Instead of pouring more money into OpenAI and Anthropic, Nvidia should invest more in expanding production capacity for the RTX 5000 series and future generations. High-end consumer GPU availability is still constrained, especially for the RTX 5090, and street prices remain elevated. Nvidia should come back to the consumer side.
Datacenter income for nVidia last quarter was something like 62B vs the gaming market of <4B. While not quite a rounding error, it feels like the gaming market is just too small for them to put more resources toward it for us consumer folks.
One strategic reason is to remove oxygen from competitors. Otherwise someone will scoop up the gaming market and put the proceeds into developing technology to compete with NVIDIA in the more lucrative AI space.
I wonder who is going to fill the gaming market if AI market focused companies would simply outbid them during manufacturing? All available and not yet available manufacture is pivoting to AI market
“I wouldn’t pick up $20 if there was $100 on the ground!”
Most people would pick up both.
These economic proclamations don’t seem to make sense, when applied to different contexts — which suggests what you’re saying might be folk wisdom rather than sound theory (and greatly over simplifying the problem).
You’re also discounting ecosystem effects — gaming GPUs driving demand for datacenter and workstation GPUs as hobbyist experimentation turns into industrial usage. We don’t know what would happen if nVidia stopped suppressing the GPU market, because it’s never been tried — nVidia has always viciously undercut their own grassroots.
> “I wouldn’t pick up $20 if there was $100 on the ground!” Most people would pick up both.
No, it’s more like there’s a massive pile of both $20s and $100s on the ground. You wouldn’t waste time running between the two, you’d focus on the $100s
if you're within reach of both, then it's not a choice, and there's no opportunity cost in picking just one - you'd be taking both.
If not within reach of both but just one, and you picking one up means someone else might pick up the other, then which would you choose? The other is then by definition, the opportunity cost.
You’re standing on a traffic island in the middle of a busy road. The lights change allowing you to cross. On one side there is a $20 note, on the other there is a $100 note. Which side do you go to first?
But so many gamers want to buy GPUs and can’t because they are sold out or won’t because they are super price inflated. Wouldn’t the gaming market be larger if the products were actually available and at their actual MSRP?
Nvidia can't sell 10x the number of GPUs they sell. As much as the supply issues are discussed, it would likely take them a long time to just double the market. They could try to become the vendor of choice for the PS6/next xbox, but that's a big strategy shift for again maybe double the market, not 10x the market.
On the other hand right now the market doesn't seem to think that the >60bn of datacenter revenue is going away or even going to slow down _growing_ any time soon. Just adding 10% more revenue there is worth more than doubling their GPU business which they likely can't do.
I am not saying it would be anywhere near equal, just that it would be "bigger" than 4B if it wasn't so constrained.
>On the other hand right now the market doesn't seem to think that the >60bn of datacenter revenue is going away or even going to slow down _growing_ any time soon.
That is not substantiable. AI bubble is wealthy hype like a single drop of blood can be used to validate 100 different diagnostic test. Reality is parts per million fails this along with reusable medium. Wealth latches to idiocy.
Gaming and CAD market are real expectations that latch to reality. Grow the education systems and grow both. So is matrix math, such as hashing.
AI has reached a state of software issue, not hardware. And the divergence of AI hardware does not equate to CAD and Gaming math.
How many of the last ten years have had some kind of "temporary" GPU shortage? It was crypto, now it's LLMs, who knows what's next?
The only winning strategy for these guys is to exploit the market for all it's worth during shortages and carefully control production to manage the inevitable gluts.
> AI has reached a state of software issue, not hardware
Citation very much needed.
At the very least, OpenAI seems to believe more and larger datacenters is the path to better models... and they've been right about that every time so far.
Why would they do that? They launched the DGX Spark last year with multiple hardware OEMs selling flavors of the reference device (Dell, Lenovo, Asus). That contains a desktop-sized Grace Blackwell architecture GPU (GB10), and word on the street is that they're moving into laptops this year. Their market is the same market Apple is pitching the MacBook 5 Pro/Max, too: devs wanting local models. It's not currently a large market, but it's growing quickly. It makes far more sense for Nvidia to build hardware to service this market than to overly focus on their gaming lines. RTX GPUs are sell once. GB-containing consumer devices are "sell once, but then collect recurring revenue when the workloads those developers build hit production on a cloud somewhere."
> Nvidia should invest more in expanding production capacity
Not if they expect build out of AI data centers to slow down. Once both OpenAI and Anthropic goes public there's going to be a pressure on them to either turn a profit or at least have the stock price go up. One way that can happen, if subscriptions, government contracts and ads aren't working, is cutting back on cost. Cutting costs means doing more with the existing GPUs and datacenters and running them for longer.
