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abbs

@abbygrace3866

3 months ago
Photo by abbs on July 23, 2026.
Photo by abbs on July 23, 2026.
Photo by abbs on July 23, 2026.
Photo by abbs on July 23, 2026.
Photo by abbs on July 23, 2026.
Photo by abbs on July 23, 2026.
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Posted On: July 24th 2026, 02:30 am
Tagged Users:
@melaniescott2006
melaniescott2006
@eraieo
eraieo
you’re djoking
Comments (25)
sophiemerritttt 3 months ago

sophiemerritttt

Djo appreciation 😩😩

g._ivy13 3 months ago

g._ivy13

beautiful

love_jillian_belcavitch 3 months ago

love_jillian_belcavitch

Jealous asf

megsie.2 3 months ago

megsie.2

MY FAV 😍😍😍😍

jordin_renninger_ 3 months ago

jordin_renninger_

What a beauty✋🏻😍

audrey.cain.09 3 months ago

audrey.cain.09

mom your so cute

gr.aviana 3 months ago

gr.aviana

oh hello gorgeous

graciecullison 3 months ago

graciecullison

caption is amazing

lily.el1zabeth 3 months ago

lily.el1zabeth

i'm in love with you.

lily.el1zabeth 3 months ago

lily.el1zabeth

MOTHERRRRRRRR

julie.wellerr 3 months ago

julie.wellerr

You're soo pretty!!!

melaniescott2006 3 months ago

melaniescott2006

truly the best night of my life with the LOVE of my life (you guys were there too!)

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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. Tap the 🔗 in bio to read the full story.
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