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This reminds me of the railroads, where once railroads were invented, there was a huge investment boom of eveyrone trying to make money of the railroads, but th

This reminds me of the railroads, where once railroads were invented, there was a huge investment boom of eveyrone trying to make money of the railroads, but the competition brought the costs down where the railroads weren’t the people who generally made the money and got the benefit, but the consumers and regular businesses did and competition caused many to fail. AI is probably similar where the Moore’s law and advancement will eventually allow people to run open models locally and bring down the cost of operation. Competiition will make it hard for all but one or two players to survive and Nvidia, OpenAI, Deepseek, etc most investments in AI by these large companies will fail to generate substantial wealth but maybe earn some sort of return or maybe not.

mjburgess 2y ago
For the curious, it was vertical integration in the railroad-oil/-coal industry which is where the money was made. The problem for AI is the hardware is commodified and offers no natural monopoly, so there isn't really anything obvious to vertically integrate-towards-monopoly.
- fullshark 2y ago
  Aren’t we approaching a scenario where the software is commodified (or at least “good enough” software) and the hardware isn’t (NVIDIA GPUs have defined advantages)
  - mjburgess 2y ago
    I think the lesson of DeepSeek is 'no' -- that by software innovation (ie., dropping below CUDA to programming the GPU directly, working at 8bit, etc.) you can trivialise the hardware requirement. However I think the reality is that there's only so much coal to be mined, as far as LLM training goes. When we're at "very dimishing returns" SoC/Apple/TSMC-CPU innovations will deliver cheap inference. We only really need a M4 Ultra with 1TB RAM to hollow-out the hardware-inference-supplier market. Very easy to imagine a future where Apple releases a "Apple Intelligence Mac Studio" with the specs for many businesses to run arbitrary models.
    - daft_pink 2y ago
      I really hope that apple realizes soon there is a market for Mac Pro/Mac Studio with a RAM in the TBs for AI Workloads under $10k and a bunch of GPU cores.
      - jppope 2y ago
        there was a company that recently built a desktop GPU for that exact thing. I'll see if I can find it
        exe34 2y ago
        https://cerebras.ai/ https://cerebras.ai/ ?
  - duped 2y ago
    Compute is literally being sold as a commodity today, software is not.
    - phkahler 2y ago
      >> Compute is literally being sold as a commodity today, software is not. The marginal cost of software is zero. You need some kind of perceived advantage to get people to pay for it. This isn't hard, as most people will pay a bit for big-name vs "free". That could change as more open source apps become popular by being awesome.
      - duped 2y ago
        Marginal cost has nothing to do with it - you can buy and sell compute like you could corn and beef at scale. You can't buy and sell software like that. In fact I'm surprised we don't have futures markets for things like compute and object storage.
floatrock 2y ago
The railroads drama ended when JP Morgan (the person, not yet the entity) brought all the railroad bosses together, said "you all answer to me because I represent your investors / shareholders", and forced a wave of consolidation and syndicates because competition was bad for business. Then all the farmers in the midwest went broke not because they couldn't get their goods to market, but because JP Morgan's consolidated syndicates ate all their margin hauling their goods to market. Consolidation and monopoly over your competition is always the end goal.
- DrScientist 2y ago
  > Consolidation and monopoly over your competition is always the end goal. Surely that's only possible when you have a large barrier to entry? What's going to be that barrier in this case - cos it turns out not to be neither training costs/hardware or secret expertise.
  - yoyohello13 2y ago
    The large syndicate will create the barriers. Either via laws, or if that fails violence.
  - tdb7893 2y ago
    So I'm not an expert in this but even with DeepSeek supposedly reducing training costs isn't the estimate still in the millions (and that's presumably not counting a lot of costs)? And that wouldn't be counting a bunch of other barriers for actually building the business since training a model is only one part, the barrier to entry still seems very high. Also barriers to entry aren't the only way to get a consolidated market anyway.
    - layer8 2y ago
      About your first point, IMO the usefulness of AI will remain relatively limited as long as we don’t have continuously learning AI. And once we have that, the disparity between training and inference may effectively disappear. Whether that means that such AI will become more accessible/affordable or less is a different question.
UncleOxidant 2y ago
> where the Moore’s law and advancement will eventually allow people to run open models locally Probably won't be Moore's law (which is kind of slowing down) so much as architectural improvements (both on the compute side and the model side - you could say that R1 represents an architectural improvement of efficiency on the model side).
rgbrgb 2y ago
I think that's a very possible outcome. A lot of people investing in AI are thinking there's a google moment coming where one monopoly will reign supreme. Google has strong network effects around user data AND economies of scale. Right now, AI is 1-player with much weaker network effects. The user data moat goes away once the model trains itself effectively and the economies of scale advantage goes away with smart small models that can be efficiently hosted by mortals/hobbyists. The DeepSeek result points to both of those happening in the near future. Interesting times.
lastofthemojito 2y ago
I saw a thought-provoking post that similarly compared LLM makers to the airlines: https://calpaterson.com/porter.html https://calpaterson.com/porter.html
taco_emoji 2y ago
Main difference is that railroads are actually useful
yonran 2y ago
I think a better analogy than railroads (which own the land that the track sits on and often valuable land around the station) is airlines, which don’t own land. I recall a relevant Warren Buffett letter that warned about investing hundreds of millions of dollars into capital with no moat: > Similarly, business growth, per se, tells us little about value. It's true that growth often has a positive impact on value, sometimes one of spectacular proportions. But such an effect is far from certain. For example, investors have regularly poured money into the domestic airline business to finance profitless (or worse) growth. For these investors, it would have been far better if Orville had failed to get off the ground at Kitty Hawk: The more the industry has grown, the worse the disaster for owners. https://www.berkshirehathaway.com/letters/1992.html https://www.berkshirehathaway.com/letters/1992.html

mjburgess 2y ago

For the curious, it was vertical integration in the railroad-oil/-coal industry which is where the money was made. The problem for AI is the hardware is commodified and offers no natural monopoly, so there isn't really anything obvious to vertically integrate-towards-monopoly.

