I'm less sure of the fact that ending subsidized token consumption (in isolation) will happen and change this. I think we've seen this play out before with other tech companies where discounting early use ends up entrenching demand and allowing the company to build larger and more efficient infrastructure.
I'm slightly _more_ convinced (still not all that strongly) that the rising cost of memory and chips, data center construction that gets outpaced by computing demand, increasing energy costs, and low switching costs for customers will force the model labs to make changes that increase the barrier to entry (either via higher pricing, more restrictive rate limiting, etc.). or force their customers into longer term commitments.
> I think we've seen this play out before with other tech companies where discounting early use ends up entrenching demand and allowing the company to build larger and more efficient infrastructure.
We've also seen failures who were convinced "they would make it up in volume." I guess the bet is that infra will get that much more efficient, but it's not clear how much slack there is.
A lot - and over the coming 2 years, even more. Utilization rates are under 50% across the board, and special and cheaper chips are coming out all the time for inference. And a truckload of research - TurboQuant, HC (deepseek), etc, etc..
How is that possible when the cost of memory and hard drives have gone up 3x+ in the last six months? Maybe cheaper if you're OAI or one of the lucky companies Nvidia is propping up. Everyone else is getting screwed.
Sorry but I don't really see how this contradicts what I said in context i.e. both our statements are compatible in the context of what I was replying to
Even so, frontier models get bigger and more complicated, and agentic workflows consume exponentially more tokens than the simple chat windows of two years ago.
I agree that the amount people pay for these services is very unlikely to decrease (i.e. Blinn's Law but for tokens). Still, the current level of "intelligence" will eventually become available for a very low price almost surely. Really I simply don't see how you can disagree with the parent's comment "There is no world in which AI is not used extensively in all employment going forward." Honestly I'd like to understand the mindset, is it mainly that you dislike working with these tools/hope they don't get imposed on you or did you actually find them harmful in your work in some way and think they are overvalued?
I'm slightly _more_ convinced (still not all that strongly) that the rising cost of memory and chips, data center construction that gets outpaced by computing demand, increasing energy costs, and low switching costs for customers will force the model labs to make changes that increase the barrier to entry (either via higher pricing, more restrictive rate limiting, etc.). or force their customers into longer term commitments.