They baited me into putting in a query and then asking me to sign up to submit it. Even have a "Stay Logged Out" button that I thought would bypass it, but no.
I get running these models is not cheap, but they just lost a potential customer / user.
super impressive. we won't need that many GPUs in the future if we can have the performance of DeepSeek R1 with even less parameters. NVIDIA is in trouble. We are moving towards a world of very cheap compute: https://medium.com/thoughts-on-machine-learning/a-future-of-...
Have you heard of Jevons paradox? That says that whenever new tech is used to make something more efficient the tech is just upscaled to make the product quality higher. Same here. Deepseek has some algoritmic improvements that reduces resources for the same output quality. But increasig resources (which are available) will increase the quality. There will be always need for more compute. Nvidia is not in trouble. They have a monopoly on high performing ai chips for which demand will at least rise by a factor of 1000 upcoming years (my personal opinion)
I agree that the Jevons paradox can apply here, however, there have been several "breakthroughs" in the last couple of months (R1, diffusion LLMs, this) that really push the amount of GPU compute down such that I think it's going to be problematic for companies that went out and bought boatloads of GPUs (like OpenAI, for example). So while it might not be bad news for NVidia (given Jevons) it does seem to be bad news for OpenAI.
Even if you have cheaper models if you have tons of compute power you can do more things than if you had less compute power!
You can experiment with huge societies of agents, each exploring multitude of options. You can run world models where agents can run though experiments and you can feed all this back to a single "spokesperson" and you'll have an increase in intelligence or at the very least you'll able to distill the next generation models with that and rinse and repeat.
I mean I welcome the democratizing effect of this but I fail to understand how this is something that is so readily accepted as a doom scenario for people owning or building massive compute.
If anything, what we're witnessing is the recognition that useful stuff can be achieved by multiplying matrices!
> I guess the investors selling NVIDIA's stock like crazy know nothing about jevons
I know you are trying to be sarcastic, but for the sake of argument let's assume that your question is genuine.
There are two types of investors and they both sell, but for different reasons:
1. Casual investors: They don't know much about investing, or Jevons paradox. They only watch the news, so they panic sell.
2. Institutional investors: They know all about Jevons paradox etc, but they also know that casual investors don't, so they sell on purpose so that they can buy the dip later.
Surprisingly those open models might be savour for Apple and gift for Qualcomm too. They can finetune them to their liking and catch up to competition and also sell more of their devices in the future. Longterm even better models for Vision will have problem to compete with latency of smaller models that are good enough but have very low latency. This will be important in robotics - reason Figure AI dumped OpenAI and started using their own AI models based on Open Source (founder mentioned recently in one interview).
