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Discovery Loop

discoveryloop.com

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Re: Discovery Loop

#101

Post by staplers »

LogicFailsMe wrote: post #85
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…

Sandbox 2.0 But also, solar power is already economical.

  3. Develop Carbon Sequestration Methods
If only we could invent a solar-powered, self-replicating, carbon-stacking, habitat-building machine..

Re: Discovery Loop

#102

Post by bonsai_bar »

tcp_handshaker wrote: post #76
ValentineC wrote: post #3

I wonder if Jeff Dean facts [1] (I hope people remember the reference) will carry over to the new startup. [1] https://github.com/LRitzdorf/TheJeffDeanFacts

Those are all fake, part of an internal Google narrative that overstates individual contribution, and obscures the work of large engineering teams. Here are some Jeff Dean well sourced facts: - Already part of engineering of Google indexing systems that lacked basic checksums and ran on non-ECC hardware, allowing silent data corruption. - One of the authors of LevelDB a database with so many documented crash-consiste…

You sound like you're quite jealous of him.

Re: Discovery Loop

#103

Post by glaslong »

LogicFailsMe wrote: post #85
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…

Sandbox 2.0 But also, solar power is already economical.

At this point the Hard Problem is policy to get out of solar's way.

Re: Discovery Loop

#104

Post by valleyer »

flakiness wrote: post #59
canes123456 wrote: post #34

Earlier quoted context omitted.

A public benefit corp shouldn’t be a start up. The primary goal of a start up is to grow as quickly as possible which is rarely benefits the public. Very silly to call every non start up a lifestyle business. It’s just a business. Start up are the weird thing that almost always an obscene waste of time and money, but sometime creates google.

Fair point. Their page doesn't list any investors.

The Times article lists several.

Re: Discovery Loop

#105

Post by mbonnet »

drivebyhooting wrote: post #87

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…

> transcendence

> immanence

somebody has been studying Christian theology!

Re: Discovery Loop

#106

Post by scrlk »

moelf wrote: post #93
drivebyhooting wrote: post #87

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…

would love to see how AI can automate the construction of the next high energy particle collider

"You're absolutely right! I shouldn't have pushed the anti-mass spectrometer to 105% power, causing a resonance cascade. This was a major oversight on my part."

Re: Discovery Loop

#107

Post by la64710 »

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…

Please add fixing neuro issues like autism add etc on the list. It creates a huge burden on families.

Re: Discovery Loop

#108

Post by returnInfinity »

tcp_handshaker wrote: post #47
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…

Acquisition back by Google in 3 years, with nothing to show for it. VCs will make a ton.

Google stock would drop big if this new company was being funded by competitors

Re: Discovery Loop

#110

Post by Taikhoom2010 »

malux85 wrote: post #62
Taikhoom2010 wrote: post #37

The problem is all these new labs don't have any competitive advanatge amongst each other, talent can only take one so far, though Jeff is a legend no doubt. Models are commodities the applications eg. BaseTen, OpenRouter should capture the value. https://taikhooms.substack.com/p/why-openrouter-can-be-the-n...

Model routers - send all of your data through a third party who totally swears not to peek at it. If youre doing anything high value (advanced research, classified work, high value industrial research, health data) then sending your data through a third party like that is insane.

yes perhaps, although I think the best option for a enterprise is to train a model on it's own data.
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