Study work with AI + robots. @MITSloan PhD, @Ucsb Assc Prof, @Stanford fellow, @tedtalks, @skillbenchinc cofounder, CEO Book: https://nitter.cf/t.co/OJQa0by9MT
Santa Barbara, CA
Joined November 2008
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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…
Matt Beane retweeted
(Very rough estimate) After 70 years, machines have just gotten cheaper than humans on $/FLOP.
Nothing in these analyses were about AI (just hardware prices). It's a pretty striking coincidence if this cost crossover hits just as we're reaching human-level AGI.
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Some details on the back-of-envelope estimates (all adjusted to 2026 dollars):
Human cost per flop: Modern US labor costs ~$30/hr and global average wage (harder to estimate) is ~$10/hr. Subsistence is the bare cost of keeping a worker alive, ~$0.75/hour. @jkcarlsmith's great analysis gives ~1e15 FLOP/s for the human brain (NB wide range of 1e13-1e17 FLOP/s as plausible). Also assuming 100% of the brain’s FLOPs are applied to the task at hand (changing this percentage makes less than an order of magnitude difference).
🧑🦱 Market cost per flop → $10 / hr / (3600 s/hr × 10¹⁵ FLOP/s) = 3e-18 $/FLOP
🧑🦱 Subsistence cost per flop → $0.75 / hr / (3600 s/hr × 10¹⁵ FLOP/s) = 2e-19 $/FLOP
Machine cost per flop – examples through history (adjusted to 2026 dollars):
💻 An early computer like the IBM 704 (1955) was leased for $530k/month and ran at 2 GFLOP/S → $530,000 / (176 h × 3,600 s × 5,000 FLOP/s) = 1.7e-4 $/FLOP.
💻 A 1999 computer like the Pentium III cost about $1090 and ran at 2 GFLOP/s. If used 24/7 for 4 years → $1,090 / (1.26×10⁸ s × 2×10⁹ FLOP/s) = 4×10⁻¹⁵
💻 A 2010 GPU like the GTX 580 (which AlexNet was trained on) cost about $590 for 1.5 TFLOP/s → $590 / (1.26×10⁸ s × 1.5×10¹² FLOP/s) = 3e-18 $/FLOP.
💻 A 2027 AI chip like NVIDIA Rubin costs about $55,000 and runs at ~35 PFLOP/s at 4-bit precision → $55,000 / (1.26×10⁸ s × 3.5×10¹⁶ FLOP/s) = 1e-20 $/FLOP
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I will try to write this up in more detail soon. Some refs:
* FLOP/s of the human brain: coefficientgiving.org/resear…
* US and global labor costs: bls.gov/news.release/empsit.…
ilo.org/sites/default/files/…
* subsistence wages:
jstor.org/stable/10.1086/498…
Matt Beane retweeted
Steve was very early on this. But he’s exactly right—chatbot era was never going to be a huge productivity boost. Analyses should put the line at January 2026; agentic AI is where productivity gains are.
Matt Beane retweeted
People who have been in research fields develop a felt sense that most "research" (in almost any field that isn't exactingly technical) is research theater, and many superstar careers enjoy star status not because of a unique connection to the truth but because of a unique connection with an audience. No one really has the time or stature to, from a position of objectivity and trust, bring popular researchers to heel. But it will get increasingly hard to hide from serious critique. The machines can do critique now, at the level of depth and rigor previously only possible for the academically deranged. We're going to have to revise a lot of what we "know" about the world that isn't really knowledge but is actually just received popular consensus - like floating voltages without grounding wires. The grounding wires are coming.
Tyler Cowen:
'I am not even sure what to say at this point. We need a radical revaluation of this work, and of the associated policy arguments. More generally, this is only a single step in the story of how AI is going to revise economic science, and indeed past research more generally. As I stress in many of my recent talks, there will be significant gains and losses in status, with the losses often outweighing the gains. I see this as one of those cases.'
Matt Beane retweeted
SIR PATRICK STEWART (1940-2026)
Before everything else, Patrick was defined by being born and bred in Yorkshire, the proud county in the north of England which he loved to the end. You could hear it in his accented voice and in the stern honesty with which he told you what he thought and felt. Yorkshiremen have no truck with half-truths or avoidance of big issues. He wore his heart on his sleeve, which made him a man to rely on, to admire and in my case, love.
