Discussion
Jensen Huang says Nvidia is pulling back from OpenAI and Anthropic, but his explanation raises more questions than it answers
dmix: A better headline:Nvidia rushed some investments in both companies just before they went public and are now are just waiting to get paid.
tl2do: 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.
returnInfinity: And why should a business do that? Limited chip production capacity be spent on most profitable ventures.
chii: 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.
SamDc73: The Stargate money didn’t show up I guess, and now the whole gridlock is collapsing?
andrewstuart: The computer industry is jam packed with single points of supply chain risk.
wingmanjd: 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.https://nvidianews.nvidia.com/news/nvidia-announces-financia...
PenguinCoder: It is insanely stupid that '4B' with a B, is 'too small' of an operating space.
tl2do: 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.
yndoendo: 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.
SR2Z: 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.
01100011: Nvidia could flip a switch and start competing with former customers. They have the talent, the models, the HW, and they know how to quickly build out DCs.
y1n0: That would not go well for nvidia. Why would they want to enter and compete in a market where everybody is losing money? And in so doing alienate the people that make them profitable?
mlyle: If those customers end up profitable, it could be tempting for nVidia to vertically integrate.I don't think it's as easy as others say, though.
wood_spirit: And they have a moat - they can control the quantity and quality of hardware flowing to their competitions?
TheDong: > AI has reached a state of software issue, not hardwareCitation 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.
creddit: They don't have the talent.
dylan604: Great, when the AI bubble bursts, they can repackage their AI chips into consumer cards! /s
whynotminot: As long as both companies remain stable and viable, there's probably limited upside to pouring more money into them. If they fail, and bring down the AI ecosystem with them, that is very bad news for Nvidia. So they've been there nurturing their success and providing capital to backstop their exponential growth.You can see Nvidia stepping in throughout the ecosystem with confidence boosting investments where needed. They haven't just supported Anthropic and OpenAI.If OpenAI and Anthropic succeed, and get their business fly-wheels fully spinning, they don't necessarily need more capital from Huang. Ultimately the goal of Nvidia is to profit from their long-term success by selling them GPUs for a long, long time. The goal isn't to keep plowing money into them forever.
iso-logi: Are you suggesting Nvidia doesn't have talent in the AI industry?NVIDIA has released NVIDIA Deep Learning Super Sampling (DLSS) and a Frame Generation model, NVIDIA Super Resolution (VSR) being the most popular/well known models. (DLSS is outstanding technology, despite the sometimes misleading marketing).Nvidia has released countless models:Alpamayo 1 (Car navigation model) Cosmos-Reason2 (reasoning vision language model) Nemotron 3 (Large Language Model series) Llama-Nemotron (Large Language Model series) Isaac GR00T (VLA Models) Nemotron OCR (Optical Character Recognition models)Take a look at their HuggingFace Collections, almost 100 different collections with countless models inside each collection: https://huggingface.co/nvidia/collections
bigstrat2003: 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.
rl3: NV has a massive amount of AI talent, and a lot of them have PhDs.Are you suggesting they're lacking on the ultra-high-end? That is: 5-10M+ in comp to sign a single researcher/IC; industry rock star territory.Major frontier AI labs do tend to have that type of talent in abundance. I'm sure NV has the equivalent when it comes to hardware design.
paradoxyl: And maybe TSMC should make cellphones? If you're higher up the supply chain why go downstream into risk? It's financially irresponsible.
eitally: They don't, not directly. That's why they've generally been winding down DGX Cloud. However, lots of folks dramatically underestimate their frontier models (Nemotron family), and they license those models (free) for embedding in MANY other, large tech companies' own products and platforms, which either directly or indirectly consume massive quantities of GPU time.Nvidia is best known for selling huge volumes of GPUs to the hyperscalers & neoclouds, but I don't think lots of folks appreciate how many GPUs ISVs like Snowflake, Databricks, Teradata, etc consume, too, just by virtue of designing much of their internal products around CUDA & Nemotron.
LarsDu88: That's not how a smart business runs and that's now how Nvidia operates.Jensen is smart. He's gone through over 30 years of tech cycles.Nvidia actively commoditizes the LLM models. Look at Nemotron. They've avoided making a SOTA model solely to keep the hyperscalers (aka crack addicts) coming back for more GPUs.As soon as the bubble bursts, they can release some open weight NemoMambaDiffusiontron and keep folks buying GPUs to run the damn thing.It still wouldn't be smart to do so, as this would fall into the common business pitfall of thinking you could easily do the next stack layer of work.
reilly3000: 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.
