Why do companies that own shopping centres lease their units out to individual shops, instead of running shops themselves? Why do airports and railway stations lease out space to coffee shops, newsagents, etc. rather than operating coffee shops and newsagents themselves? Are these things different to selling AI access instead of doing whatever it is the companies buying AI access are doing?
(Perhaps they are! Perhaps a dedicated clothes shop or coffee shop has some advantage that a shopping centre or railway station can’t duplicate, but the companies that are renting AI access to run their businesses have no advantage that frontier AI labs couldn’t duplicate?)
If frontier models are only 12 months ahead of open models, how would the frontier labs get around the “If we can do it now the whole world can do it in 12 months” problem? Could a frontier lab build up enough of a running start in 12 months that you could never be caught? They couldn’t do this with AI development despite that being their speciality.
Finally—how much would the supply-demand equation for frontier AIs have to change for the labs to expect they could increase their value more by spending whatever resources they have on business ventures other than “developing frontier AI”? Would the equation change enough if AI development runs into diminishing returns or physical limits and stalls out, or if open AIs catch-up enough to saturate the market?
I’m not claiming that everything is of this shape. There are gains to specialization. In the shopping centres case, your core competency is probably the construction of real estate, or your big moat is all in owning the valuable real estate, so you can charge very high rents where most of the profits come from.
You would, in fact, get a discount on using your own real estate for other purposes, but others have more and better purposes, and you don’t specialize in this. This is because most things in shopping centres are either relatively low margins, all things considered, or have fairly low total markets ($<50M/year or w/e). The ability to make coffees is fairly commoditized. You can either implicitly pay the rent and run the business where you expect lots of revenue, or you can charge it out to someone else to do that.
There is a widespread joke about companies saying they are going to “make a bunch of alpha and sell it to hedge funds”. This is incredibly hard to do and basically never makes sense. If you have alpha, you should just use it yourself because it is more valuable that way.
Suppose you found an arbitrage between bitcoin across two exchanges that can make you $1M/year because there is $100M of volume and the arbitrage is for 1%. If you tell me about this strategy, I will be willing to close this spread further, and market make such that the edge is maybe 0.5% now. As more people enter the space, there is still $100M of volume, but the arbitrage between the exchanges is going to reduce further and further towards $0.
I’m not saying that all businesses are of this form. There are, of course, things you need other than AIs to run a lot of businesses. I’m saying there are some with extreme profit margin potential, such that the incentive is to keep it internally as opposed to sell it and widely distribute it. Perhaps they will still sell models for use by the public, but it’ll be 2nd-best models or models without all the intelligence needed for LLM-based trading on earnings reports or presswires.
If frontier models are only 12 months ahead of open models, how would the frontier labs get around the “If we can do it now the whole world can do it in 12 months” problem? Could a frontier lab build up enough of a running start in 12 months that you could never be caught? They couldn’t do this with AI development despite that being their speciality.
I see what you are getting at. I think it is closer to 6 months. I think if you try to charge too much, you are simply going to run into the problem that you simply do not need that much intelligence for most use cases, and so you won’t be able to charge 10x as much for Opus 4.7>4.6 or w/e. You get to charge like 20% more, maybe.
Finally—how much would the supply-demand equation for frontier AIs have to change for the labs to expect they could increase their value more by spending whatever resources they have on business ventures other than “developing frontier AI”?
I think Phil Tramell should get involved here. But “developing frontier AI” is not a business that makes money. Selling the frontier AI through API is the business currently. I’m saying that there is a new line of business that makes a lot of sense. Keeping your AI internally and using it to make money in a few specific industries, particuarly where having the best model all to yourself really pays dividends.
Why do companies that own shopping centres lease their units out to individual shops, instead of running shops themselves? Why do airports and railway stations lease out space to coffee shops, newsagents, etc. rather than operating coffee shops and newsagents themselves? Are these things different to selling AI access instead of doing whatever it is the companies buying AI access are doing?
(Perhaps they are! Perhaps a dedicated clothes shop or coffee shop has some advantage that a shopping centre or railway station can’t duplicate, but the companies that are renting AI access to run their businesses have no advantage that frontier AI labs couldn’t duplicate?)
If frontier models are only 12 months ahead of open models, how would the frontier labs get around the “If we can do it now the whole world can do it in 12 months” problem? Could a frontier lab build up enough of a running start in 12 months that you could never be caught? They couldn’t do this with AI development despite that being their speciality.
Finally—how much would the supply-demand equation for frontier AIs have to change for the labs to expect they could increase their value more by spending whatever resources they have on business ventures other than “developing frontier AI”? Would the equation change enough if AI development runs into diminishing returns or physical limits and stalls out, or if open AIs catch-up enough to saturate the market?
I’m not claiming that everything is of this shape. There are gains to specialization. In the shopping centres case, your core competency is probably the construction of real estate, or your big moat is all in owning the valuable real estate, so you can charge very high rents where most of the profits come from.
You would, in fact, get a discount on using your own real estate for other purposes, but others have more and better purposes, and you don’t specialize in this. This is because most things in shopping centres are either relatively low margins, all things considered, or have fairly low total markets ($<50M/year or w/e). The ability to make coffees is fairly commoditized. You can either implicitly pay the rent and run the business where you expect lots of revenue, or you can charge it out to someone else to do that.
There is a widespread joke about companies saying they are going to “make a bunch of alpha and sell it to hedge funds”. This is incredibly hard to do and basically never makes sense. If you have alpha, you should just use it yourself because it is more valuable that way.
Suppose you found an arbitrage between bitcoin across two exchanges that can make you $1M/year because there is $100M of volume and the arbitrage is for 1%. If you tell me about this strategy, I will be willing to close this spread further, and market make such that the edge is maybe 0.5% now. As more people enter the space, there is still $100M of volume, but the arbitrage between the exchanges is going to reduce further and further towards $0.
I’m not saying that all businesses are of this form. There are, of course, things you need other than AIs to run a lot of businesses. I’m saying there are some with extreme profit margin potential, such that the incentive is to keep it internally as opposed to sell it and widely distribute it. Perhaps they will still sell models for use by the public, but it’ll be 2nd-best models or models without all the intelligence needed for LLM-based trading on earnings reports or presswires.
I see what you are getting at. I think it is closer to 6 months. I think if you try to charge too much, you are simply going to run into the problem that you simply do not need that much intelligence for most use cases, and so you won’t be able to charge 10x as much for Opus 4.7>4.6 or w/e. You get to charge like 20% more, maybe.
I think Phil Tramell should get involved here. But “developing frontier AI” is not a business that makes money. Selling the frontier AI through API is the business currently. I’m saying that there is a new line of business that makes a lot of sense. Keeping your AI internally and using it to make money in a few specific industries, particuarly where having the best model all to yourself really pays dividends.