Join us for a special workshop on Governance at the Technological Frontier: Translating Research into Policy for AI Oversight.
Keynotes by California State Senator Jerry McNerney and Suresh Venkatasubramanian.
Thursday, 4/30, 1–5:30 p.m. Registration required.
simons.berkeley.edu/workshops/go...
3/3 Misha Belkin of @ucsandiego.bsky.social spoke at the Simons Institute workshop on Theoretical Foundations: From the Early Days of Neural Networks to the Modern Deep Learning Era, celebrating Peter Bartlett's birthday and decades of work in machine learning. www.youtube.com/live/xgaZPTG...
2/3 "If you look carefully at the perceptron, a lot of modern machine learning just kind of appears, maybe sometimes even in a fairly explicit form," said Misha Belkin of @ucsandiego.bsky.social. In retrospect, it justified the 1958 NY Times claim that the perceptron was the embryo of modern ML.
1/3 In 1958, the NY Times wrote about Frank Rosenblatt's perceptron, as an "embryo of computer designed to read and grow wiser." @ucsandiego.bsky.social's Misha Belkin examined this astonishing claim and came to a surprising conclusion, at a Simons Institute workshop honoring Peter Bartlett's work
"Can AI assist in Mathematics and Computer Science research?"
Berkeley EECS Colloquium
Prabhakar Raghavan, Chief Technologist, Google
4 – 5 p.m., Wed., April 15
Banatao Auditorium, Sutardja Dai Hall
eecs.berkeley.edu/research/col...
Next week at the Simons Institute, a workshop on Agency in Collaborative Learning. Join us!
simons.berkeley.edu/workshops/ag...
Congratulations to our friend and colleague @matei-zaharia.bsky.social on being awarded the ACM Prize in Computing!
Thursday and Friday this week, a workshop on Theoretical Foundations: From the Early Days of Neural Networks to the Modern Deep Learning Era, celebrating Peter Bartlett's 60th birthday.
simons.berkeley.edu/workshops/th...
We're thrilled that our short doc, "Until the Sun Engulfs the Earth: Lower Bounds in Computational Complexity," is featured in mathēmatiká, the April issue of Labocine.
www.labocine.com
The call for Winter Vacation Research Internships (VRI) in CS at #USyd is out! Open to students (undergrads and postgrads) currently enrolled in an 🇦🇺 uni.
Have a look! Apply by April 19.
www.sydney.edu.au/engineering/...
(Want to work with me? Check out CS2026/9, CS2026/10, CS2026/38, CS2026/39)
In this episode of The New Quantum Era podcast, Simons Institute Quantum Pod postdoc Dominik Hangleiter maps the path toward verifiable quantum advantage.
www.newquantumera.com/podcast/quan...
Theoretical Foundations: From the Early Days of Neural Networks to the Modern Deep Learning Era
Thursday, Apr. 9 – Friday, Apr. 10
Join us!
simons.berkeley.edu/workshops/th...
Great series of blog posts on quantum advantage by Dominik Hangleiter, one of the postdocs in our Quantum Research Pod.
quantumfrontiers.com/2026/01/06/h...
#simonsquantum
Next week at the Simons Institute, a workshop on Trust in Decentralized Systems. Register to attend in person or view the livestream. Hope to see you there!
simons.berkeley.edu/workshops/tr...
4/4 If you ask an LLM to categorize a movie review, you implicitly give it the task & the review and get the answer in one go, said Matthew McDermott of @columbiauniversity.bsky.social, at the Simons Institute workshop on Theory of Computing and Healthcare simons.berkeley.edu/talks/matthe...
3/4 A foundation model "takes in both the data and the task and predicts a label specific for that task...This is exactly how we use the best examples of foundation models today, which are language models," said Matthew McDermott of @columbiauniversity.bsky.social, at the Simons Institute.
2/4 For a single task, an ML model transforms an input x into an output y, via some function g. For foundation models, we need to know the space of all possible tasks. "We need a notion of a task set," said Matthew McDermott of @columbiauniversity.bsky.social, at the Simons Institute.
1/4 Foundation Models: "We don't really know what we should expect [the phrase] to mean...and this causes real challenges," said Matthew McDermott of @columbiauniversity.bsky.social, at the Simons Institute workshop on Theory of Computing and Healthcare. We need a formal definition, he said.
From our friends at Berkeley Math.
math.berkeley.edu/about/events...
2/2 Ken Rothman spoke of the history of, and the right way to do epidemiology, arguing that "computing technology is not really a fundamental necessity for epidemiology research," at the Simons Institute workshop on Theory of Computing and Healthcare. Video: simons.berkeley.edu/talks/ken-ro...
1/2 Ken Rothman of @bostonu.bsky.social began his Distinguished Lecture at the Simons Institute on "Epidemiology is Easy – Anyone Can Do It" with a caveat: “Anyone can attempt to do it but doesn’t always work out that well.” He spoke at the workshop on Theory of Computing and Healthcare.
2/2 "Most of the interesting computations that happen today are in some way or another computations that happen on individuals’ potentially sensitive data," said Katrina Ligett of HUJI at the Simons Institute workshop on Theory of Computing and Healthcare. simons.berkeley.edu/talks/katrin...
1/2 "There is sort of an obligation on the part of somebody who spends a lot of time thinking about privacy to open with the bad news," said Katrina Ligett of HUJI, talking about Research on Sensitive Data at the Simons Institute workshop on Theory of Computing and Healthcare.
Join us at 3:30 p.m. PT. Register to attend or access the livestream.
simons.berkeley.edu/events/respo...
3/3 "Current training recipe doesn't really support fragmented data," said Sewon Min of @ucberkeleyofficial.bsky.social at the Simons Institute workshop on Federated and Collaborative Learning Boot Camp. Video: youtu.be/vmt2_LZ8zgI?...
2/3 One reason neural scaling laws might stall is because data is getting fragmented. "I’m talking about proprietary datasets, where datasets are owned by different owners...that cannot be gathered into a central location," said Sewon Min of @ucberkeleyofficial.bsky.social at the Simons Institute.
1/3 Will increasing compute and training data continue to improve performance of foundation models? Maybe. "I’m interested in asking: if it’s not the case, then why?" said Sewon Min of @ucberkeleyofficial.bsky.social at the Simons Institute workshop on Federated and Collaborative Learning Boot Camp
#FlashbackFriday
www.youtube.com/watch?v=soQR...
#FlashbackFriday
ls.berkeley.edu/news/uc-berk...