Could there be a benefit to releasing a new model, slowly dumbing it down over a couple months, then releasing a new model that’s marginally if at all better than the original to create a perceived improvement when in reality there isn’t really one?
For an industry that’s stagnant in progress yet relies on new frequent releases to survive (non-progress being an existential risk), this could make sense.
I have no idea if that’s what’s happened, I completely pulled it out of my butt. And I have no idea is the actual frontier is stagnating.
I have not been attributing it so much to malice, just that all the major cloud vendors seem to be running at full capacity, and can't build new datacenters fast enough. I just kind of assumed that as they got busy training newer models, that they allocated less resources to handle the existing systems, because they aren't able to get more capacity right now.
I’m not sure why this point keeps coming up — if your service/product is so popular that it’s capacity-constrained, then the answer is to raise prices, not degrade service, because the demand should be inelastic.
Raising prices also has second order effects, like consumer and business expectations around how widespread the tech can be. Valuations depend on it being reasonably affordable to roll out on a much more massive scale than today. If people get the impression that it seems too limited to very rich people (200 is affordable for a North American / Western European professional), the impression about the trajectory will change.
talon8635 · · focus · HN ↗
For an industry that’s stagnant in progress yet relies on new frequent releases to survive (non-progress being an existential risk), this could make sense.
I have no idea if that’s what’s happened, I completely pulled it out of my butt. And I have no idea is the actual frontier is stagnating.
briffle · · focus · HN ↗
Denzel · · focus · HN ↗
bonoboTP · · focus · HN ↗