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Discovery Loop

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Re: Discovery Loop

#481
post #422
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.

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...

Re: Discovery Loop

#482

Earlier quoted context omitted.

> Our mission is straightforward: we are building AI solutions that can automatically solve important problems in machine learning, science, and engineering. Genuinely curious which part you found complex.

We are building _ solutions (building solutions != building a thing. Can't you just say 'solving'?) That can _ solve _ problems in _, domains (Wait so the solutions are only the thing that solves the actual thing?)

It's clunky, but still clear. They're building AI things (systems, solutions, harnesses, whatever) that can tackle big research problems.

Re: Discovery Loop

#483
post #241

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…

I don’t understand why all of these companies need to frame it like this. Why not a large amount of people doing an even larger amount of science?

When you define prosperity in large amount of people, it makes you sound like a communist, and America spent decades to avoid that. The other alternative is to sound like a capitalist, which is very much ok by today’s standards.

Re: Discovery Loop

#484

Earlier quoted context omitted.

The solution to most of these problems lies in policy, not in new tech advancements. Maybe if our biggest companies did something other than suck up to science denying wackos, some progress could be made in these areas.

Making progress requires first not dismissing your ideological outgroup along such lines, and instead trying to understand what actually motivates them.

I was not expecting such a high level of maturity and sophistication here. Bravo, sir.

Re: Discovery Loop

#485
post #241

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…

I think this take is too cynical. Small groups of people can do better, faster work than large groups, and it's more fun.

Re: Discovery Loop

#486

Earlier quoted context omitted.

Would be great if they'd add: Reverse human aging. (Maybe a sub-topic under "Engineer Better Medicines".)

At a population level, humans getting rid of their off switch is about as good of a thing as your own pancreas cells getting rid of theirs.

I know you're gesturing emphatically at some kind of analogy to cancer, but malignant cancer requires replication not immortality.

Re: Discovery Loop

#488
post #197

Earlier quoted context omitted.

Would be great if they'd add: Reverse human aging. (Maybe a sub-topic under "Engineer Better Medicines".)

Why not just add 'mind control' while you're at it. Only death stops stagnation in the end. Without death, especially if death can be avoided by the rich and powerful but not the poor, life will get much, much worse for the average person (until only the rich and their automated capital remain I suppose, in which scenario they will simply turn on each other).

This is the classic "without death, authoritarian depots will be in power forever".

But it's actually the wrong way around. Hope that the despot will soon die saps peoples' will to do the difficult and dangerous job of removing them. Take away that hope and they are forced to find the courage.

Re: Discovery Loop

#489
post #32

Jeff Dean, Sanjay, et al have achieved so much. I'm very happy for them. Truly deserving. Sometimes I couldn't resist wondering if I'll ever do work that has a tenth of the impact of theirs.

> Between us, we have pioneered massive scale computing and led the creation of critical infrastructure, products, and foundational AI advances that the world relies on, including multiple generations of Google Search, Google Ads, Google News, Google Translate, Google File System, MapReduce, BigTable, Spanner, TensorFlow, Pathways, TPUs, AlphaChip, AlphaStar, AlphaCode, AlphaFold, Gemini, model distillation, mixture-…

Hmm word2vec doesn’t seem to belong to any on the four. Dean was a last coauthor of the paper.

Re: Discovery Loop

#490
post #241

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…

you can have many many small groups
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