Nvidia projects $673B in sales as AI demand widens
71–80 of 116 posts
Re: Nvidia projects $673B in sales as AI demand widens
#72Earlier quoted context omitted.
Yeah, I think there's a tendency to underestimate how much demand is still gated behind cost constraints. The market for this is HUGE. The PC era, call it 1975-2005, was one of the greatest wealth creation events in history, was characterized by the cost of the underlying commodity dropping mercilessly for the whole time. Each time it did, the space of problem you could solve with a PC would increase, to the point th…
> The market for this is HUGE. Source(s)?
Re: Nvidia projects $673B in sales as AI demand widens
#73Can anyone who actually understands finance please explain a couple things to me?
1. Are those accusations are true in a significant way, and are actually a bad thing?
2. This claimed $673B in sales, how much of it comes from NVIDIA's own money, invested into their clients? Is there any way to know that?
Re: Nvidia projects $673B in sales as AI demand widens
#74Earlier quoted context omitted.
I don't know about that. I made a fair bit every time Musk opened his face hole.
And I made a lot off oil futures in high school thinking I had a plan, but it was just gambling
Re: Nvidia projects $673B in sales as AI demand widens
#75Earlier quoted context omitted.
> Small models are rapidly growing in capability, require less compute to train and serve According to Jevons' paradox a reduction in resource requirements (improved resource efficiency for the same payoff) leads to an increase in demand. This stops working when demand for compute is completely exhausted, but we are very far from that. There's even some very silly predictions floating around (see the latest Dwarkesh…
There is no paradox, simply (a/b) increasing tells you nothing about a nor b. Jevons only “destroys” the (wrong) intuition that total b would decrease
Jevons paradox is a veridical paradox, which, as you said, means that it's a true statement that merely looks wrong because it is counterintuitive.
I know that some people think that the word "paradox" should be only used to refer to antinomy paradoxes which are often called "true paradoxes" (such as "this sentence is false") which lead to a contradiction without requiring a flaw in reasoning.
Re: Nvidia projects $673B in sales as AI demand widens
#76Earlier quoted context omitted.
> Small models are rapidly growing in capability, require less compute to train and serve According to Jevons' paradox a reduction in resource requirements (improved resource efficiency for the same payoff) leads to an increase in demand. This stops working when demand for compute is completely exhausted, but we are very far from that. There's even some very silly predictions floating around (see the latest Dwarkesh…
Yeah, I think there's a tendency to underestimate how much demand is still gated behind cost constraints. The market for this is HUGE. The PC era, call it 1975-2005, was one of the greatest wealth creation events in history, was characterized by the cost of the underlying commodity dropping mercilessly for the whole time. Each time it did, the space of problem you could solve with a PC would increase, to the point th…
I think this misses the actual limits here.
The problem isn't demand it's, "how much people are willing to spend on it".
Cheap AI has to be served on cheap compute, and if inference gets cheap enough to unlock massive usage numbers, by definition it also doesn't require anywhere near as much infrastructure per unit of demand.
Take DeepSeek serving ~100T tokens/day, depending on workload and utilization, you're potentially talking about only a few thousand last-gen GPUs. With current-gen GPUs maybe closer to ~1,000, and with Rubin even fewer I will be damned if I could get my hands on one.
That's the part I think people are missing when they extrapolate token demand into enormous infrastructure or AI revenue.
Yes usage will explode. But if the cost per unit collapses, the revenue doesn't necessarily go up with it.
You can't simultaneously argue that intelligence becomes so cheap that everyone uses enormous amounts of it, while also assuming customers will somehow spend trillions of dollars a year consuming it.
There is no obvious $1T customer-facing AI revenue number at the end of this rainbow in the short/medium term.
The average person isn't going to spend anything remotely comparable to what they spend on a car every year for an AI service. Even businesses have budgets now, huge demand doesn't matter if the willingness to pay isn't there.
The only path I can see to numbers like that is AI consuming existing business domains, even then it's very thin.
Say SaaS + legal + consulting + BPO + various other service industries collectively represent something like $10-20T globally.
Even if AI eventually replaces an enormous portion of that, it's probably not doing so at the same price. Why would customers switch otherwise?
Either the AI product has to be dramatically better, which is difficult for mature workflows, or dramatically cheaper which is much more plausible.