We first met as ambitious young actors with the Royal Shakespeare Company half a century ago but we weren’t in the same productions. My first strong memory was a few years later, meeting him in the street in central London when he told me about an offer to take over a leading part in 'Star Trek'. “But Patrick think of your stage career in the UK. Do you really want to risk—getting lost in Hollywood for years and years?”. Well, he took the risk and thank goodness for us all that he did for not just his devoted Trekkies but film and theatre audiences, who marvelled at his using international celebrity to star in a string of cinema successes ('X-Men' of course) and in great classical plays by Shakespeare, Ibsen, Arthur Miller, Peter Shaffer, Pinter and Beckett at Stratford-upon-Avon, in London’s West End and on Broadway.
America was his adopted home, where he met his adored Sunny who has cared for him through sickness and health, through thick and thin. But he never forsook his origins: and the proudest achievement of the most respected and beloved actor of his generation on either side of the Atlantic, was his appointment as Chancellor of Huddersfield University in Yorkshire.
His farewell performance in 'Avengers: Doomsday' is yet to be seen.
Ian McKellen 29 October 2026
Photo: University of Huddersfield
Matt Beane retweeted
New DeepMind Institute essay: "What is work for? Human wellbeing and the value of work in the AGI era."
The empirical evidence shows that many people value their jobs beyond earning a salary, and the importance of agency, status, and meaning. At the same time, we investigate alternate sources of wellbeing, and the possibility that societal norms around work may change over time.
with @JulianDJacobs @locross
Read it here: bit.ly/wellbeing-work-agi
We're in the early days of a Cambrian explosion of an agentic ecosystem.
Just yesterday (i.e., last week) it was reverse engineer anything.
Now, as a countermeasure, this adversarial defense packet is ripping around the interwebs: github.com/qybaihe/bla
Matt Beane retweeted
Lots of debate this week on whether journals should ban AI in peer review.
We actually tested this in our new preprint, and the results were pretty clear to me.
For context, I've reviewed for most of the big journals and evaluated 1,000 human reviews as an editor. I love to read and evaluate science.
TLDR: From now on I won't do any peer review without AI. For clinical trials, I'd even call human-only review dangerous 🧵
Top of my queue.
This doesn't answer "what new jobs can we expect?" but it does help us see the stocks and flows of labor in the economy, and the types of work involved, given a variety of assumptions about the AI cost/performance curve. Massive potential predictive power.
I joined @GoogleDeepMind to develop a research program on the economics of AGI. Today, together with Andrew Koh (@andrewjkoh) and Shane Legg (@ShaneLegg), we are incredibly excited to release The Economics of Intelligence, the first in a series of projects from our group on how AGI will change the economy.
How do capability improvements transform the economy, and when? In this project, we define thresholds of economic capabilities, e.g., minimal AGI, based on how they transform the economy. We then track how the economy–market structure, employment, and wages–changes during the transition across capability regimes.
We have seen exponential increases in what AI agents can do but the broader economy seems almost remarkably unchanged. Part of the reason is that the solo AI agent is the wrong economic object; economic transformation is an equilibrium outcome where organizations compete. Looking at how intelligence functions within organizations, transformation will depend on when two key capability thresholds are crossed: competence (gains on individual skills, e.g., coding, math) and coordination (gains on ability of agents to cooperate and work together).
We show that what economic transformation looks like depends on whether AI becomes supercompetent, supercooperative, or both—the regime of artificial superintelligence (ASI). Tracking this transition shows why the real visible transformation may come from improvements in coordination—a capability most benchmarks don’t yet track. Past a certain threshold, AI capabilities can break the Coasian ceiling on firm size and lead to an economy that looks drastically different than the one we see today.
Two main takeaways:
1. To understand the path of transformation, we should be tracking agentic coordination more closely.
2. The impact of AI will likely show up in wages before market structure or employment.
We are really excited about this paper. Excited to hear people’s thoughts.
Link: institute.deepmind.com/essay…
This has only been presented to 4m people.
Endorsed by 10k.
Shared by 2.1k.
Jason is right, but not loud enough. Don't think anyone could be, really.
Let's hope this is y2k-level. That would mean we really don't understand the emerging AI security ecosystem!
Matt Beane retweeted
as bad as things have gotten in the past 4 days, they are going to get a lot worse before they get better. security leaders, never let a crisis go to waste: please go to your boards and ask for help right now. not for ai, for the basics. (we need to hold on for ~18 months.)
Matt Beane retweeted
Personally, I also wonder a little at what we are doing in economics if treatment effects can be forecast so well.
Part of it is surely that many treatments have very small effects.
But can we not shift to working on those projects that have particularly high uncertainty and upside potential? 6/
Matt Beane retweeted
Gemini 4 Carbon is our next frontier model.
It’s state-of-the-art across cybersecurity and long-horizon capabilities.
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
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
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…
Matt Beane retweeted
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…
Matt Beane retweeted
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
ALT The front entrance of a building with a sign reading, "U.S. National Science Foundation."
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.
