I still don't get why this is bad for NVIDIA either. If anything, it brings more people into their ecosystem. NVIDIA is the AI hardware/platform company right now and people will deploy AI for more tasks if it becomes cheaper to do so.
But there's a more subtle point here which I don't see a lot of people talking about, maybe because they know more about this than me. Why wouldn't frontier model developers take DeepSeek R1 techniques and make their models even better or even larger? Or another way to ask: Are the DeepSeek R1 innovations only for making models cheaper (and slightly worse) or can the algorithms developed by the DeepSeek team be scaled up to make more powerful frontier models? Leading edge model developers don't just care about cost, they also want to release models with maximum capabilities. And as we've seen over the past few years, they're willing to pay almost anything to achieve this.
I think most AI researchers know there are still many things to explore in this space so disruptive innovations shouldn't be seen as a bubble burst but as more opportunity.
NVIDIA is in an extremely strong position right now. Even if someone has a major breakthrough on the hardware design side that dramatically lowers the cost of compute for AI workloads (which is highly unlikely), NVIDIA will just create their own implementation that will outperform the original since they have a stranglehold on an entire stack-up of technology: circuits, drivers, libraries and software.
You’re absolutely right. If there are corrections, it’s only because people have gone a little crazy. People sometimes get enamored with the idea of one country or company dominating in a winner-takes-all situation. OpenAI has been trying to spin narratives in which the only rational move is for everyone to invest all of their money in OpenAI, immediately.
I don’t think the Nvidia CEO is losing any sleep. He doesn’t have a planet-sized ego, like some. They are still selling pickaxes during a gold rush, as the saying goes. And the stock is still up 100% in the past year. CEOs don’t control the stock price (much as some try), anyway, the market does. Also, the market is insane. You also can’t control the competition, or what new innovations come along. You just have to run a good business, which they are doing.
Innovation is good for all players. Reality-checks are good. Nothing here is unexpected. There are lots of smart researchers in the world. Software innovations that make better use of hardware are expected. People just like drama.
Like if Tim does a better job at a skateboard trick that has always been Tom’s thing, people want to be that kid who is the one to say, “Oh, snap!!” and won’t stop talking about it at school, because they were there. And how it’s so mind-blowing and previously inconceivable.
But there's a more subtle point here which I don't see a lot of people talking about, maybe because they know more about this than me. Why wouldn't frontier model developers take DeepSeek R1 techniques and make their models even better or even larger? Or another way to ask: Are the DeepSeek R1 innovations only for making models cheaper (and slightly worse) or can the algorithms developed by the DeepSeek team be scaled up to make more powerful frontier models? Leading edge model developers don't just care about cost, they also want to release models with maximum capabilities. And as we've seen over the past few years, they're willing to pay almost anything to achieve this.
I think most AI researchers know there are still many things to explore in this space so disruptive innovations shouldn't be seen as a bubble burst but as more opportunity.
NVIDIA is in an extremely strong position right now. Even if someone has a major breakthrough on the hardware design side that dramatically lowers the cost of compute for AI workloads (which is highly unlikely), NVIDIA will just create their own implementation that will outperform the original since they have a stranglehold on an entire stack-up of technology: circuits, drivers, libraries and software.