The Laude Institute named four university labs that will each receive $10 million for multi-year AI research, in a post dated 5 November: Stanford, Cornell, a joint UCSF and UC Berkeley team, and the University of Chicago. The National Science Foundation committed $17 million, and individual gifts from Jeff Dean, Sanjay Ghemawat, John Hennessy, Ben Gomes and Dave Patterson complete the funding, the post says.
Laude first committed to fund one $10 million lab, the post says; the total is now $40 million. The four winners came from 125 proposals, so about 3.2% of proposals became funded labs, by our arithmetic, and the NSF share is 42.5% of the $40 million.
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The key insight: As we read it, the program grew from one funded lab to four once public and private money joined: Laude committed to one $10 million lab, the NSF added $17 million and five individuals filled the rest, and 4 of 125 proposals, about 3.2%, became labs, by our arithmetic.
The post lists one winner per category: Workforce Reskilling, Stanford University; Strengthening Civic Discourse, Cornell University; Advancing Healthcare, UCSF and UC Berkeley; Accelerating Science, University of Chicago. “Each will receive $10 million for a multi-year lab”, and “all four decisions were unanimous”, it says.
Stanford’s team (Diyi Yang, Tatsunori Hashimoto, Chris Piech and Erik Brynjolfsson) studies how AI can help people learn new skills as work changes, the post says, using payroll-provider partnerships to track where jobs are emerging. Cornell’s team builds tools that let communities set rules for AI systems in their spaces and audit them, according to the post.
The UCSF and UC Berkeley team builds JupyterHealth, open infrastructure for data from wearables and medical records, the post says. The University of Chicago team, including Rebecca Willett, Ian Foster, Pedram Hassanzadeh and Michael Kremer, is developing AI weather forecasting for regions where reliable local information is scarce, such as when the monsoon arrives, the post says.
Laude Institute Moonshots // ONE: 125 proposals from more than 600 researchers at 47 institutions, eight finalist teams that received $250,000 each for six months, and four funded labs at $10 million each. Source: Laude Institute post, 5 November 2026. The 3.2% share and the NSF’s 42.5% of $40 million are our arithmetic.
What Was Posted on X
I’m delighted to partner with @LaudeInstitute (along with my @Sanjay_Ghemawat, John Hennessy, Dave Patterson, Ben Gomes and @andykonwinski) to support funding of open science moonshots!
Jeff Dean, who describes himself on X as a former chief scientist at Google, posted on 6 November that he is partnering with the Laude Institute, alongside Sanjay Ghemawat, John Hennessy, Dave Patterson, Ben Gomes and Andy Konwinski, to support funding of open science moonshots. The piece uses it for his part in funding the four labs.
anyone who is close to research knows how broken the incentives are. doing open science at the frontier is harder than ever, compute costs alone price most teams out. we kept wondering what might happen if we give the right resources to the right researchers at the right time
Andy Konwinski, one of the Laude post’s authors, posted on 5 November that compute costs alone price most teams out of open science at the frontier, and linked the announcement. The piece quotes it as the backers’ stated reason.
How the Money Was Raised
The post says that when the program launched, “Laude committed to funding one $10 million lab”. After the eight finalists were chosen, “NSF and a group of fellow technologists joined us, making it possible to back a team in every category”.
The NSF’s Directorate for Technology, Innovation, and Partnerships “committed $17 million to help fund labs in science, workforce reskilling, and healthcare”, according to the post. The gifts from the five individuals “complete the funding of these four labs”; the post does not give the split between Laude and the individual donors.
Dean, who describes himself on X as a former chief scientist at Google, posted on 6 November that he was “delighted to partner with @LaudeInstitute” to “support funding of open science moonshots”.
From 125 Proposals to Four Labs
The first call drew “125 proposals from more than 600 researchers across 47 institutions”, the post says. “Eight finalist teams received $250,000 apiece and six months” to build prototypes and make their case, which is $2 million for the finalist stage, by our arithmetic.
The four finalists that did not win labs, at UCLA, Carnegie Mellon, Harvard and MIT, and Stanford and Harvard, received seed grants, and there were 13 honorable mentions, according to the post. The selection committee included Jeff Dean, John Jumper, John Hennessy, Yejin Choi, Eric Horvitz and Thomas Wolf.
Why the Backers Say It Matters
Andy Konwinski, one of the post’s four authors, wrote on X on 5 November: “doing open science at the frontier is harder than ever, compute costs alone price most teams out”.
The post says the labs are expected to “ship: open software, useful tools, scientific advances, and evidence that their work is reaching people”. Ben Gomes said at the ceremony: “None of what exists today in Silicon Valley would exist were it not for the educational institutions that gave birth to it.”
As we read the post, the NSF is backing teams picked through a private selection process: the post says the agency put federal resources behind teams chosen through Laude’s process, with its own external review testing them.
As we read the funding split, the NSF supplies 42.5% of the $40 million by our arithmetic, and the post names it for three of the four labs (science, workforce reskilling and healthcare), not the civic-discourse lab.
As we read Konwinski’s post, the backers frame compute cost as the barrier for academic teams; the Laude post itself does not say how much of each lab’s $10 million goes to compute.
Andy Konwinski on X, 5 November 2026
“doing open science at the frontier is harder than ever, compute costs alone price most teams out”
Three Implications
FOR UNIVERSITY AI RESEARCHERS The first call funded 4 of 125 proposals as labs, and gave eight finalists $250,000 each for six months, the post says.
FOR PUBLIC RESEARCH FUNDING The NSF’s technology directorate committed $17 million to labs chosen through Laude’s process, according to the post.
FOR AI’S BUILDERS Five computing figures, including Jeff Dean, gave money to complete the funding of the four labs, the post says.
The framework says: “This entire ecosystem has been shaped by constraints, bottlenecks, chokepoints, and scarcity at every layer.”
As we read it, the Laude backers point to one such constraint for universities, the cost of compute, and answer it with money for a few labs. The framework does not discuss Laude, the NSF or these labs.
What Is Not Established
The post does not say how many years each lab will run, how much of each $10 million goes to compute, how the $23 million outside the NSF commitment splits between Laude and the five donors, or the size of the seed grants. It does not name compute providers.
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Four university AI labs will each get $10 million, the Laude Institute says, after Laude’s single planned lab grew to four with $17 million from the NSF and gifts from five computing figures including Jeff Dean. Four of 125 proposals, about 3.2%, became labs, by our arithmetic.
A note on sourcing. We read the Laude Institute post of 5 November 2026 in full on laude.org, and the X posts by Jeff Dean and Andy Konwinski, on 6 November 2026 between 11:50 and 12:05 UTC. The 3.2%, 42.5%, $2 million and $23 million figures are our arithmetic. Jeff Dean’s title is from his X profile. We did not contact the Laude Institute, the NSF or the donors.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