Even if the both companies can turn a profit, there's going to be a pressure to not spend on datacenters, if existing facilities can be pushed harder or used more efficiently.
OpenAI and Anthropic going public is going to mean reduced spend on datacenters and GPUs.
If I were Nvidia, I would give more attention to consumer GPUs to hedge my bets. When (not if) this AI bubble pops, their AI customers will become worthless to them very quickly as they won't be buying more GPUs. And when that day comes, I would want to still have consumers to sell to, rather than have them all buying from AMD because I ignored them.
the only way this argument works is if AMD somehow creates GPUs that run circles around nvidia and boxes them out price wise, and at the same them themselves don’t start prioritizing enterprise customers more. otherwise consumers will choose the best performing gpu possible, generally people don’t care about companies turning their backs on consumers in this way
I should admit this is partly my personal preference.
That said, gaming has been a durable market for decades, and there’s a strong cycle where better chips enable better games, which then drives more demand for better chips.
nvidia will come back to the consumer side when the AI side stops being as profitable. Right now, it still seems like the margins for AI hardware is way higher than the same consumer product would sell for.
This leaves an opening for Intel to get in the game. Their new lines have a pretty decent value proposition for mid-tier gaming. If they focused on the higher end they would could own it. There is massive latent demand because of the NVidia situation. It’s easier to make money from than the R&D to build the next Blackwell but there is just as much demand for local/private models on the prosumer level.
I am Japanese. I want to share a well-known Japanese idea: 人は見た目が9割 ("people are judged 90% by appearance"). It is ironic because it goes against our common sense that substance should matter more than appearance. The intention of this idea is to emphasize the importance of first impressions.
I think the AIDMA model is still relevant. I've seen similar dashboards elsewhere, but FUBAR Daily's design keeps me coming back.
The linked article seems to suggest that rather than "appearance" what's actually meant is "anything non-verbal"? In which case the related english language thing to look for is writings on the importance of the non-verbal aspects of communication, of which there are a lot.
Also, why does the linked article (容姿) contain a fully nude image? I don't understand the usefulness or significance (and wouldn't have expected it to be permitted regardless). https://ja.wikipedia.org/wiki/%E5%AE%B9%E5%A7%BF
Yes. I do not understand how an article about physical appearance meaningfully benefits from a nude photo. I thus find myself wondering if the machine translation perhaps lost some important nuance.
In Japan, my country, this looks a bit different. A lot of electricity still comes from oil- and gas-fired plants. The mechanics differ (gas turbines vs. car engines), but in both cases we’re still relying on combustion. I suppose some countries have the same issue.
Transmitting on AM broadcast frequencies is generally prohibited unless it meets an extremely low-power exemption , even if you have amateur license(I have a Japanese amateur radio license). A practical way to reduce risk is to put a large resistor before the antenna so the radiated power stays within that exemption. You could start with 100 MΩ; if the receiver cannot pick it up, try 10 MΩ, and so on.
Given GPIO frequency limits, reproducing a beautiful sine wave for a 1000 kHz carrier is a real challenge. He should borrow an oscilloscope and measure the output waveform.
An oscilloscope is the wrong tool for that. You can tell the difference between kind-of-square and kind-of-sine wave using one, but hardly more. At least DSO often have a FFT option and on the new ones with 12bit ADC that might actually be more than just a gimmick.
You'd want to use a spectrum analyzer to verify that other frequencies are present only at very low levels. TinySA might be the cheapest option or an used Digilent Analog Discovery.
With AI coding agents, reverse-engineering a codebase into a spec doc has become much more feasible, including details below the usual spec level. That gives PMs a practical way to understand systems more deeply than before, without having to land production diffs themselves. So to "Why should PMs code?" my take is: sometimes they should, but now there are multiple levels of involvement depending on what understanding is needed.
The article doesn't address where human oversight is actually necessary. I sometimes use AI for simple spell checking—requiring human review for that would be over-complication. In some more difficult tasks, having AI review AI output works fine for me.
Contrast with Japan, my country, where bike accidents have risen 3 years straight and now make up 20%+ of all traffic incidents. Japan's response: heavier fines. Helsinki's: redesign the system. Big difference in philosophy.
I'm not sure where I saw it but I think I read that most recent increases in Japanese bicycle accidents are from bicycles turning right. It seems like the push to make bicycles use the road more (to reduce pedestrian vs bicycle accidents, which are still rising) had the unintentional consequence of making cyclists more likely to perform right turns like cars and motorcycles. However the road law actually requires bicycles to do two-stage turns, which they were more likely to do when they were riding on the sidewalk, and what cyclists in Amsterdam and Copenhagen recommend doing. So, I mean, sure, more cycling paths would improve the situation by making cyclists perform 2 stage turns, but there's nothing really stopping us from doing it now.
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