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Discovery Loop

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Re: Discovery Loop

#541

Post by theptip »

VikRubenfeld wrote: post #521

In many cases, isn't the time-consuming part of experiments irreducible? E.g. breeding plants? Or to take another example, Make Solar Energy Economical How does Discovery Loop make this go faster in a way that a different group of scientists, also using frontier models, will proceed? I'm sure Discovery Loop has considered this and has good answers to this question. I'd be interested in hearing more about this.

It’s true in the limit, but I think we are nowhere near that limit. A friend recently started a bio startup and automated parts of mouse experiments enabling higher throughput on in vivo experimentation. This is not commonplace, and there is a lot of room for further automation here.

As anyone who works with agents daily can attest, 1) you can use agents to help with hypothesis refinement, bridging into areas adjacent to your expertise, etc. 2) once you have a rigorous /goal definition you can parallelize and let the agent crank.

It seems pretty obvious to me that with the right actuators and sensors you can apply this to real physical research loops too. (To be clear, this is not easy; a lot of bench work is Métis and needs experts in the loop at every stage.)

To your point, you can’t make plants grow faster but you can increase research throughput by enabling a researcher to have 10x or 100x as many experiments going at once.

Re: Discovery Loop

#542

Post by snowwrestler »

kube-system wrote: post #291
snowwrestler wrote: post #240

Earlier quoted context omitted.

> The only real practical difference is that they give directors a little more leeway in their fiduciary duties to say "no" to doing evil things. I’d like to provide maybe a clarification here that there is zero existing fiduciary duty in regular corporations to say yes to evil things, or even to turn a profit at all. A for-profit C corporation can legally sell stock, lose money every year, and go out of business, if…

Fiduciary duty absolutely does go beyond accurate communication and fraud. Directors have a duty of care that goes beyond simply not engaging in criminal fraud. Sure, you don't have to be competent, successful, etc. It is completely legal to suck at your directorship. But it's not legal to do something that you can't justify as being good for the business, which is where a public benefit activities can cross the line…

Craigslist the corporation was not even a party to this suit, and it continued operating the same way after this decision as before it. eBay’s only recourse to that was to sell its equity, which it ultimately did in 2015.

I don’t think anyone can look at the company Craigslist in 2026 and say it has spent the last 30 years satisfying a legal duty to maximize profit.

Re: Discovery Loop

#543

Post by kube-system »

snowwrestler wrote: post #542
kube-system wrote: post #291

Earlier quoted context omitted.

Fiduciary duty absolutely does go beyond accurate communication and fraud. Directors have a duty of care that goes beyond simply not engaging in criminal fraud. Sure, you don't have to be competent, successful, etc. It is completely legal to suck at your directorship. But it's not legal to do something that you can't justify as being good for the business, which is where a public benefit activities can cross the line…

Craigslist the corporation was not even a party to this suit, and it continued operating the same way after this decision as before it. eBay’s only recourse to that was to sell its equity, which it ultimately did in 2015. I don’t think anyone can look at the company Craigslist in 2026 and say it has spent the last 30 years satisfying a legal duty to maximize profit.

The case was about Craig and Jim's stockholder-rights plan which they put into place to protect the direction of the company after their death. They're still alive... so of course, the past 30 years don't have anything to do with it.

The point of my example was the legal standard used.

Re: Discovery Loop

#544

Post by gopalv »

pilooch wrote: post #451
pm90 wrote: post #306

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.

The risk is they are a magnet for many more talented ML scientists to leave google.

> a magnet for many more talented ML scientists to leave google.

Also to leave Meta, Amazon, Microsoft and everywhere else.

There would be more people who wouldn't join Google, but would love to do this instead.

Re: Discovery Loop

#545

Post by roflmaostc »

decimalenough wrote: post #481
zackwu wrote: post #422

Earlier quoted context omitted.

It depends on your lens, some may think it's a way to show them the doors after failed corp politics.

Sanjay has been Google's most tenured IC since forever and is basically as immune to politics as you can be in a megacorp. He is also rich beyond dreams of avarice and can do basically whatever he wants, but apparently he decided to go hack some more with his buddy Jeff. There's a famous New Yorker story about them: https://www.newyorker.com/magazine/2018/12/10/the-friendship...

Reading this article, now I can understand why there is jokes about Jeff Dean's binary readability...

Re: Discovery Loop

#546

Post by [deleted] »

cjbarber wrote: post #18

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…

[deleted]

Re: Discovery Loop

#547

Post by amai »

cjbarber wrote: post #18

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…

> Make Solar Energy Economical

That is already solved.

> Develop Carbon Sequestration Methods

That is not necessary, because 1 is solved.

> Reverse engineer the brain

What for? There was already the european human brain project, which didn't do anything useful.

> Prevent nuclear terror

Easy one: Every country stops developing nuclear weapons and destroys existing ones.

It seems this list itself has many flaws. Maybe we need a bigger computer which figures out the questions we really need to ask.

Re: Discovery Loop

#549

Post by summerlight »

VikRubenfeld wrote: post #521

In many cases, isn't the time-consuming part of experiments irreducible? E.g. breeding plants? Or to take another example, Make Solar Energy Economical How does Discovery Loop make this go faster in a way that a different group of scientists, also using frontier models, will proceed? I'm sure Discovery Loop has considered this and has good answers to this question. I'd be interested in hearing more about this.

This is a valid take but at this moment, AI is not trying to solve this fundamental dynamic. But it can still accelerate the process by aggressive exploration of the solution space which cannot be done even with an army of human researchers. Many ideas can be relatively quickly verified (and discarded if needed) by proper simulation even before real world experimentation, but we don't have enough capacity to process all potential ideas. If you can build a good model for simulation and establish a robust methodologies, we can use some ideas which never had a chance before.
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