A week ago, analyst TD Cowen revealed that Microsoft had canceled leases "totalling a couple hundred MWs," with "at least two private data center operators across multiple US markets." The report also details how Microsoft "pulled back on converting negotiated and signed Statement[s] of Qualifications (SQQs)," which it added
If a new driver came out that gave Nvidia 5090 performance to games with gtx1080 equivalent hardware would you still buy a new video card this year?
It doesn’t make any sense to compare games and AI. Games have a well-defined upper bound for performance. Even Crysis has “maximum settings” that you can’t go above. Supposedly, this doesn’t hold true for AI, scaling it should continually improve it.
So: yes, in your analogy, MS would still buy a new video card this year if they believed in the progress being possible and reasonably likely.
Like games have diminished returns on better graphics (it’s already photo realistic few pay $2k on a GPU for more hairs?), AI has a plateau where it gives good enough answers that people will pay for the service.
If people are paying you money and the next level of performance is not appreciated by the general consumer, why spend billions that will take longer to recoup?
It’s still not a valid comparison. We’re not talking about diminished returns, we’re talking about an actual ceiling. There are only so many options implemented in games - once they’re maxed out, you can’t go higher.
That’s not the situation we have with AI, it’s supposed to scale indefinitely.
Current games have a limit. Current models have a limit. New games could scale until people don’t see a quality improvement. New models can scale until people don’t see a quality improvement.
I’m supposed to be able to take a model architecture from today, scale it up 100x and get an improvement. I can’t make the settings in Crysis 100x higher than they can go.
Games always have a limit, AI is supposed to get better with scale. Which part do you not understand?
It doesn’t make any sense to compare games and AI. Games have a well-defined upper bound for performance. Even Crysis has “maximum settings” that you can’t go above. Supposedly, this doesn’t hold true for AI, scaling it should continually improve it.
So: yes, in your analogy, MS would still buy a new video card this year if they believed in the progress being possible and reasonably likely.
Like games have diminished returns on better graphics (it’s already photo realistic few pay $2k on a GPU for more hairs?), AI has a plateau where it gives good enough answers that people will pay for the service.
If people are paying you money and the next level of performance is not appreciated by the general consumer, why spend billions that will take longer to recoup?
And again data centers aren’t just used for AI.
It’s still not a valid comparison. We’re not talking about diminished returns, we’re talking about an actual ceiling. There are only so many options implemented in games - once they’re maxed out, you can’t go higher.
That’s not the situation we have with AI, it’s supposed to scale indefinitely.
Current games have a limit. Current models have a limit. New games could scale until people don’t see a quality improvement. New models can scale until people don’t see a quality improvement.
I’m supposed to be able to take a model architecture from today, scale it up 100x and get an improvement. I can’t make the settings in Crysis 100x higher than they can go.
Games always have a limit, AI is supposed to get better with scale. Which part do you not understand?