Exactly. If AI were to scale like the people at OpenAI hoped, they would be celebrating like crazy because their scaling goal was literally infinity. Like seriously the plan that openai had a year ago was to scale their AI compute to be the biggest energy consumer in the world with many dedicated nuclear power plants just for their data centers. That means if they dont grab onto any and every opportunity for more energy, they have lost faith in their original plan.
I’m gonna disagree - it’s not like DeepSeek uncovered some upper limit to how much compute you can throw at the problem. More efficient hardware use should be amazing for AI since it allows you to scale even further.
This means that MS isn’t expecting these data centers to generate enough revenue to be profitable, and they’re not willing to bet on further advancements that might make them profitable. In other words, MS doesn’t have a positive outlook for AI.
unexposedhazard@discuss.tchncs.de 1 year ago
Blue_Morpho@lemmy.world 1 year ago
If you can achieve scaling with software, you can delay current plans for expensive hardware. 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?
When all the Telcos scaled back on building fiber in 2000, that was because they didn’t have a positive outlook for the Internet?
Or when video game companies went bankrupt in the 1980’s, it was because video games were over as entertainment?
There’s a huge leap between not spending billions on new data centers ( which are used for more than just AI), and claiming that’s the reason AI is over.
FooBarrington@lemmy.world 1 year ago
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.
Blue_Morpho@lemmy.world 1 year ago
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.
FooBarrington@lemmy.world 1 year ago
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.
Takumidesh@lemmy.world 1 year ago
If buying a new video card made me money, yes.
This doesn’t really work, because the goal when you buy a video card isn’t to have the most possible processing power ever and playing video games doesn’t scale linearly so having an additional card doesn’t add anything.
If I was mining crypto, or selling GPU compute (which is basically what ai companies are doing) and the existing card got an update that made it perform on par with new cards, I would buy out the existing cards and when there are no more, I would buy up the newer cards, they are both generating revenue still.
Blue_Morpho@lemmy.world 1 year ago
But this is the supposition that not buying a video card makes you the same money. You’re forecasting free performance upgrades so there’s no need to spend money now when you can wait and upgrade the hardware once software improvements stop.