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Neftchi 🏆 Alisher

@vodiychasi

2 days ago

Co Creator:

islomelectro

126

29

Posted On: November 3rd 2026, 07:47 am

Tagged Users:

@islomelectro

Hammaga rahmat akalar

Comments (29)

yonkischi_bola

a day ago

yonkischi_bola

Man uchun har doim Nefchi nomer adin

ra_vshan2580

2 days ago

ra_vshan2580

😂😂😂😂😂

ra_vshan2580

2 days ago

ra_vshan2580

comment media

isakov8421

2 days ago

isakov8421

Ёриб ташлаши керак эди

akbar506430

2 days ago

akbar506430

azodjon1

2 days ago

azodjon1

Ёнида туравиринг 😂😂😂😂😂 10 киши

nasimboy_boymirzayev

2 days ago

nasimboy_boymirzayev

Нефчига омад тилаб коламиз зур уйнади Навбахордан 🔥

soibovavazbek878

2 days ago

soibovavazbek878

🔥🔥🔥🔥🔥✊✊✊✊✊✊

temurxonmirzayev

2 days ago

temurxonmirzayev

Inshaalloh Neftchi chempion❤️❤️❤️❤️👏

azimxonxabibullayev1

2 days ago

azimxonxabibullayev1

🔥🔥

yoqibjanov_80

2 days ago

yoqibjanov_80

Nefchi uyini yondirdi Navbaxor nomida omad👏

abdusalom.1414

2 days ago

abdusalom.1414

Ойин 10 киши билан тенг ойнайшти 😂

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Linköping University professor Peter Jonsson is set to have his work presented in two weeks’ time at one of the most prestigious conferences in theoretical computer science. As of Monday, much of that work is “dead,” he says, after AI showed that a 27-year-old hypothesis underpinning it is wrong.

Both OpenAI and Anthropic claimed this week to have disproved the exponential time hypothesis (ETH). Vast swaths of theoretical computer science research on complexity and algorithm design have been built on the premise that the effort it takes to solve certain problems increases exponentially with the size of the problem.

Jonsson expects his predicament will be “very common” at the IEEE Symposium on Foundations of Computer Science, where his work will be presented by one of his coauthors. “People will start the talks: ‘ETH is false, half of my paper does not work,’” he says. It’s a vexing problem, Jonsson says, “but at the same time, we learn a lot from it. And this is what science is about.”

Researchers haven’t independently verified, let alone had time to fully understand, the AI-produced proofs, which both firms have published on GitHub in both natural language and its machine-checkable Lean format. OpenAI has asked the UC Santa Barbara computer scientists who originally proposed the hypothesis, plus an MIT academic who has refuted a version of ETH, to rally researchers to unpack the proofs. So far, this effort includes a Google form asking for volunteers and feedback, and a commitment from OpenAI to fund a conference on the topic.

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