fullshark 2y ago
Aren’t we approaching a scenario where the software is commodified (or at least “good enough” software) and the hardware isn’t (NVIDIA GPUs have defined advantages)
- mjburgess 2y ago
  I think the lesson of DeepSeek is 'no' -- that by software innovation (ie., dropping below CUDA to programming the GPU directly, working at 8bit, etc.) you can trivialise the hardware requirement. However I think the reality is that there's only so much coal to be mined, as far as LLM training goes. When we're at "very dimishing returns" SoC/Apple/TSMC-CPU innovations will deliver cheap inference. We only really need a M4 Ultra with 1TB RAM to hollow-out the hardware-inference-supplier market. Very easy to imagine a future where Apple releases a "Apple Intelligence Mac Studio" with the specs for many businesses to run arbitrary models.
  - daft_pink 2y ago
    I really hope that apple realizes soon there is a market for Mac Pro/Mac Studio with a RAM in the TBs for AI Workloads under $10k and a bunch of GPU cores.
    - jppope 2y ago
      there was a company that recently built a desktop GPU for that exact thing. I'll see if I can find it
      - exe34 2y ago
        https://cerebras.ai/ https://cerebras.ai/ ?
- duped 2y ago
  Compute is literally being sold as a commodity today, software is not.
  - phkahler 2y ago
    >> Compute is literally being sold as a commodity today, software is not. The marginal cost of software is zero. You need some kind of perceived advantage to get people to pay for it. This isn't hard, as most people will pay a bit for big-name vs "free". That could change as more open source apps become popular by being awesome.
    - duped 2y ago
      Marginal cost has nothing to do with it - you can buy and sell compute like you could corn and beef at scale. You can't buy and sell software like that. In fact I'm surprised we don't have futures markets for things like compute and object storage.

floatrock 2y ago

The railroads drama ended when JP Morgan (the person, not yet the entity) brought all the railroad bosses together, said "you all answer to me because I represent your investors / shareholders", and forced a wave of consolidation and syndicates because competition was bad for business. Then all the farmers in the midwest went broke not because they couldn't get their goods to market, but because JP Morgan's consolidated syndicates ate all their margin hauling their goods to market. Consolidation and monopoly over your competition is always the end goal.

DrScientist 2y ago
> Consolidation and monopoly over your competition is always the end goal. Surely that's only possible when you have a large barrier to entry? What's going to be that barrier in this case - cos it turns out not to be neither training costs/hardware or secret expertise.
- yoyohello13 2y ago
  The large syndicate will create the barriers. Either via laws, or if that fails violence.
- tdb7893 2y ago
  So I'm not an expert in this but even with DeepSeek supposedly reducing training costs isn't the estimate still in the millions (and that's presumably not counting a lot of costs)? And that wouldn't be counting a bunch of other barriers for actually building the business since training a model is only one part, the barrier to entry still seems very high. Also barriers to entry aren't the only way to get a consolidated market anyway.
  - layer8 2y ago
    About your first point, IMO the usefulness of AI will remain relatively limited as long as we don’t have continuously learning AI. And once we have that, the disparity between training and inference may effectively disappear. Whether that means that such AI will become more accessible/affordable or less is a different question.

UncleOxidant 2y ago

> where the Moore’s law and advancement will eventually allow people to run open models locally Probably won't be Moore's law (which is kind of slowing down) so much as architectural improvements (both on the compute side and the model side - you could say that R1 represents an architectural improvement of efficiency on the model side).

rgbrgb 2y ago

I think that's a very possible outcome. A lot of people investing in AI are thinking there's a google moment coming where one monopoly will reign supreme. Google has strong network effects around user data AND economies of scale. Right now, AI is 1-player with much weaker network effects. The user data moat goes away once the model trains itself effectively and the economies of scale advantage goes away with smart small models that can be efficiently hosted by mortals/hobbyists. The DeepSeek result points to both of those happening in the near future. Interesting times.

lastofthemojito 2y ago

I saw a thought-provoking post that similarly compared LLM makers to the airlines: https://calpaterson.com/porter.html https://calpaterson.com/porter.html

taco_emoji 2y ago

Main difference is that railroads are actually useful

yonran 2y ago

I think a better analogy than railroads (which own the land that the track sits on and often valuable land around the station) is airlines, which don’t own land. I recall a relevant Warren Buffett letter that warned about investing hundreds of millions of dollars into capital with no moat: > Similarly, business growth, per se, tells us little about value. It's true that growth often has a positive impact on value, sometimes one of spectacular proportions. But such an effect is far from certain. For example, investors have regularly poured money into the domestic airline business to finance profitless (or worse) growth. For these investors, it would have been far better if Orville had failed to get off the ground at Kitty Hawk: The more the industry has grown, the worse the disaster for owners. https://www.berkshirehathaway.com/letters/1992.html https://www.berkshirehathaway.com/letters/1992.html