That’s not to say I’m brave enough to short NVDA.
I am a long time fan of Dave Sacks and the All In podcast ‘besties’ but now that he is ‘AI czar’ for our government it is interesting what he does not talk about. For example on a recent podcast he was pumping up AI as a long term solution to US economic woes, but a week before that podcast, a well known study was released that showed that 95% of new LLM/AI corporate projects were fails. Another thing that he swept under the rug was the recent Stanford study that 80% of US startups are saving money using less expensive Chinese (and Mistral, and Google Gemma??) models. When the Stanford study was released, I watched All In material for a few weeks, expecting David Sack’s take on the study. Not a word from him.
Apologies for this off-topic rant but I am really concerned how my country is spending resources on AI infrastructure. I think this is a massive bubble, but I am not sure how catastrophic the bubble will be.
The US is burning good will at an alarming rate, how long will countries keep paying a premium to be spied on by the US instead of China?
This country used to have congressional hearings on all kinds of matters from baseball to the Mafia. Tech collusion and insider knowledge is not getting investigated. The All-in podcast requires serious investigation, with question #1 being “how the fuck did you guys manage to influence the White House?”.
Other notes:
- Many of them are technically illiterate
- They will speak in business talk , you won’t find a hint of intimate technical knowledge
- The more you watch it, the more you realize that money absolutely buys a seat at the table:
https://bloximages.chicago2.vip.townnews.com/goskagit.com/co...
(^ Saved myself another thousand words)
I mean. I think some of us knew this. There's a lot of issues with AI, some psychological, some are risk adverse individuals who would love to save hours, weeks, months, maybe years of time with AI, but if AI screws up, its bad, really bad, legal hell bad, unless you have a model with a 100% success rate for the task, it wont be used in certain fields.
I think in the more creative fields its very useful, since hallucinations are okay, its when you try to get realistic / look reasonably realistic (in the case of cartoons) that it gets iffy. Even so though, who wants to pay the true cost of AI? There's a big uphill cost involved.
It reminds me a lot of crypto mining, mostly because you need an insane amount to invest into before you become profitable.
Anyone who's listened to him (even those who align with him politically) for an extended period of time can't help but to notice so obviously so self interested to the point of total hypocrisy—the examples of which are too many to begin to even wanting to enumerate. Like—take the Trump/Epstein stuff, or the Elon/Trump fallout—topics he would absolutely lose his sh*t over if these were characters on the left. I find it hard to believe anyone actually ever took him seriously. Branding myself as a fan of his would just be a completely self-humiliating insult to my intelligence and my conscience IMO.
At least for me, Google has some real cachet and deserves kudos for not losing money selling Gemini services, at least I think it is plausible that they are already profitable, or soon will be. In the US, I get the impression that everyone else is burning money to get market share, but if I am wrong I would enjoy seeing evidence to the contrary. I suspect that Microsoft might be doing OK because of selling access to their infrastructure (just like Google).
A major reason Deepseek was so successful margins wise was because the team heavily understood Nvidia, CUDA, and Linux internals.
If you have an understanding of the intricacies of your custom ASIC's architecture, it's easier for you to solve perf issues, parallelize, and debug problems.
And then you can make up the cost by selling inference as a service.
> Amazon and I think Microsoft are also working on their own NVIDIA replacement chips
Not just them. I know of at least 4-5 other similar initiatives (some public like OpenAI's, another which is being contracted by a large nation, and a couple others which haven't been announced yet so I can't divulge).
Contract ASIC and GPU design is booming, and Broadcom, Marvell, HPE, Nvidia, and others are cashing in on it.
A long time ago I worked as a contractor at Google, and that experience taught me that they don’t like things that don’t scale or are inefficient.
My opinion, the problems for NVIDIA will start when China ramp up internal chip manufacturing performance enough to be in same order of magnitude as TMSC.
Wont it be enough to just solder on a large amount of high bandwidth memory and produce these cards relatively cheaply?
Perf is important, but ime American MLEs are less likely to investigate GPU and OS internals to get maximum perf, and just throw money at the problem.
> solder on a large amount of high bandwidth memory and produce these cards relatively cheaply
HBM is somewhat limited in China as well. CXMT is around 3-4 years behind other HBM vendors.
That said, you don't need the latest and most performant GPUs if you can tune older GPUs and parallelize training at a large scale.
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IMO, Model training is an embarrassingly parallel problem, and a large enough cluster leveraging 1-2 generation older architectures that is heavily tuned should be able to provide similar performance to train models.
This is why I bemoan America's failures at OS internals and systems education. You have entire generations of "ML Engineers" and researchers in the US who don't know their way around CUDA or Infiniband optimization or the ins-and-outs of the Linux kernel.
They're just boffins who like math and using wrappers.
That said, I'd be cautious to trust a press release or secondhand report from CCTV, especially after the Kirin 9000 saga and SMIC.
But arguably, it doesn't matter - even if Alibaba's system isn't comparably performant to an H20, if it can be manufactured at scale without eating Nvidia's margins, it's good enough.
Cerebras get their chipped fabbed by them. I assume Eucyld will have their chips fabbed by them.
If there's orders, why would they prefer NVIDIA? Customer diversity is good, is it not?
Money talks. Apple asked for first dips a while earlier (exclusively).
AMD are, Cerebras are, I assume OpenChip's and Euclyd's machines will be.
Sure, but in my example Apple got access exclusively for a few months to a newer node, which would make a world of difference if you compete in the same space.
Their multiples don't seem sustainable so they are likely to fall at some point but when is tricky.
They've been trying really hard to pivot and find new growth areas. They've taken their "inflated" stock price as capital to invest in many other companies. If at least some of these bets pay off it's not so bad.