It’s not the same thing because the whole valuation of the LLM-based AI sector is on the basis of what it can possibly be capable of at some point in the future even though it is unreliable today. The hope is that this AI continues to improve at a constant rate and can reduce every corporation’s biggest expense (labour cost) reliably soon. Deepseek’s success does not do anything to bring sobriety to this view. It just shows tbat you can bring about comparable performance at a fraction of the resource usage.
No, that’s not how investment works. Investors expect returns when they make an investment. Investors invested in Nvidia expecting Nvidia to be the vehicle by which they make their returns. If someone else reduces labor cost for the market, Nvidia doesn’t capture any of that value, and therefore cannot be the vehicle for investors to make a profit.
So while AI itself my still reduce labor costs and open up huge margin for already existing companies, the individual companies producing AI will not have the same investment value if there is strong competition.
This is the real answer. AI may still be a game-changer, but if any mom & pop shop can do it now, all the expected future profit currently built into the stock price of Nvidia, et al. is suddenly very questionable.
It’s the same thing. The value of any given stock has to do with the perceived future value of the stock. The perceived future value of the stock has to do with the ability of a company to profitably grow. No one invests in startups expecting dividends, but if the startup cannot demonstrate monopoly potential, it’s very difficult to get investment.
There’s plenty of theorists who argue otherwise. Profit distribution represents value that have nowhere else to grow, whereas as stock value growth represents money deployed to growth that otherwise could have been distributed. In the end, it’s value capture.
There’s plenty of theorists who argue otherwise. Profit distribution represents value that have nowhere else to grow, whereas as stock value growth represents money deployed to growth that otherwise could have been distributed. In the end, it’s value capture.
I don’t think we are disagreeing. All I wanted to say was that this Deepseek phenomenon is not going to burst the LLM bubble. It is just going to challenge the monopoly of western AI firms.
I guess it depends on what Deepseek does next. Western tech has this really bad habit of wasting away any hardware advances with unoptimised software. It works out in the favour of both software and hardware companies, because this kind of software is easier to produce and hardware companies get to sell expensive hardware. During this whole LLM craze AI companies have been using more and more compute and data in zombie mode and there has been zero effort in reducing it for some reason. I don’t know why that is because even a small saving percent wise translates to a large absolute number but they don’t seem to care. It is like they want to be shit. Maybe they will realise that planning for startup-run nuclear fusion reactors powering AGI datacentres is not something they should be planning for? I doubt it though.
Generally this is because of the logic of capitalism. Optimizing is far less important than Adam Smith believed it would be. More important is market capture. If I get to 2% market share with 50% margins and you get 30% market share with 10% margins, you are considered the winner. Bigger absolute numbers win with investors. This is partly because of the theory that if an investor is going to spend money they want it spent on the thing that will produce the most money, and optimizing small things is worse than growing big things. The theory continues that optimization is the job of specialists who take the big thing and optimize it incrementally after it’s established market dominance, but establishing market dominance is the first job. The theory finishes with the idea that by the time optimization becomes a viable option for making ROI, there’s probably another new growth project that presents greater upside potential. So, we end up with a ton of companies that focus entirely on growth until they can’t anymore and then they get abandoned for the next big thing, picked up by vultures, torn apart and reorganized into oblivion, and everyone makes money except the workers.
It’s not the same thing because the whole valuation of the LLM-based AI sector is on the basis of what it can possibly be capable of at some point in the future even though it is unreliable today. The hope is that this AI continues to improve at a constant rate and can reduce every corporation’s biggest expense (labour cost) reliably soon. Deepseek’s success does not do anything to bring sobriety to this view. It just shows tbat you can bring about comparable performance at a fraction of the resource usage.
No, that’s not how investment works. Investors expect returns when they make an investment. Investors invested in Nvidia expecting Nvidia to be the vehicle by which they make their returns. If someone else reduces labor cost for the market, Nvidia doesn’t capture any of that value, and therefore cannot be the vehicle for investors to make a profit.
So while AI itself my still reduce labor costs and open up huge margin for already existing companies, the individual companies producing AI will not have the same investment value if there is strong competition.
This is the real answer. AI may still be a game-changer, but if any mom & pop shop can do it now, all the expected future profit currently built into the stock price of Nvidia, et al. is suddenly very questionable.
TBH, most of investors are buying stocks not because they expect dividends, but because they plan to sell them later for more.
It’s the same thing. The value of any given stock has to do with the perceived future value of the stock. The perceived future value of the stock has to do with the ability of a company to profitably grow. No one invests in startups expecting dividends, but if the startup cannot demonstrate monopoly potential, it’s very difficult to get investment.
No, there is a difference between buying stock for dividends and buying stock exclusively to sell it to a bigger rube Bitcoin-style.
There’s plenty of theorists who argue otherwise. Profit distribution represents value that have nowhere else to grow, whereas as stock value growth represents money deployed to growth that otherwise could have been distributed. In the end, it’s value capture.
There’s plenty of theorists who argue otherwise. Profit distribution represents value that have nowhere else to grow, whereas as stock value growth represents money deployed to growth that otherwise could have been distributed. In the end, it’s value capture.
I don’t think we are disagreeing. All I wanted to say was that this Deepseek phenomenon is not going to burst the LLM bubble. It is just going to challenge the monopoly of western AI firms.
Don’t confuse “bubbles” with “hype”. It will not burst the LLM hype but it could burst the speculation bubble of investments in AI companies.
I guess it depends on what Deepseek does next. Western tech has this really bad habit of wasting away any hardware advances with unoptimised software. It works out in the favour of both software and hardware companies, because this kind of software is easier to produce and hardware companies get to sell expensive hardware. During this whole LLM craze AI companies have been using more and more compute and data in zombie mode and there has been zero effort in reducing it for some reason. I don’t know why that is because even a small saving percent wise translates to a large absolute number but they don’t seem to care. It is like they want to be shit. Maybe they will realise that planning for startup-run nuclear fusion reactors powering AGI datacentres is not something they should be planning for? I doubt it though.
Generally this is because of the logic of capitalism. Optimizing is far less important than Adam Smith believed it would be. More important is market capture. If I get to 2% market share with 50% margins and you get 30% market share with 10% margins, you are considered the winner. Bigger absolute numbers win with investors. This is partly because of the theory that if an investor is going to spend money they want it spent on the thing that will produce the most money, and optimizing small things is worse than growing big things. The theory continues that optimization is the job of specialists who take the big thing and optimize it incrementally after it’s established market dominance, but establishing market dominance is the first job. The theory finishes with the idea that by the time optimization becomes a viable option for making ROI, there’s probably another new growth project that presents greater upside potential. So, we end up with a ton of companies that focus entirely on growth until they can’t anymore and then they get abandoned for the next big thing, picked up by vultures, torn apart and reorganized into oblivion, and everyone makes money except the workers.