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
Um, and so I think that tells you something interesting.
Like, well, okay, yeah, like we're clearly missing something big here.
Uh, we don't have it all figured out.
We're we're not in just like a scaling up regime.
We are in a we're sort of an idea constrained regime.
And I think that's an important conclusion because if it's true, it means that individual researchers and small teams on small budgets can actually have a significant impact on the frontier of AI research.
Today you don't need, you know, a million, 10 million billion dollar training budgets in order to
actually make a material impact on AI.
I mean, this forms my thesis.
I think talent is very distributed in my era globally.
Um, if you look at most of the teams that are on the leaderboard from, you know, past years of the art contest, you know, a lot a large percentage, I'm not sure if it's over fifty percent, but it might be, are outside the United States.
and again, this is like, you know, if you're sort of c trying to create a sort of optimization function for creating A GI, uh, you know, you
You would like to shape in an innovation environment that's very open.
There's a lot of sharing, and there's a lot of diversity of approach.
Um, the opposite would be like there's very little sharing, everyone's working on the same ideas.
Um, like, and if the because if those ideas are wrong, then like, okay, you've sort of shooting yourself in the foot.
And so um that those are I I think that's what that's one of the reasons we sort of launched Archprise in the first place, was try to try and help communicate the story that individual people, young folks without with very little budget can actually have a large impact.
And encourage them, if they have new ideas towards AGI, to go work on those, you know, may uh maybe as opposed to going and you know just starting the next language model uh startup.
I think that's happening, right?
The scores are much higher in V1 than V2.
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