[judge123]

I'm wondering if 'slow AI' like this is a temporary bridge, or a whole new category we need to get used to. Is the future really about having these specialized 'deep thinkers' alongside our fast, everyday models? Or is this just a clunky V1 until the main models get this powerful on their own in seconds?

[onlyrealcuzzo]

It's not unreasonable to think that with improvements on the software side - a Saturn-like model based on diffusion could be this powerful within a decade - with 1s responses.

I'd highly doubt in 10 years, people are waiting 30m for answers of this quality - either due to the software side, the hardware side, and/or scaling.

It's possible in 10 years, the cost you pay is still comparable, but I doubt the time will be 30m.

It's also possible that there's still top-tier models like this that use absurd amounts of resources (by today's standards) and take 30m - but they'd likely be at a much higher quality than today's.

[regularfry]

The pressure in the other direction is tool use. The more a model wants to call out to a series of tools, the more the delay will be, just because it the serial process isn't part of the model.

[twobitshifter]

we’re optimizing for quality over performance right now, at some point the pendulum will swing the other way, but there might be problems that require deep thinking just like we have a need for supercomputers to run jobs for days today.