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
We're giving these models time to think out loud additional data.
Um every major lab now pretty much at this point, uh I I guess my except for meta.
Uh has has one of these uh systems that we've been able to test and and report results on.
And um I think there's some really, really interesting stuff we're we're starting to see.
Um I I think the most notable thing is that like there's not an absolute
clear winner across the sort of like landscape right now.
There's basically a a sort of preter frontier that's emerged.
What one of the most important things if if listeners are like listening here, I think you should take away is that like any any anybody who gives you a benchmark score uh on an AI system that is a single number is is is uh is just marketing to you.
Um, because the reality is now with these AI reasoning systems, you have to report score on like a two-dimensional act.
You have to consider cost and efficiency alongside the accuracy.
And all these different lab providers have come out with different AR reasoning systems that sort of score differently.
They're trading off cost for accuracy at at different points.
So like if you want just like the absolute highest horse, you know, highest raw horsepower sort of cost and time is no option, O three high is gonna be your like clear winner today for that.
but if you're somebody who's saying, like, you know, hey, I want to plug in an AR easing system into an existing product I have where I I want like faster answers and I'm willing to sacrifice some raw horsepower for generality for like quicker response times, lower lower cost, you might look at something like Brock or Gemini two point four two point five pro thinking.
there there's not like a single like best best answer, which which I think is pretty interesting.
And and we haven't seen like this this sort of frontier is I think what all the labs are sort of working to to try and figure out, okay, how can we get accuracy as high as we can, but also we got to try and keep costs as low as we can down the human efficiency rolls.
actually one of the reasons these AR reasoning systems, I I would assert, uh, and I I don't have inside based upon the data, but like I from the outside looking, I think there are some interesting
Suspicions that would suggest that these like AR reasoning systems, at least today in their current form, have like relatively weaker product market fit um compared to the uh like non-A, the non-reasoning based systems, right?
The pure language model based based things.
Interesting.
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