If it replaces $10-20T of existing services at roughly 1/10th or 1/100th (more likely) the cost, then you're looking at maybe a ~$1T AI revenue opportunity after replacing an absurdly large fraction of the existing service economy.
Who are now unemployed and can't pay for shit.
And that's before competition.
I think it's crazy to assume AI companies won't compete aggressively on price. As capabilities diffuse, smaller models catch up, inference hits pareto frontier the open-source alternatives have already improved and caught up, margins on routine intelligence should compress "hard" (emphasis on "hard").
We've already seen how difficult adoption can be even when the technology looks impressive on paper. Cheap here means 100x cheaper for 10x more demand that's a net 10x loss before any software or hardware optimizations.
So yes, I completely agree that cheap intelligence can bring an enormous amount of new usage.
"I just don't think usage means revenue." (you can plaster it on a wall if you want to, "usage doesn't mean revenue", if you want to find that out I have foss software bridge to sell)
The PC analogy actually reinforces this if you really think about it. Compute became "vastly more useful" while the cost per unit of compute collapsed. Society captured enormous value, but all computer companies are literal failing giants without the AI hype. Value got caught by people who provided productionization.
Now if people expect AI to self productize itself I am happy to tell your try it. We all saw how OpenAI fell behind Anthropic because they thought that would work...
Google couldn't productize the search, instead they sold the eye balls and web-real-estate. Maybe that's the AI business model, but that's not $1T worth given you need to unglue people from other stuff.
Unless we get something approaching genuine ASI producing so much additional economic value that entirely new trillions, I don't see a path to $1-2T in direct AI revenue from customers.
The market simply can't absorb that level of spending.
Demand can be effectively infinite at the right price. But I think people are delusional on HN and SF if they think that number is in Trillions like the investments seem to suggest.
I am not saying Nvidia will fall tomorrow but someone will have to pull the breaks before this car goes to hell.
Re: Nvidia projects $673B in sales as AI demand widens
#77I have not been paying much attention to the whole circular deal thing that NVIDIA is supposedly doing. As in, they invest in their clients, who buy their products. Can anyone who actually understands finance please explain a couple things to me? 1. Are those accusations are true in a significant way, and are actually a bad thing? 2. This claimed $673B in sales, how much of it comes from NVIDIA's own money, invested…
Re: Nvidia projects $673B in sales as AI demand widens
#78I have not been paying much attention to the whole circular deal thing that NVIDIA is supposedly doing. As in, they invest in their clients, who buy their products. Can anyone who actually understands finance please explain a couple things to me? 1. Are those accusations are true in a significant way, and are actually a bad thing? 2. This claimed $673B in sales, how much of it comes from NVIDIA's own money, invested…
Still that's not to say these companies aren't leveraging the Nvidia capital with others' in a way that magnifies or multiplies some of the effect.
But it looks like a second order contributor unless Nvidia's actions are acting like a backstop that causes way more risk and leverage to pile up in a way that could come tumbling down
Re: Nvidia projects $673B in sales as AI demand widens
#79What if there are no memory chips for people to build hardware with, using nvidia components?
SK Hynix (together with Samsung and Nvidia) claims $700B investment [1], Samsung itself is investing $70B, Micron $25B, Sandisk announced $31B today [2]
[1] https://asia.nikkei.com/business/technology/artificial-intel... [2] https://www.wsj.com/tech/kioxia-sandisk-to-invest-more-than-...
Re: Nvidia projects $673B in sales as AI demand widens
#80Earlier quoted context omitted.
> Small models are rapidly growing in capability, require less compute to train and serve According to Jevons' paradox a reduction in resource requirements (improved resource efficiency for the same payoff) leads to an increase in demand. This stops working when demand for compute is completely exhausted, but we are very far from that. There's even some very silly predictions floating around (see the latest Dwarkesh…
I don’t think this line of thinking is particularly robust because it ignores how AI is being used and where the resource usage is coming from. Right now there are a small number of very very resource intensive use cases that are being subsidized by OpenAI and Anthropic. There are people generating millions of lines of code because it’s basically free at the point of use, despite the code producing very little value.…
Surely this applies to fixed-price subscriptions, not per-token spend? Large enterprises (the "very very resource intensive" large-scale users) have to pay per token.