Simons Institute for the Theory of Computing

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[Simons Institute for the Theory of Computing @SimonsInstitute]

3/3 For example, OpenAI's Astra 6.1, when prompted to place 31 Stanford tree mascots in front Sather Gate in Berkeley, produced an image with 33 mascots, and a misplaced Campanile behind the gate. "Geographically, it's not possible," said Mahdi Soltanolkotabi of @USC.

[Simons Institute for the Theory of Computing @SimonsInstitute]

1/ 3 "The progress in reasoning models has been really crazy recently...But the frontier is quite jagged. Despite all of this progress, there are some very weird shortcomings that still exist, even in the latest models," said Mahdi Soltanolkotabi of @USC at the Simons Institute.

[Simons Institute for the Theory of Computing @SimonsInstitute]

2/3 "If you have simple, visual reasoning questions...the models tend to get them wrong," said Mahdi Soltanolkotabi of @USC at the Simons Institute workshop on Trustworthy AI: From Hallucinations to Reliable Autonomy. Video: https://t.co/MkD4WFGqcx

[Simons Institute for the Theory of Computing @SimonsInstitute]

2/2 Their task: to discuss the immediate future of theoretical computer science in light of the challenges posed by AI. Read a report of that closed-door meeting, in the Polynomial Times (see Theoretical Computer Science Meets Its AI Moment, page 3): https://t.co/zMXmxcSKWj

[Simons Institute for the Theory of Computing @SimonsInstitute]

1/2 The day after OpenAI dropped a bombshell about "a solution to the Navier–Stokes existence and smoothness problem," 32 theoretical computer scientists met for a closed door meeting (that had been planned for months) at the Simons Institute for the Theory of Computing.

[Simons Institute for the Theory of Computing @SimonsInstitute]

2/2 Their task: to discuss the immediate future of theoretical computer science in light of the challenges posed by AI. Read a report of that closed-door meeting, in the Polynomial Times (see Theoretical Computer Science Meets Its AI Moment, page 3): https://t.co/zMXmxcSKWj

[Simons Institute for the Theory of Computing @SimonsInstitute]

1/2 The day after OpenAI dropped a bombshell about "a solution to the Navier–Stokes existence and smoothness problem," 32 theoretical computer scientists met for a closed door meeting (that had been planned for months) at the Simons Institute for the Theory of Computing.

[Simons Institute for the Theory of Computing @SimonsInstitute]

Join us for two special events this month:

Quantum Industry Day | Wednesday, 11/18
https://t.co/9WlBZhuTct

Industry Day | Thursday, 11/19
https://t.co/pEBxSRtxUB

Space is limited, so register early!

[Simons Institute for the Theory of Computing @SimonsInstitute]

Join us!

https://t.co/VudqYqypsF

[Simons Institute for the Theory of Computing @SimonsInstitute]

Our earlier post should have mentioned that @AnthropicAI announced on the same day that it had independently disproven ETH.

More coverage: https://t.co/RIzLN8IVKr

[Simons Institute for the Theory of Computing @SimonsInstitute]

@nytimes story out today on the OpenAI breakthrough on the Exponential Time Hypothesis, featuring our friends @RussellImpaglia and @rrwilliams.

https://t.co/0NW3DR5xaB

[Simons Institute for the Theory of Computing @SimonsInstitute]

“Immediate, practical applications? There aren’t any,” Dr. Williams said.

“This could lead to better A.I.,” Dr. Impagliazzo said, “in all sorts of ways.”

[Simons Institute for the Theory of Computing @SimonsInstitute]

Congratulations to our senior scientist, @jasondeanlee and all the other worthy recipients!

[Berkeley Computing, Data Science, and Society @BerkeleyCDSS]

Congratulations to the nine faculty receiving CDSS Machine Learning Research Awards! @UCBStatistics @Berkeley_EECS
@Cal_Engineer @UCBerkeley

🔗 Read more: https://t.co/NZ8LlMncw0

#MachineLearning #Statistics #ComputerScience #ResearchAwards #PeopleOfCDSS

[Anil Ananthaswamy @anilananth]

Theoretical Computer Science Meets Its AI Moment

The day after OpenAI dropped a bombshell about "a solution to the Navier–Stokes existence and
smoothness problem," 32 theoretical computer scientists met for a 2-day closed door meeting (that had been planned for months) at the Simons Institute for the Theory of Computing, to discuss and debate their field's response to AI. In this issue of the @SimonsInstitute's annual magazine, Polynomial Times, is my report of that meeting. Read the article and the entire issue here: https://t.co/AE4ufScFk9

[Simons Institute for the Theory of Computing @SimonsInstitute]

Hot off the press, this year's issue of Polynomial Times, our annual magazine!

Read online: https://t.co/zMXmxcSKWj

Download: https://t.co/iweizUQyMn

[Lakshmi Chandrasekaran, PhD (she/her) @science_eye]

Here's my latest on the increasing gaps between open-weight and frontier #AI models revealed in the #1stproof third batch results, announced earlier this week: https://t.co/47vPamRZYk

[Simons Institute for the Theory of Computing @SimonsInstitute]

We're delighted to have received a grant from @RenPhilanthropy and @xtxmarkets to create a Research Pod on AI for TCS.

In connection with this new initiative, we're advertising two new postdoctoral fellowships on the intersections of AI and TCS.

https://t.co/YyikMm9fma

[Simons Institute for the Theory of Computing @SimonsInstitute]

3/3 "Causality gives us a very, very easy way to see that this is actually very dangerous," said Pradeep Ravikumar of @CarnegieMellon at the Simons Institute. Video: https://t.co/Ds42upRBky

[Simons Institute for the Theory of Computing @SimonsInstitute]

1/3 What aspects of a large language model are actually determined by the training data itself? "This might seem like a nonsensical question...[But] not all aspects of your model are determined by the data," said Pradeep Ravikumar of @CarnegieMellon at the Simons Institute.

[Simons Institute for the Theory of Computing @SimonsInstitute]

2/3 Certain aspects of an LLM could be determined by something as random as random seeds. "Do we really want that? We don’t," said Pradeep Ravikumar of @CarnegieMellon at the Simons Institute workshop on Trustworthy AI: From Hallucinations to Reliable Autonomy.