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oliwia sierakowska

@oliwia.sierakowska

2 years ago

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Posted On: February 9th 2025, 01:08 pm

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which do you prefer?🧖🏼‍♀️🪞🎀

#thatgirl #thatgirlaesthetic #thatgirlroutine #thatgirllifestyle #morningroutine #skincare #morningskincare #skincareroutines #eveningroutine #nightroutine #MakeupRoutine

Comments (235)

dais.ysummmer

7 days ago

dais.ysummmer

Omg love the pink accents

fayeedew

7 days ago

fayeedew

Which serum do you use first

amourryayaa___

a month ago

amourryayaa___

Commenting to keep this algorithm

darciesheppard6

4 months ago

darciesheppard6

Pm all the way!🩰

lyelle.76856610

5 months ago

lyelle.76856610

Interest

bykatemov

5 months ago

bykatemov

Ofc night girl

anasa.london

6 months ago

anasa.london

perfect perfect perfect😍🩷🩷

christa.lysne

6 months ago

christa.lysne

Love this aesthetic

hersuccessnotes

10 months ago

hersuccessnotes

Evening routine > Morning Rotine

thelumea.store

10 months ago

thelumea.store

Exactly what I needed tonight 🤍”

discovernight

a year ago

discovernight

We have to get you some NIGHT for this routine 🌙

kkssu.beauty

a year ago

kkssu.beauty

😍😍😍

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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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