‘Building LLMs Is Probably Not Going Be a Brilliant Business’
Cal Paterson:
Large language models (LLMs) like Chat-GPT and Claude.ai are
whizzy and cool. A lot of people think that they are going to be
The Future. Maybe they are — but that doesn’t mean that building
them is going to be a profitable business.
In the 1960s, airlines were The Future. That is why old films have
so many swish shots of airports in them. Airlines though, turned
out to be an unavoidably rubbish business. I’ve flown on loads of
airlines that have gone bust: Monarch, WOW Air, Thomas Cook,
Flybmi, Zoom. And those are all busts from before coronavirus –
times change but being an airline is always a bad idea.
That’s odd, because other businesses, even ones which seem really
stupid, are much more profitable. Selling fizzy drinks is,
surprisingly, an amazing business. Perhaps the best. Coca-Cola’s
return on equity has rarely fallen below 30% in any given year.
That seems very unfair because being an airline is hard work but
making Coke is pretty easy. It’s even more galling because
Coca-Cola don’t actually make the Coke themselves – that is
outsourced to “bottling companies”. They literally just sell it.
This is such a crackerjack essay. Clear, concise, and uncomplicated. I find it hard to argue with. I’ve repeatedly mentioned an internal paper that leaked out of Google last year, titled “We Have No Moat, and Neither Does OpenAI”. The fact that OpenAI has lobbied for stringent AI regulation around the globe suggests that they fear this too — their encouragement of regulation could be explained by seeking a regulatory moat because there is no technical or business model moat to be had.
Paterson, expounding on his comparison to the airline industry, observes that commercials airlines have only two suppliers: Boeing and Airbus. He continues:
LLM makers sometimes imply that their suppliers are cloud
companies like Amazon Web Services, Google Cloud, etc. That
wouldn’t be so bad because you could shop around and make them
compete to cut the huge cost of model training.
Really though, LLM makers have only one true supplier:
NVIDIA. NVIDIA make thechips that all models are
trained on — regardless of cloud vendor. And that gives
NVIDIA colossal, near total pricing power. NVIDIA are more
powerful relative to Anthropic or OpenAI than Airbus or
Boeing could ever dream of being.
At this moment, there are three companies in the world with market caps in excess of $3 trillion: Apple, Nvidia, and Microsoft. There are only two more with market caps in excess of $2 trillion: Amazon and Google. Engineering, training, and providing LLMs isn’t the business with a moat. The business with a moat is making the cutting-edge computer hardware that trains LLMs, and that belongs to Nvidia.
I have more to say about Paterson’s essay, but I really just want you to read it for now.
★
Cal Paterson:
Large language models (LLMs) like Chat-GPT and Claude.ai are
whizzy and cool. A lot of people think that they are going to be
The Future. Maybe they are — but that doesn’t mean that building
them is going to be a profitable business.
In the 1960s, airlines were The Future. That is why old films have
so many swish shots of airports in them. Airlines though, turned
out to be an unavoidably rubbish business. I’ve flown on loads of
airlines that have gone bust: Monarch, WOW Air, Thomas Cook,
Flybmi, Zoom. And those are all busts from before coronavirus –
times change but being an airline is always a bad idea.
That’s odd, because other businesses, even ones which seem really
stupid, are much more profitable. Selling fizzy drinks is,
surprisingly, an amazing business. Perhaps the best. Coca-Cola’s
return on equity has rarely fallen below 30% in any given year.
That seems very unfair because being an airline is hard work but
making Coke is pretty easy. It’s even more galling because
Coca-Cola don’t actually make the Coke themselves – that is
outsourced to “bottling companies”. They literally just sell it.
This is such a crackerjack essay. Clear, concise, and uncomplicated. I find it hard to argue with. I’ve repeatedly mentioned an internal paper that leaked out of Google last year, titled “We Have No Moat, and Neither Does OpenAI”. The fact that OpenAI has lobbied for stringent AI regulation around the globe suggests that they fear this too — their encouragement of regulation could be explained by seeking a regulatory moat because there is no technical or business model moat to be had.
Paterson, expounding on his comparison to the airline industry, observes that commercials airlines have only two suppliers: Boeing and Airbus. He continues:
LLM makers sometimes imply that their suppliers are cloud
companies like Amazon Web Services, Google Cloud, etc. That
wouldn’t be so bad because you could shop around and make them
compete to cut the huge cost of model training.
Really though, LLM makers have only one true supplier:
NVIDIA. NVIDIA make thechips that all models are
trained on — regardless of cloud vendor. And that gives
NVIDIA colossal, near total pricing power. NVIDIA are more
powerful relative to Anthropic or OpenAI than Airbus or
Boeing could ever dream of being.
At this moment, there are three companies in the world with market caps in excess of $3 trillion: Apple, Nvidia, and Microsoft. There are only two more with market caps in excess of $2 trillion: Amazon and Google. Engineering, training, and providing LLMs isn’t the business with a moat. The business with a moat is making the cutting-edge computer hardware that trains LLMs, and that belongs to Nvidia.
I have more to say about Paterson’s essay, but I really just want you to read it for now.