381–390 of 625 posts
"Our mission is straightforward" continued by the most complex sentence on that page. Wondering what the definition of straightforward is now
Genuinely curious which part you found complex.
Earlier quoted context omitted.
3. Develop Carbon Sequestration Methods If only we could invent a solar-powered, self-replicating, carbon-stacking, habitat-building machine..
Not to say we shouldn't grow plants... But we can do it 2 or 3 orders of magnitude more efficiently with machines.
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 factorie…
That objective then gets loaded into an ML model that spits out an experimental protocol. A protocol can be as simple as: "make 1 million test tubes, each with the protein, and in each, a custom molecules, and look for test tubes that show some reaction of interest". It can be a lot more complicated (for some reason, biologists who run these systems always try to do the most challenging experiments first, while I tend to spend all my time demonstrating the system can pass basic controls first). The protocol is then loaded into a robotic work cell which has access to protein-making machines and drug making machines, and then it handles all the experimental details (which previously would have been done by a technician). It scales up far larger than individual technician, is much more reliable, and faster (in theory- all of these are aspirational goals right now). T he results of those experiments are used to fine tune the experimental protocol and run another round. You run this in a loop and the result is better drugs faster (again- in theory.)
This is already an active area of research with more resources going to into it every day. The fact that Jeff and Sanjay have chosen to bet on this approach should be no surprise. In many ways, this is exactly what I intended when I wrote the documents inside Google (15 years ago) that motivated Jeff and Sanjay to work on scientific computing problems, and my current company is already trying to figure out how to work with Discovery Loop.
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 NAE Grand Challenge problems. We think doing this well requires strong expertise…
4. Manage the Nitrogen Cycle Easy solution - eat less products that pass an animal first - reduces nitrogen pollution by 10x intantly, low tech. I'd re-formulate: 4. Make people more flexible to changing their mindsets & habits - this is the ultimate problem.
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> Note that Jeff and crew have cleverly structured their company to avoid problematic uses of AI Do you have more sources/info on this?
x2 All the "bad guys" of today were the "good guys" at some point in time. You even cheered for them back then.
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 NAE Grand Challenge problems. We think doing this well requires strong expertise…
They make many bold promises, but their core goal is neatly encapsulated on the website: "Imagine a future where a handful of people can conduct scientific research and engineering tasks much more rapidly, and with higher quality, than massive teams of scientists and engineers do today." This is the same goal as every other AI company out there. Automate away the human employees and let a small number of "people" (no…
So...
judging by the amount being installed, it already is.
Discovery and optimization are very different processes. Optimization is the process of finding the shortest path to a goal. Discovery is the process of stumbling on new goals and redrawing the map of what's possible. Ambitious goals and new discoveries happen via novelty-based search. Progress in scientific discovery is measured by how different/interesting the outcomes are, not by closeness to a predetermined goal.…
I think that’s exactly the kind of problem this group is looking to solve. You make a compelling intuitive argument, but that’s not the same thing as a proof
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 NAE Grand Challenge problems. We think doing this well requires strong expertise…
Such a weird list. How is preventing nuclear terror an engineering problem?
Earlier quoted context omitted.
They make many bold promises, but their core goal is neatly encapsulated on the website: "Imagine a future where a handful of people can conduct scientific research and engineering tasks much more rapidly, and with higher quality, than massive teams of scientists and engineers do today." This is the same goal as every other AI company out there. Automate away the human employees and let a small number of "people" (no…
> "Imagine a future where a handful of people can conduct scientific research and engineering tasks much more rapidly, and with higher quality, than massive teams of scientists and engineers do today." I don't think the US have this capability because you guys don't really have manufacturing that is really necessary for scientific research. For example, if I want a highly toxic chemical, how difficult it would be to…
With trustworthy composition and purity?
I work with researchers in both the US and China. Definitely easier to procure in the US.