Rob Wiblin

speaker

5,091 appearances 15 recordings 1 series first heard Oct 2021 last heard 6 Aug

Rob Wiblin’s voice in public audio — every appearance, attributed to the second.

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recordings per month · last 12 months

Recordings per month over the last 12 months — 13 in all, peaking in Apr 2026 with 3.

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80,000 Hours Podcast · #250 – Toby Ord on where AGI timelines go wrong · 6 Aug 2026 podcast

I guess you could have really big improvements in the speed of learning, basically, by that point, or the sample efficiency is the technical term for how many examples or how much experience do you need in order to figure out how to do stuff.

I guess human sample efficiency is actually unfathomable, extraordinary in some ways.

I guess I don't often get to pull the parent card, having a toddler.

It is unbelievable that they can see an example of a pig, and then they will be able to tell all of these other things that look very different are also pigs, and this picture, this stylized picture of a pig is also a pig.

I don't actually understand how on earth it's going on.

I guess AI researchers don't know either.

It is incredible.

The art of sample generalization.

Yeah.

So that's a point against what I was saying.

So they have awful sample efficiency, but you could get like a million-fold improvement.

Like, well, we know it could be a million-fold better because humans are a million-fold better and we're presumably not the very best that's possible.

So that's one way that this sort of thing could not pan out as if through recursive self-improvement or some other way you have a different architecture for learning.

Well, yes.

So that's one way is that the AIs could learn very quickly because like,

many, many instances of them are deployed and they all collect data and they pull it together.

Another one is we're already beginning to kind of put video cameras basically on people's heads and like record all their keystrokes.

So it's possible by this time, we'll have actually a huge new data set of basically what lawyers do and how they think and what they look at and so on that they could learn from.

Yeah, it's hard to predict.

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