Study work with AI + robots. @MITSloan PhD, @Ucsb Assc Prof, @Stanford fellow, @tedtalks, @skillbenchinc cofounder, CEO Book: https://xitter.cf/t.co/OJQa0by9MT

Santa Barbara, CA
Joined November 2008
I'm so grateful and exited to share that my book will be published on June 11th! It's called "The Skill Code: How to Save Human Ability in an Age of Intelligent Machines" Available for preorder now, here's a bit of the story: wildworldofwork.org/p/big-in…
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Gemini 4 Carbon is our next frontier model. It’s state-of-the-art across cybersecurity and long-horizon capabilities.
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Matt Beane retweeted
Great work. The problem of "can AI propose interesting new questions rather than just answer open ones" is key to AI for science. Less hill climbable though of course not impossible...
AI is now taking on some of the hardest open problems that scientists have posed. But research is broader than solving problems. Can AI also propose research questions that experts find genuinely interesting? We built After42 to find out. Experts judged 45 of its 135 final questions genuinely interesting, across mathematics, statistics, theoretical computer science, and physics, with wide variation across subfields. The key idea: develop questions by trying to solve them. We also asked whether AI can judge which questions are interesting. We find that model judges' top choices align with expert consensus but do not consistently capture individual experts' preferences. We release the expert-assessed questions as an open resource for researchers to discuss, refine, and pursue, as a step toward integrating AI into the broader research enterprise. after42.org
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Matt Beane retweeted
Ok, I stopped work on this AI creativity "ideator" and dropped in on Git. All of these render in browser with no run-time AI. The goal: a scaffold for super high-variance AI for creative work, to "unlock creativity", as an experiment for AI+human science. 1/2
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Wait wait. Quite odd to offer a raft of (great) advice to junior devs when Anthropic has gone from 23% to 7% juniors recently? Those left standing are newly valuable, cool, but the volume drop means we don't grow enough expertise for the economy: theskillcodebook.com
The coding interview is dead, at least for my team at Anthropic. I've seen enough to know that it no longer provides signal. I removed it from loops this month. I have a spicy, optimistic take - I think there's an opportunity for junior engineers: felixrieseberg.com/hunger-be…
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The coding interview is dead, at least for my team at Anthropic. I've seen enough to know that it no longer provides signal. I removed it from loops this month. I have a spicy, optimistic take - I think there's an opportunity for junior engineers: felixrieseberg.com/hunger-be…
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NSF is establishing a new Office of Metascience to study existing practices, test new approaches, and translate evidence into improvements in how NSF supports scientific discovery to achieve broad impact. Learn more: brnw.ch/21x6HUf
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Matt Beane retweeted
Five years ago, Miles Arnone, Will Barker and I started Re:Build because we believed deindustrialization was an economic failure and a national security risk. Today we announced $2.1B in new funding, led by General Catalyst and JPMorganChase’s Strategic Investment Group. Our mission is to ensure the next generation of important products are made, at scale, in America.
$2.1 billion in new capital to ensure the next generation of important products are made, at scale, in America. Led by @generalcatalyst + @jpmorgan. Covered today in @dealbook.
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They predicted, desired, and shaped. SV VCs read Kurzweil (Jurvetson is open about this) and set about making bets on the underlying trends. Those bets bent the arc of history. Not placing a value judgement on this. But it's not as if they are separable from the AI wave.
Given how out-of-nowhere it seems to many, it is astonishing that there was a small group of people who predicted with remarkable accuracy everything that is happening in AI today a decade ago (@kevinroose shows this in The AGI Chronicles). Many are now very rich and/or powerful
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Matt Beane retweeted
SITUATION EXPLAINED: A months-old startup founded by ex-DOGE staffers used AI agents to break into Anthropic in under 12 hours. • Cathedral found paths to Anthropic's meeting transcripts, salary and job-offer details, and Slack messages about its advanced models • It got in through weaknesses in third-party business software, after days of failing to break into Anthropic directly • Anthropic says no customer prompts, Claude responses, source code, or model weights were touched, and it cut off access the same day • The test was authorized under Anthropic's bug bounty program, but Anthropic says Cathedral didn't disclose all of its activity • Cathedral is valued at $1.4B with backing from a16z and Sequoia, and 3 federal agencies already contract with it • Its co-founders include Luke Farritor, who helped decode the ancient Herculaneum scrolls with AI @theojaffee: "If a bunch of kids who have just started a company can do this, then potentially the Chinese aren't far behind. Aren't far behind? If anything, they're far ahead."
