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Nvidia Sales Jump 56%, a Sign the A.I. Boom Isn’t Slowing Down
(www.nytimes.com)
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this post was submitted on 28 Aug 2025
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Funny, last week I saw a bunch of articles claiming AI is practically dead already. And now this?
Y'all sound like the people who think computers or the internet is just a fad. Shit like this is here to stay, wether you like it or not.
Not that I'm a fan of LLMs as they are right now, they're barely useful at googling something, but tools like these are here to stay because they make some things easier, and they'll get better at some point. Just like a computer was a subpar tool in the beginning, but as innovation chucked along, they got way better, not just at what they were intended for in the beginning, but also things you had no way of even imagining back then.
Really? Companies are going to keep building datacenters that need entire nuclear reactors to themselves without any of that converting into revenue? This is going to keep going forever in your mind?
The power usage is massively overstated, and a meme perpetuated by Altman so he’ll get more more money for ‘scaling’. And he’s lying through his teeth: there literally isn’t enough silicon capacity in the world for that stupid idea.
GPT-5 is already proof scaling with no innovation doesn’t work. So are open source models trained/running on peanuts nipping at its heels.
And tech in the pipe like bitnet is coming to disrupt that even more; the future is small, specialized, augmented models, mostly running locally on your phone/PC because it’s so cheap and low power.
There’s tons of stuff to worry about over LLMs and other generative ML, but future power usage isn’t one.
Except none of these companies are making money. Like almost literally none. We're about three years into the LLM craze, and nobody has figured out how to turn a profit. Hell, forget profit, not bleeding through prodigious piles of cash would be a big deal.
Nods vigorously.
The future of LLMs basically unprofitable for the actual AI companies. We are in a hell of a bubble, which I can’t wait to pop so I can pick up a liquidation GPU (or at least rent one for cheap).
That doesn’t mean power usage is an existential issue. In fact, it seems like the sheer inefficiency of OpenAI/Grok and such are nails in their coffins.
Power usage is what's sucking the cash. What else could it be? Not all of these companies are building out lots of datacenters the way OpenAI is. They built what they have, and are now trying to make money on it.
The companies that are charging for AI are charging about as much as buyers are willing to pay, but it's orders of magnitude too small to cover their costs. The big cost is power usage.
On the training side, it’s mostly:
Paying devs to prepare the training runs with data, software architecture, frameworks, smaller scale experiments, things like that.
Paying other devs to get the training to scale across 800+ nodes.
Building the data centers, where the construction and GPU hardware costs kind of dwarf power usage in the short term.
On the inference side:
Sometimes optimized deployment frameworks like Deepseek uses, though many seem to use something off the shelf like sglang
Renting or deploying GPU servers individually. They don’t need to be networked at scale like for training, with the highest end I’ve heard (Deepseek's optimized framework) being like 18 servers or so. And again, the sticker price of the GPUs is the big cost here.
Developing tool use frameworks.
On both sides, the biggest players burn billions on Tech Bro “superstar” developers that, frankly, seem to Tweet more than developing interesting things.
Microsoft talks up nuclear power and such just because they want to cut out the middleman from the grid, reduce power costs, reduce the risk of power outages and such, not because there’s physically not enough power from the grid. It’s just corporate cheapness, not an existential need.
A lot will fail, sure, but that happens in literally every single developing industry. There are plenty of industries out there that aren't profitable, but are still going. Tesla wasn't profitable between 2003 and 2020, yet here we are, where they not only make profit, but they've kickstarted the electric cars industry. And that's despite that they sell shitty cars and their CEO is a nazi.
What AI companies are profitable? Besides the one selling shovels in a gold rush.
They will be profitable in ten years after everything crashes and only a few are left
Definitely a bubble to be burst at some point unless we are able to harness energy and reduce waste substantially better than now.
Two things can be true. AI is here to stay, and we're in a bubble. Look at the dot com crash, the bubble super popped, yet we still have the web.
Its not the AI tech thats gonna die, it's its extreme overvaluation.
Of course. Just like VR, AR, the Metaverse, NFTs, cryptocurrency, and hundreds of other boom-and-bust, hype-cycle remnants. "AI" is a bubble. "AI" will burst. The tech will continue, just without the hype and the cohort wildly over-funded moonshot start-ups.
I look forward to the day when ROI-focused tech executives aren't trying to cram non-intelligent LLMs into roles where they do not excel. Let people find their own uses, on their own terms for these things. Perhaps someday people will train bespoke, subject-specific ML tools on their laptops in a matter of minutes with a single click, and it will be an unremarkable part of their day. I'd like to see that.
Crypto is still here, we had a StarCraft tournament funded in part by Bitcoin Cash just recently
Exactly.
Well it's "here to stay" I agree. But there are some real economic indicators that it is also a bubble. First, the number of products and services that can be improved by hamfisting AI into them is perhaps reaching critical mass. We need to see what the "killer app" is for the subsequent generation of AI. More cool video segments and LLM chatbots isn't going to cut it. Everyone is betting there will be a gen 2.0, but we don't know what it is yet.
Second, the valuations are all out of whack. Remember Lycos, AskJeeves, Pets.com etc? During the dotcom bubble, the concept of the internet was "here to stay" but many of the original huge sites weren't. They were massively overvalued based on general enthusiasm for the potential of the internet itself. It's hard to argue that's not where we are at with AI companies now. Many observers have commented the price to earnings ratios are skyhigh for the top AI-related companies. Meaning investors are parking a ton of investment capital in them, but they haven't yet materialized long-term earnings.
Third, at least in the US, investment in general is lopsided towards tech companies and AI companies. Again look at the top growth companies and share price trends etc. This could be a "bubble" in itself as other sectors need to grow commensurate to the tech sector, otherwise that indicates its own economic problems. What if AI really does create a bunch of great new products and services, but no one can buy them because other areas of the economy stalled over the same time period?
"Nvidia had good sales in the last 3 months" doesn't necessarily conflict with whatever drove those articles last week...
"A technology got more useful in the past" isn't a compelling reason to argue something else will get more useful...
Use your critical thinking skills lol
Are you seriously arguing that AI and LLMs won't get better? For real? In that case I'm sorry, but you're going to be left behind like 95% of the people older than 50 who didn't bother to learn how to use a pc properly.
You know that technology doesn't actually get better by default, right? It reaches plateaus. Some things are just dead ends.
Have you bought any bubble memory recently?
AI is a very generic term and people should stop using it synonymously with LLM which is a very specific thing.
LLMs have the hallucination problem, and that is a fundamental aspect of the technology that makes it unfit for many of the purposes that are driving investment.
If I'm somehow wrong and LLM based tools actually become useful, I can learn them then. "Use shitty tools or you'll get left behind!" Is a completely stupid argument - "skills" in using a shitty tool probably won't transfer to using this hypothetical good tool anyway.
And just to reiterate, the argument of "the internet/smart phones/whatever was revolutionary so this is too", even though so far all we really have is "some ok sometimes coding tools", "search that lies sometimes", "summary that lies sometimes" is completely stupid. There are plenty of technologies that didn't become part of our daily lives as well.....