently refuted the Exponential Time Hypothesis on October 16, with 14M output tokens and no human input. 'Anthropic researchers worked with Claude to improve the presentation, resulting in this paper.'Read original on X
SITUATION DETECTED: An Anthropic internal model also produced an independent refutation of the Exponential Time Hypothesis, it was discovered on October 16.Read original on X
Two professors spent 27 years as the guys whose guess an entire corner of computer science was built on. This month a machine proved the guess wrong, and the two of them got asked to grade its homework. Back in 1999, Russell Impagliazzo and Ramamohan Paturi at UC San Diego made a bet about a logic puzzle called 3-SAT. You've got a bunch of switches you can flip on or off, plus a long list of rules they all have to satisfy at once. Trying every combination means 2^n tries for n switches, so every switch you add doubles the work. People found ways to make that less brutal over the years, but their bet, the Exponential Time Hypothesis, said it would always stay exponential. Computer scientists treated it like a law of physics. Hundreds of papers proving that problems like map coloring and…Read original on X
Decades-old complexity conjecture falls to OpenAI and Anthropic models
OpenAI and Anthropic models each disprove a decades-old complexity conjecture
OpenAI and Anthropic models each claim to refute a complexity conjecture
Shared connections
It would be a second AI lab claiming a result against the same decades-old complexity conjecture.
One claimed result would show the Exponential Time Hypothesis is false, a central conjecture in complexity theory.
Businesses can automate more office work when a cheaper model scores the same on real tasks.
Price cuts are pulling large AI spending contracts away from Anthropic and intensifying competition between the labs.