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Doesn't really seem like a Paradox. There may only be 10 people willing to pay $100 for something, but 1000 willing to pay $10 for it, so lower price results in more revenue.
Another counter argument is that’s Nvidia will sell less high margin advanced GPUs that require expensive networking equipment.
Problem with that argument is that every competitor gets the benefit of higher efficiency and the baseline will reset back to 0.
This is IMO a spefic case of the induced demand concept ( https://en.wikipedia.org/wiki/Induced_demand ).
The concept of "Induced Demand" is easily explained by the default state of the downward sloping demand curve, and upward sloping supply curve.
In basic economic theory, if you reduce the cost of a good, more people will consume it.
e.g. the classic building a highway example; there was always demand for cheap housing with accessibility to downtowns, but the supply of cheap housing with accessibility to downtowns did not exist prior to building the highway there. The "demand curve" doesn't shift at all, you're just moving along it as perception of cost changes.
Has there ever been a case where a highway was run through the middle of nowhere and traffic didn't increase? It's intuitive why
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Is that really the analogy you want to use? « In 1873, greed, speculation and overinvestment in railroads sparked a financial crisis that sank the U.S. into more than five years of misery » https://www.smithsonianmag.com/history/robber-baron-gamble-r...
And yet, in history, railroad is one of the few examples of bubbles that didn't ultimately popped. You can still lose money in the greed-fear cycle even if the road leads up to unimaginable heights.
With AGI/ASI, there will come a point where this paradox breaks down: once the ASI is self-sufficient and "agentic enough", people's direct use for it will actually reduce. You won't need to "micromanage" it - and the total amount of compute it requires might actually drop drastically if the ASI improves its own efficiency much better than humans can. At that point the question becomes one of alignment: will overall…
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Sure, 31 December 2024 is by definition last year, but at the same time that was not even a month ago.
Come on. Which do you think is more likely, that it was a normal EOY sale of a lucrative stock, or that they sold based on insider info obtained weeks before anyone else?
deepseek v2 showed effeciency months ago, and nothing happened, there's also nothing happened after v3 and r1 release
the insider info is about when will Wall Street stop pushing and squeezing the market and start harvesting, and, IMO, this will happen anytime after rotation of ruling parties
i don't know if the similar scene happened before in the US, but this happened elsewhere, the rulling party with connected market makers and puppet central bank, push the market to highest and let it freely fall after rotation
nancy definetly know what the timing is
Just some nonsense, but if I’m right, it won’t take too long to witness it happen.
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majority of Nvidia's profits are from huge companies particularly Microsoft and META not individuals buying graphics cards. Look at their current video gaming graphics sales and even if these ai consumer purchases were 10x what there previous graphics sales were then the current valuation wouldn't make sense. This is all ignoring the fact that if the h800 was good enough amd's top line cards should be too.
>This is all ignoring the fact that if the h800 was good enough amd's top line cards should be too. You can't pay me to use AMD cards. I have work to do. I don't have time to write drivers for cards that no one supports. The point of the deepseek r1 paper is that the more synthetic data you generate by over trained models the better the resulting model. That means more GPUs. There is no reason why you can't train a d…
So yes, an increase need for ever better thinking models.
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Having read the paper from deepseek I seriously don't get how anyone can think "Oh now is the time to sell nvidia". Both at the tactical level and strategic level that paper means we will see _more_ nvidia gpus fly off the shelves. If anything it's showing why the h800 is a decent card and everyone in China should buy one (dozen thousands).
But, I thought the CUDA moat is primarily needed for training. On the inference side, why does one need Nvidia GPUs over Intel and AMD GPUs?
Not to mention there’s little real world evidence that AMD is better at inference speed not cost/inference over Nvidia.
This "paradox" is being cited everywhere, and while it might apply to AI, people are wrongly using it to justify why nvidia should have a $3.6T or greater valuation. What happens to a holistic system doesn't necessarily apply to every player in that system. nvidia's heights are largely because of a few super capitalized players dumping enormous amounts of money into data centre GPUs, letting nvidia enjoy outrageous p…
This "paradox" is being cited everywhere, and while it might apply to AI, people are wrongly using it to justify why nvidia should have a $3.6T or greater valuation.
Nvidia being worth $3.6T is a different topic. People think DeepSeek should have reinforced that valuation or even increased it, not lower it.
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Do you have a use case for your opinion? On the assumption that we’d want super intelligence to do interesting things, consider that we currently have many very smart humans and society is not maximizing their use, quite the opposite.
Do you have a use case for your opinion? Use the ultra smart AI to convince you that I’m right. :)