From one piece Scaling and the Road to Human-Level AI (Jared Kaplan, AI Startup School, Y Combinator; speaker-labelled transcript) 9 beliefs, in the piece's order there
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Their words
We need to train AI models that don't just greet you with a blank slate but can learn to work within companies, organizations, governments as though they have the kind of context that someone who's been working there for years has.
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Their words
I think generally it's really asking very naive dumb questions that gets you very far.
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I think that probably leveraging AI to integrate AI into parts of the economy as quickly as possible, I expect there's just a lot of leverage there.
+ 6 more
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korrents.com
How long a task a model can accomplish depends largely on its ability to notice its own mistakes and correct them.Their words
I think that a lot of what determines the horizon length of what models can accomplish is their ability to notice that they're doing something wrong and correct it.
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Their words
I think that right now human AI collaboration is going to be the sort of most interesting place because I think that for the most advanced tasks you're really going to need humans in the loop.
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korrents.com
Eventually AI models, perhaps millions working together, may be able to do the work of whole human organizations.Their words
Eventually, we imagine AI models—or millions of AI models perhaps working together—will be able to do the work that whole human organizations can do.
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korrents.com
Products that do not quite work yet are worth building, because the next model may make them work.Their words
That means that if you build a product that doesn't quite work because Claude 4 is still a little bit too dumb, you could expect that there'll be a Claude 5 coming that will make that product work and deliver a lot of value.
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korrents.com
Scaling results gave conviction that AI would keep getting smarter in a very predictable way.Their words
These gave us a lot of conviction to believe that AI was just going to keep getting smarter and smarter in a very predictable way.
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korrents.com
AI progress comes from a simple, systematic way of improving models, not from researchers suddenly getting smarter.Their words
It's not that AI researchers are really smart or they suddenly got smart. It's that we found a very, very simple way of making AI better systematically, and we're turning that crank.