I understand the point that you are making but why do we have to fulfill the supply just as much as demand. There is a demand frenzy going on right now with still being substantially subsidized.

Why do we have to burn tokens just for the sake of it if we aren't finding any actual productive use of them?

> And this might slow down the funding enough that they never reach escape velocity with the training run scaling. But we'll see.

I would consider this to be good rather than bad, or just neutral...? Given the past record of these companies, I wouldn't try to wish them luck for reaching escape velocity, as if I feel like perhaps it can have more net harm than positive.

And especially so if you are already suggesting that current models are good enough for your work already. More improvements or escape velocity might not really translate anywhere to the actual work that you are doing economically but it could translate into a more consolidated form of wealth and control.

I am imagining that your workload is quite complicated and that, the AI being good enough means that it is most likely good "enough" for other use cases as well (that "enough" is doing quite some heavy weight lifting here)

So what is the point of advancing further to reach escape velocity. The good argument (for the sake of neutrality) that i see is are advances within science but that's kinda about it whereas the downsides of p(doom) as many are now genuinely suggesting is more terrifying.

Perhaps it can be worth it to ask, shall we stop or just stopping and asking what's the point. A form of self introspection on what these companies ideals actually wanted when they were formed and if they have completed it or not, but I suppose when trillions of dollars depend on you, you do have some incentives to not stop. We will have to wait and see how it all pans out.