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ESD

@egoonie

6 months ago
Photo by ESD on April 26, 2026.
Photo by ESD on April 26, 2026.
Photo by ESD on April 26, 2026.
Photo by ESD on April 26, 2026.
Photo by ESD on April 26, 2026.
Photo by ESD on April 26, 2026.
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Posted On: April 27th 2026, 01:46 am
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@dairy_lynn
dairy_lynn
Comments (36)
iam_uneek 6 months ago

iam_uneek

You look angelic Z 😍

_xoxonecole_ 6 months ago

_xoxonecole_

G 😍😍🫢🏽 so pretty

gabrielle.wright 6 months ago

gabrielle.wright

😍😍

iesha__domnick 6 months ago

iesha__domnick

You look soo cute πŸ₯°πŸ˜πŸ”₯

kortnemonet 6 months ago

kortnemonet

😍😍😍

__corcor 6 months ago

__corcor

😍😍😍

simonaeeee 6 months ago

simonaeeee

😍😍

iamhillarymarie 6 months ago

iamhillarymarie

😍😍😍😍😍😍😍

iraeee3 6 months ago

iraeee3

😍😍

allprayersneeded 6 months ago

allprayersneeded

You look so beautiful Missy!

lifeofafarmer 6 months ago

lifeofafarmer

A vision 😍😍😍

dairy_lynn 6 months ago

dairy_lynn

My girl !! 😍😍😍😘

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LinkΓΆping 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 β€œdead,” 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 β€œvery common” at the IEEE Symposium on Foundations of Computer Science, where his work will be presented by one of his coauthors. β€œPeople will start the talks: β€˜ETH is false, half of my paper does not work,’” he says. It’s a vexing problem, Jonsson says, β€œbut 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. Tap the πŸ”— in bio to read the full story.
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