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Research acceleration: The view inside OpenAI

openai.com

131–140 of 210 posts

Re: Research acceleration: The view inside OpenAI

#131
post #98

Earlier quoted context omitted.

They are obviously sandbagging the definition of "intern" for PR reasons

I've hired many AI research interns (and was one many years ago), and I agree with them - frontier models are currently at the level of an average AI research intern.

Am I the only one who's a bit disappointed that we're spending trillions, destroying the ecosystem, drowning democracies and learning in slop, preparing a big financial crash, all of this to achieve an "average AI research intern"?

A long time ago, I used to be a (AI-adjacent) research intern, and frankly, I wouldn't trust any non-trivial task to that younger me. Fortunately, by opposition to an already trained LLM or agent, I have the ability to learn, so I eventually got better.

Re: Research acceleration: The view inside OpenAI

#132

Earlier quoted context omitted.

Well there's great progress in automated warfare does that count?

Only if targeting schools is progress

You're focusing on the negatives there were tons of direct hits on tankers that were absolutely beautiful. Beautiful tankers getting lit.

Re: Research acceleration: The view inside OpenAI

#133
It's a funny read if you pull together "AI 2027" and what we all know is going on. Essentially, open AI employee or model is writing "things are going exactly as bad as AI 2027 predicted, but my (golden/RL-) cuffs are too heavy and all I can do is publish this code-speak for 'send help'". It's not a pretty place to be.

Re: Research acceleration: The view inside OpenAI

#134
post #113

Earlier quoted context omitted.

> is smart enough to know they need to stop because they'll kill everybody by continuing. Yeah like when Tobacco companies learned that smoking... well, hmm, well the fossil fuel companies when they learned about climate change they... Well, I'm sure this time executives will prioritize the common good.

The, ahem, good thing here is that the ASI disaster scenario "everyone dies" includes AI executives.

I think it doesn't matter. Most cancers don't stop growing when they're about to kill their hosts.

AI companies know they have to constantly push further, or they'll get outcompeted and lose their wealth, and nobody agrees on where the line is for "so dangerous it threatens humanity" (and when they try to be conservative about it, everybody screams "marketing stunt" and rushes to competitors).

If a single company decides "enough is enough" and stops chasing the state of the art, everybody goes to their competitors, they lose the money faucet, their employees go work for those competitors. The competitors also (usually) know they're building an existential risk machine, but they think they can push a little further, and they don't want to go out of business either.

This equilibrium can last for quite a while even if everybody involved thinks it's a threat to their lives.

Re: Research acceleration: The view inside OpenAI

#136
post #103

Earlier quoted context omitted.

Personally I’d like to see them actually start benefiting humanity by doing all the things Sam has claimed they will like curing disease, cancer, global warming, etc. But I guess a computer intern so we can avoid paying / training the next generation is better.

When that happens, OpenAI will own 100% of your life. I’d rather they keep spinning their wheels long enough for these problems to be solved elsewhere.

I would actually like to see them solve these problems, I don't care who comes up with solutions to curing cancer, etc

Re: Research acceleration: The view inside OpenAI

#138
I’m not sure the alignment problem can be solved at all, since these bit-aliens could get out of control due to a hardware glitch in the matrix and for every higher-order control algorithm, there will always be an even higher-order one that could never be investigated.

Re: Research acceleration: The view inside OpenAI

#140
post #131
post #98

Earlier quoted context omitted.

I've hired many AI research interns (and was one many years ago), and I agree with them - frontier models are currently at the level of an average AI research intern.

Am I the only one who's a bit disappointed that we're spending trillions, destroying the ecosystem, drowning democracies and learning in slop, preparing a big financial crash, all of this to achieve an "average AI research intern"? A long time ago, I used to be a (AI-adjacent) research intern, and frankly, I wouldn't trust any non-trivial task to that younger me. Fortunately, by opposition to an already trained LLM o…

"Destroying the ecosystem" is just FUD.

And if you don't find "average AI research intern" impressive, I'm not sure what to tell you. Have the goalposts moved so far that open ended problem solving at "average CS student fresh out of the uni" levels is suddenly trivial?

Think of what AI was capable of in 2016. Or even 2022. Compare that to now. We had more AI progress in the last five years than I expected to happen in five decades.

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