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Ep 84: OpenAI’s Chief Scientist on Continual Learning Hype, RL Beyond Code, & Future Alignment Directions

9 Apr 2026 6 published claims 0 attributable people
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belief 5uncertainty 1

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6 published records

01 / belief

I think I'll start with one of the most the juiciest things you said, which is, you know, 4 months ago I think you and the OpenAI team talked about aiming for a system with research level intern capabilities by September of this year.

“I think I'll start with one of the most the juiciest things you said, which is, you know, 4 months ago I think you and the OpenAI team talked about aiming for a system with research level intern capabilities by September of this year.”
Speaker
Not verified from transcript
Publisher
Unsupervised Learning

02 / belief

The the way my thinking about the problem has evolved over the past few years is definitely kind of gone from you know, always this like very nebulous problem that like it's just like very hard to even grapple with or define uh to like, oh, you know, I I think we can actually make progress at it by very concrete technical solutions and technical insights.

“The the way my thinking about the problem has evolved over the past few years is definitely kind of gone from you know, always this like very nebulous problem that like it's just like very hard to even grapple with or define uh to like, oh, you know, I I think we can actually make progress at it by very concrete technical solutions and technical insights.”
Speaker
Not verified from transcript
Publisher
Unsupervised Learning

03 / belief

I think I think there will be a lot of deficiencies for a while of of like these models, right? But But I think also like they they are able to discover new things because they have a lot of these capabilities.

“I think I think there will be a lot of deficiencies for a while of of like these models, right? But But I think also like they they are able to discover new things because they have a lot of these capabilities.”
Speaker
Not verified from transcript
Publisher
Unsupervised Learning

04 / belief

One thing we've been What one kind of discipline we've started keeping is we we try to make sure we just like explicitly budget like a large chunk of our compute to the most scalable methods of the things that we believe are the most responsible for driving general model intelligence. And you know, even if it's not the most efficient allocation of computer at all times, because, you know, if you're allocating so much computer to like one experiment or like one set of experiments, you know, there's so many things you can accelerate with a little bit of that computer elsewhere.

“One thing we've been What one kind of discipline we've started keeping is we we try to make sure we just like explicitly budget like a large chunk of our compute to the most scalable methods of the things that we believe are the most responsible for driving general model intelligence. And you know, even if it's not the most efficient allocation of computer at all times, because, you know, if you're allocating so much computer to like one experiment or like one set of experiments, you know, there's so many things you can accelerate with a little bit of that computer elsewhere.”
Speaker
Not verified from transcript
Publisher
Unsupervised Learning

05 / belief

Uh and especially maybe more applied sciences. And the reason for this shift is because we believe the models are now capable enough, not as smart as people in all ways, but capable enough to actually materially change the economy, change how things are done.

“Uh and especially maybe more applied sciences. And the reason for this shift is because we believe the models are now capable enough, not as smart as people in all ways, but capable enough to actually materially change the economy, change how things are done.”
Speaker
Not verified from transcript
Publisher
Unsupervised Learning

06 / uncertainty

Yeah. And I guess like, you know, we have a lot of folks listening that maybe have, you know, have been able to do a lot of simpler things with these models and then they try to do like some of these more complex, you know, I don't know call it hundred step or longer term tasks and they're like oh, you know, the the the models don't work for this yet.

“Yeah. And I guess like, you know, we have a lot of folks listening that maybe have, you know, have been able to do a lot of simpler things with these models and then they try to do like some of these more complex, you know, I don't know call it hundred step or longer term tasks and they're like oh, you know, the the the models don't work for this yet.”
Speaker
Not verified from transcript
Publisher
Unsupervised Learning
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