Earlier quoted context omitted.
Why mention it if you're not gonna link it?
Because paywall.
Nvidia’s $589B DeepSeek rout
741–750 of 1001 posts
Re: Nvidia’s $589B DeepSeek rout
#742Earlier quoted context omitted.
You can train, or at least run, llms on intel and less powerful chips
> You can train, or at least run, llms on intel and less powerful chips The claimed training breakthrough is an optimization targeting NVidia chip, not something that reduces NVidia's relative advantage. Even if it is easily generalizable to other vendors hardware, it doesn't reduce NVidia's advantage over other vendors, it just proportionately scales down the training requirements for a model of a given capacity. Wh…
It's not an optimization targeting Nvidia chips. It's an optimization of the technique through and through regardless of chip
But your point is well taken and perhaps both mine and GP's metaphors break down.
Either way, we saw massive spikes in demand for Nvidia when crypto mining became huge followed by a massive drop when we hit the crypto winter. We saw another massive spike when LLMs blew up and this may just be the analogous drop in demand for LLMs
Re: Nvidia’s $589B DeepSeek rout
#74390% of the comments in this thread make it clear that knowing about technology does not in any way qualify someone to think correctly about markets and equity valuations.
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Re: Nvidia’s $589B DeepSeek rout
#744Earlier quoted context omitted.
Markets aren't rational. NVidia is currently a hype stock which means LOTS of speculation, probably with lots of leverage. So, the people who have made large gains and/or are leveraged are highly incentivized to panic sell on any PERCEIVED bad news. It doesn't even matter if the bad news will materially impact sales. What matters is how the other gamblers will react to the news and getting in front of them. :)
Another thing, the markets had priced in X demand scaling @ ~145 and suddenly it's X/30 demand scaling and therefore the price should drop.
That's wrong.
DeepSeek is a problem for Big Tech, not for Nvidia.
Why?
Imagine a small startup can do something better than Gemini or ChatGPT or Claude.
So it can be disruptive.
What can Big Tech do to avoid disruption? Buying every SINGLE GPU Nvidia produces! They have the money and they can use the GPUs in research.
The worst nightmare of any Tech CEO is a startup which disrupts you so you have to either be faster or you kill access to needed infrastructure for the startup. Or even better, the startup has to rent your cloud infrastructure, this way you earn money and you have an eye on what's going on.
Additionally, Hyperscalers only get 50-60% of Nvidia's supply. They all complain of being undersupplied yet they get only 60% and not 99% of Nvidia's supply. How come? Because Nvidia has a lot of other customers they like to supply to. That alone tells you how huge the demand is that Nvidia even has to delay Big Tech deliveries.
Also the demand for Nvidia didn't drop. DeepSeek isn't a frontier model. It's a distilled model therefore the moment OpenAI, Meta or the others release a new frontier model, DeepSeek will become obsolete and will have to start again to optimize.
Re: Nvidia’s $589B DeepSeek rout
#745Earlier quoted context omitted.
The increase in efficiency is usually accompanied with the process of commoditization as stuff get cheaper to develop, which is very bad news for nvidia. If you dont need the super high end chips than Nvidia loses it's biggest moat and ability to monopolize the tech, CUDA isn't enough.
> Nvidia loses it's biggest moat and ability to monopolize the tech, CUDA isn't enough CUDA is plenty for right now. AMD can't/won't get their act together with GPU software and drivers. Intel isn't in much better of a position than AMD and has a host of other problems. It's also unlikely the "let's just glue a thousand ARM cores together" hardware will work as planned and still needs the software layer. CUDA won't b…
Intel seems to be getting its act together. Battlemage is a decent mid-range GPU, and Gaudi 3 seems to be a fairly decent AI attempt.
Re: Nvidia’s $589B DeepSeek rout
#746Earlier quoted context omitted.
The full DeepSeek model is ~700B params or so - way too large for most end users to run locally. What some folks are running locally is fine-tuned versions of Llama and Qwen, that are not going to be directly comparable in any way.
Many people are missing this due to journalists completely missing the point when presenting these facts. Distilled models are nothing new.
Ollama calling the distilled models deepseek-r1:7b etc. doesn't help
Re: Nvidia’s $589B DeepSeek rout
#747Earlier quoted context omitted.
The other way is certainly also true. Your short piece is rational, but lacks insight into the inference and training dynamics of ML adoption unconstrained. The rate of ML progress is spectacularly compute constrained today. Every step in today’s scaling program is setup to de-risked the next scale up, because the opportunity cost of compute is so high. If the opportunity cost of compute is not so high, you can skip…
Everyone can say things that sound smart. When it comes to markets the only thing that matters is if your portfolio was green or red.
Since when gambling on a RNG output makes you smart?
Re: Nvidia’s $589B DeepSeek rout
#748Nvidia has gotten lucky repeatedly. The GPUs were great for PC gaming and they were the top dog. The crypto boom was such an unexpected win for them partly because Intel killed off their competition by acquiring it. Then the AI boom is also a direct result of Intel killing off their competition but the acquisition is too far removed to credit it to that event. Unlike the crypto boom though, two factors make me think…
> the models are going to get better/smaller/faster overtime reducing our reliance on the GPU Yes, because we've seen that with other software. I no longer want a GPU for my computer because I play games from the 90s and the CPU has grown powerful enough to suffice... except that's not the case at all. Software grew in complexity and quality with available compute resources and we have no reason to think "AI" will be…
interesting take.
the aaa games industry is struggling (e.g. look at the profit warnings, share price drops and studio closures) specifically because people are doing that en masse.
but those 90s games are not old - retro has become a movement within gaming and there is a whole cottage industry of "indie" games building that aesthetic because it is cheap and fun.
Re: Nvidia’s $589B DeepSeek rout
#749Earlier quoted context omitted.
You could even say that overconfidence in abilities and knowledge outside of core expertise is the critical flaw of today's entire tech industry.
As a great example of this read Paul Graham’s essays that aren’t anout his core expertise.
I think that’s unfair unless you give specific examples and clear evidence he’s wrong.
I disagree with PG on economics and politics, but much of his writing on that is subjective.
Re: Nvidia’s $589B DeepSeek rout
#75090% of the comments in this thread make it clear that knowing about technology does not in any way qualify someone to think correctly about markets and equity valuations.
I don’t understand why this is not obvious to many people: tech and stock trading are totally two different things, why on earth a tech expert is expected to know trading at all? Imagining how ridiculous it would be if a computer science graduate will also automatically get a financial degree from college even though no financial class has been taken.
I’ve noticed this phenomenon among IT & tech VC crowd. They will launch pod cast, offer expert opinion and what not on just about every topic under the Sun, from cold fusion to COVID vaccine to Ukraine war.
You wouldn’t see this in other folks, for example, a successful medical surgeon won’t offer much assertion about NVIDIA.
And the general tendency among audience is to assume that expertise can be carried across domains.