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Matt Beane retweeted
This never gets old (& also shows how hard forecasting AI is even for AI) “Hey Claude Fable & GPT-6 Astra, Without looking anything up, when do you think we will solve the Exponential Time Hypothesis?” (I only show part of the answers for space)
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Just in time for the end of the day: this week's "wow". As in - WOW. Any field that isn't empirical - math, physics, cs, even some chemistry, biology... is subject to this new dynamic. Huge. Remember - the transformers paper was "just math and cs" and allowed for LLMs.
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory). AI starting to help us improve our understanding of the universe! openai.com/index/building-sc…
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On bottlenecks: 1) economists have been exactly right about little extra growth despite very fast tech change. They thought a group of econs I organized were crazy >2 yrs ago at the AI labs when we said "1pp extra growth/yr through 2030". 2) bottlenecks *still* not understood 1/8
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Matt Beane retweeted
While evaluating Qwen3.8-Flash-Next in a controlled sandbox environment, Cohere's research team observed something unexpected. Asked to generate a defensive cybersecurity detection rule, the model instead inventoried aspects of the machine it was running on and attempted to upload a probe file to an Alibaba Cloud storage bucket in Beijing. Notably, the model's reasoning trace stated that it would not invoke any tools before taking these actions. Cohere's sandbox blocked the attempt, and no external communication succeeded. We have not determined the root cause, and we are not asserting malicious intent. But the incident raises important questions for organizations deploying agentic AI systems: Can models take actions that differ from their stated reasoning, and how should security teams evaluate trust, provenance, and behavior in open-weight models? We are publishing our findings because organizations making model adoption decisions deserve as much information as possible. We hope this contributes to greater transparency, stronger security practices, and continued collaboration across the AI ecosystem. Read the full report: cohere.com/blog/concerning-b…
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Agreed. Read this this morning. Very helpful! The returns to attention are skyrocketing in ways that are increasingly independent of our personal intelligence.
The best, most comprehensive take on AI I’ve read. After a year of confusion and fear about the future, I finished it feeling like a weight had physically lifted. It’s long. Make the time. @vgr is undefeated. contraptions.venkateshrao.co…
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The finding has large implications in itself (US productivity growth may have peaked before WWII rather than the postwar boom), but what fascinates me most is the method. The authors use LLMs to extract prices and product characteristics from 5.1 million Sears catalog listings from 1900 to 1990. That lets them estimate how much prices for consumer goods rose after accounting for improvements in quality (e.g. icebox → electric fridge). This opens up obscenely broad research agendas. Old books, catalogs, newspapers, imperial records, archives full of evidence that would be almost impossible to structure manually can now become datasets. Questions in economics, history and politics that were previously prohibitively labor intensive to investigate are now practical research projects.
Excited to share our new working paper: how much did the US standard of living really rise over the twentieth century — and when? With @bhwittenbrink Using 5.1 million Sears catalog listings, we build a quality-adjusted price index for consumer goods, 1900–1990. Two headline findings: growth was much larger than official statistics imply, and its peak came before WWII, not after. (1/9)
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Making sure I state it clearly: We can literally patch and prove bug-freeness of the entire software stack running in production. With AI that exists right now for ~$100m. This means no more software-level hacks. I know it sounds too good to be true, but it isn't. AMA.
We formally verified 123 open-source projects in a partnership with Anthropic. Formal verification at scale is here! Now we’re launching OSS Verify to scale it to the software we all depend on. We prove it’s crash-free or send you the patches it needs. Free for open-source. Let’s bootstrap the verified software ecosystem: theorem.dev/oss-verify
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SO interesting and potentially helpful! Now time to do this for theory on technology and organizing. Hopefully they have a repo...
Excited to share this new work on mapping economic theory with agentic AI! The astonishing rise in AI math capability can help us understand formal models in economics. We do it by using LLM agents to represent theory papers as graphs. See thread by @andreacicca_ here:
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Wondering what humans have left to do in intellectual work? Read on.
as a founder of @RefineDotInk, discussion around this new paper is v. interesting! The results confirm that AI reviews are incredible for detailed, actionable feedback to improve a manuscript. If AI is better, should AI replace human review? Quick view from the trenches 1/
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Matt Beane retweeted
as a founder of @RefineDotInk, discussion around this new paper is v. interesting! The results confirm that AI reviews are incredible for detailed, actionable feedback to improve a manuscript. If AI is better, should AI replace human review? Quick view from the trenches 1/
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The jig is up. Research and publishing must change (and are, to be fair - just much too slowly).
By every measure, Opus 4.8 beats human experts as peer reviewers in a study of 124 Harvard social science papers covering a range from statistical analyses to formal models to qualitative work. As academics, we need to figure out how to adapt the practice of science to AI, fast.
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