I really don't understand the market thinks Nvidia is losing its value.
If DeepSeek reduce the required computational resources, we can pour more computational resources to improve it further. There's nothing bad about more resources.
If DeepSeek reduce the required computational resources, we can pour more computational resources to improve it further. There's nothing bad about more resources.
Training is a huge component of Nvidia's projected growth. Inference is actually much more competitive, but training is almost exclusively Nvidia's domain. If Deepseek's claims are true, that would represent a 10x reduction in cost for training for similar models (6 million for r1 vs 60 million for something like o1).
It is absolutely not the case in ML that "there is nothing bad about more resources". There is something very bad - cost. And another bad thing - depreciation. And finally, another bad thing - the fact that new chips and approaches are coming out all the time, so if you are on older hardware you might be missing out. Training complex models for cheaper will allow companies to potentially re-allocate away from hardware into software (ie, hiring more engineering to build more models, instead of less engineers and more hardware to build less models).
Finally, there is a giant elephant in the room that it is very unclear if throwing more resources at LLM training will net better results. There are diminishing returns in terms of return on investment in training, especially with LLM-style use cases. It is actually very non-obvious right now how pouring more compute specifically at training will result in better LLMs.
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.
:)
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.
So, so many misinformed takes in this thread (not just you...)
nVidia is going to be a very volatile stock for years to come.
I don't see deepseek changing nvidia's short term growth potential though. Efficiencies in training were always inevitable, but more GPU still equals smarter AI....probably.
because the less GPU need to train, the less money to be made
- "If DeepSeek reduce the required computational resources, we can pour more computational resources to improve it further. There's nothing bad about more resources."
thats why you are not hedgefund manager, these guys job is to ensure that the HYPETRAIN for company to buy as many nvidia gpu to sell no matter what, if we can produce comparable model without using B (as it stands billions of dollar), it means there are less billions of dollar to be made and the HYPETRAIN is near the end