Mike Knoop
speaker
927 appearances
4 recordings
1 series
first heard Mar 2025
last heard 18 Nov
Mike Knoop’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 1 in all, peaking in Nov 2025 with 1.
Appearances
The definition that I use for AGI these days is basically when we r stop being able to easily find tasks that humans can do that AI can't do,
got we've got AGI.
Um, and uh you know, I I think that's like I said, a bit of a pragmatic answer.
Uh one of the things that surprised me about Arc AGI too was the relative degree of ease by which we were able to create it.
Okay.
Given this like big moment in December of like,
O3 beating RKJ1, um, you know, it was actually not too hard for us to come up with tasks that we were able to sort of verify.
We actually did a controlled human study to make sure every task in the V2 data set was solvable by at least two humans on the same rule set.
Um, and we were able to find that relatively easily.
So I I think that shows we still have a ways to go.
Um, I I think once we hit that bar though, when the gap between like easy for humans, hard for AI is zero, I think it would be extremely difficult for anyone to like argue the opposite side.
But like we we don't have AGI.
Um I I'm not I don't find the economic like measurements quite as useful for understanding
The capabilities of what Frontier AI does, I think it's a good measure of impact.
And I have no problems using it for that point.
But I think if you want to use like an economic measure to make a statement about capabilities, the challenge is it obscures and there's multiple ways to get to that outcome.
And this is one of the challenges with like language models.
Like language models generally work in like a memorization style regime where they're right, learning lots of data, they're able to apply it to very similar types of patterns that they've seen.
seen before, but not novel patterns.
That's what RKG RKGI shows.
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