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Petra 🧚🏾‍♀️

@pthestalli

2 months ago

Photo by Petra 🧚🏾‍♀️ on August 31, 2026. May be an image of one or more people, makeup, people smiling and text.

Photo by Petra 🧚🏾‍♀️ on August 31, 2026. May be an image of text.

Photo by Petra 🧚🏾‍♀️ on August 31, 2026. May be an image of one or more people, makeup, eyeliner and text.

Photo by Petra 🧚🏾‍♀️ on August 31, 2026. May be an image of shellfish, escargot, oyster and text.

Photo by Petra 🧚🏾‍♀️ on August 31, 2026. May be an image of wine, wine glass and text.

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Posted On: August 31st 2026, 03:30 pm

wine, pasta and good company 🍝

Comments (11)

bina_luv

2 months ago

bina_luv

SISSY LOVE 💕

elatedcole

2 months ago

elatedcole

Gorgeous gorgeous girl!😍😍😍

danaremii

2 months ago

danaremii

😍😍😍

zeeboo_00

2 months ago

zeeboo_00

😍

ashacee

2 months ago

ashacee

Gorgeous 😍

freemagrandma

2 months ago

freemagrandma

First pic my favorite one

befitangels_

2 months ago

befitangels_

😍😍

More posts

I made seafood boil! How can it not be tasty with so much butter, garlic, and old bay 😝
#mealprepideas #costco #seafoodboil

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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