Nick Grossman
speaker
350 appearances
1 recordings
1 series
first heard Jul 2026
last heard 20 Jul
Nick Grossman’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 Jul 2026 with 1.
Appearances
And then the market, you know, goes away.
And then the question is, what's the difference between having the general intelligence and like specific intelligence?
And, like, trade the market with them.
That you could just turn the labs into prop funds.
Yeah, and it's, you know, that's...
I guess a point you're making is like, I think we're just at the beginning of understanding how superintelligence goes to market in what package, right?
Because like right now, the labs are selling the models as APIs or as consumer applications, but you can also internalize them, right?
So like you could
in theory, develop a frontier model and not sell it and just turn it into a trading fund or something else, you know, where like it's a little bit like Google, you know, channeling it back in the day, channeling all of its data into making its own product better.
And and we haven't, you know, seen any of the big model companies go this way, but it's not inconceivable that there could ultimately be a better business model for developing superintelligence than the ones that we're familiar with today.
Going down from the application layer.
Correct.
They just have unique data, right?
And if you have that big of a footprint with that much user coverage and that much data, I think it's potentially possible to do that depending on what type of model you want to train.
I don't know how...
how broad their model is versus how narrow.
But presumably they, you know, have enough data to train.
And I think any really scaled application company is going to have enough data to train models to do certain things.
And then there's a question back to your point at the beginning about the pace of generalized models versus specialized models and how those continue to shake out.
But I think we'll continue to see application layer companies go down to the model layer and also the sort of big labs, like go up to the application layer and we'll see where it all lands.
Showing 161–180 of 350 · page 9 of 18
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