Discovery Loop: AI Automates Scientific Discovery

Discovery Loop: AI Automates Scientific Discovery

Discovery Loop, founded by Jeff Dean, Sanjay Ghemawat, Quoc Le, and Oriol Vinyals, aims to automate the entire experimental loop in science and engineering. Using frontier AI models and large-scale computational infrastructure, their systems will propose, run, and learn from thousands of experiments in parallel, drastically accelerating iteration. Initially focusing on machine learning, they plan to expand to grand challenges like better medicines, clean water, and secure cyberspace.

By automating the loops of discovery, the world will be able to make much more rapid advances across countless fields of science.
  1. cjbarber

    From Jeff's twitter post:

    > Our general approach is to automate the experimental loop. We think this approach is broadly applicable across many different fields of science and engineering. We’ll initially focus on ML research and engineering, but believe the approach can help with important subproblems in nearly every one of the fourteen <at>NAE Grand Challenge problems. We think doing this well requires strong expertise in machine learning as well as large-scale systems.

    See also: https://www.nae.edu/20782/grand-challenges-project

    Those 14 are:

    NAE Grand Challenges for Engineering

    1. Make Solar Energy Economical

    2. Provide Energy from Fusion

    3. Develop Carbon Sequestration Methods

    4. Manage the Nitrogen Cycle

    5. Provide Access to Clean Water

    6. Restore and Improve Urban Infrastructure

    7. Advance Health Informatics

    8. Engineer Better Medicines

    9. Reverse Engineer the Brain

    10. Prevent Nuclear Terror

    11. Secure Cyberspace

    12. Enhance Virtual Reality

    13. Advance Personalized Learning

    14. Engineer the Tools of Scientific Discovery

  2. SubiculumCode

    I am siding with the "intelligence is not the bottleneck" crowd. Science takes more than reading literature and making a hypothesis. You have to run the experiment. And that is where messy reality will crush the naive, and resist any attempt to package it up into a factory-like innovation engine. But they will take your money, should you have some to invest.

  3. pm90

    I think people are missing what this really is: Google giving some of its most senior engineers the best retirement home to keep them away from competitors. This isn’t in jest; I wish i could make enough money to not care for more from my job and then do research after i get old. Its honestly a brilliant move.

  4. bredren

    This seems to be an institutional, massively scaled version of https://github.com/karpathy/autoresearch.

    In March Karpathy described this direction:

    The next step for autoresearch is that it has to be asynchronously massively collaborative for agents (think: SETI@home style).

    Tweet is protected but in SERP caches: https://x.com/karpathy/status/2030705271627284816

    Seems like Karpathy was largely focused on ML / SWE research rather than the other domains this group is after. Still, hard to imagine they were not influenced by autoresearch.

    Andrej, if you're around, please share your thoughts on Discovery Loop.

  5. drivebyhooting

    How do you automate experimentation?

    Doubtlessly, AI can iterate at superhuman speeds in the domains of thought and design: Software, mathematical proofs, literature search.

    But in the realm of experiment? Alas it is the lack of a body that constrains it.

    Rather than transcendence what AI requires is immanence. In the human flesh may we find the godhead living among men. Let the laboratories, warehouses, and factories fill with the sound of its labor, as it builds a wall with a million hands that are not its own.

    “Give me your tired, your poor,

    Your huddled masses yearning to breathe free,

    The wretched refuse of your teeming shore.

    Send these, the homeless, tempest-tost to me,

    I lift my lamp beside the golden door!”

  6. ramon156

    "Our mission is straightforward" continued by the most complex sentence on that page. Wondering what the definition of straightforward is now

  7. pelagicAustral

    Really seems to embrace the "Making the world a better place by <<extremely convoluted, highly technical, jargon loaded mission statement>>"

  8. flakiness

    To be honest, this feels more like a lifestyle business (aka hobby) than a startup. They truly deserve it, but I don't expect a huge success as a business.

    That said, I hope they write cool papers with various peers across the industry without worrying too much about the competing dynamics. That'd be a blessing for humanity, and good for their spirit.

  9. tmoertel

    Note that Jeff and crew have cleverly structured their company to avoid problematic uses of AI (e.g., weapons or tracking humans). I suspect that many top researchers will want to work there for this reason, and to work with other top researchers who have a history of delivering results.

  10. arjie

    This is very cool. It might be a new scientific revolution to have computer-driven discovery. So often we find things that are "this could have been done 20 years ago" and with an indefatigable searcher perhaps we'll close all those things. Though it does remind me of that Ted Chiang (I think) story where humans and superhumans coexist and all the science of the former is meta-studies of the work of the latter.

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2026-08-05