To put that in context, Alphabet (Google’s parent) is the biggest software company in the world. It’s the 3rd biggest company in the world after nVidia and Apple, but they’re mostly hardware companies.
Google’s annual revenues are creeping up towards $500b/year. So, the AI companies (Google included I suppose) would need 12x Google’s annual revenue just to break even.
There are 2 companies that have over $1b in annual revenue, Amazon and Wal*Mart. But, those are companies that sell goods to consumers, they’re not just digital services businesses. But, even then, you’d need 3x the revenue of Amazon and Wal*Mart combined to hit $6t.
Google, Apple, nVidia, Wal*Mart and Amazon each took decades to grow enough to capture hundreds of millions of dollars in revenue. So, somehow OpenAI and Anthropic are going to need to grow faster than any other company on earth to hit these trillion dollar targets.
Also putting this number into scale, there are about 8.3 billion people on the Earth. But, most of them are poor goat herders, subsistence farmers, sweatshop employees, and AI model trainers / reviewers living in Asia and Africa. These aren’t the kinds of people who are going to be buying a subscription to ChatGPT. There are maybe 1 billion people globally who have disposable cash they can spend on AI. So, to hit 6 trillion annually, each person living in a developed country would need to personally hit $6000 in AI spending on a yearly basis. Note, that includes children and the elderly. If you limit it to working-age people, that’s more like $10k per person per year.
Now, it doesn’t have to be that this is down to consumers. Maybe this is so valuable that Wal*Mart, the US government, and every other large employer pays for a ChatGPT subscription for each of their millions of employees. But, really, despite the fact that there have been very few actual successful AI deployments that saved companies money, or generated more profits, they’re suddenly going to be spending a significant fraction of each worker’s wage on AI subscriptions?
I think it’s pretty obvious that the AI companies thought that they were about to invent AI jesus. They thought they were just a few datacentres away from the machine god coming to life. They thought that AGI would change the world to such a degree that it might make the entire economy obsolete, so there was no limit on how much they should spend so either they would get there first (and maybe be seen as the god’s parents?) or out of some kind of altruism-type-feeling so that they could make a machine god which would align with their beliefs. But, that didn’t happen.
I saw a comment the other day about AI firms and CapEx vs OpEx. CapEx is Capital Expenditures – basically one-time costs for setting up a business. OpEx is Operational Expenses, basically ongoing costs for running a business. A good way to generate money from a business is to have a high CapEx and low OpEx. It’s hard for someone to set up a competing business because of the high initial costs, but once it’s up and running you can provide services for a low ongoing cost, and you can make a high profit on each customer. If CapEx is low but OpEx is high, sometimes it can work as a luxury business. Think an artist who hand-carves furniture. If both CapEx and OpEx are low, it’s basically a commodity business, think something like a nail salon. Cheap to set up, cheap to run, hard to fight off competitors.
The AI companies are stuck in a world where they have incredibly high CapEx (building DCs and training new models), and incredibly high OpEx (inference queries – basically talking to the chatbot, is also very expensive). Right now to try to hook customers they’re subsidizing the OpEx side of things, so each new customer costs them more money. Their paid tiers are even worse because people actually start really using the chatbots once they pay for them, and the money lost per customer goes way up for the paid tiers.
The only thing that would work is if the companies can somehow manage to get customers to pay incredibly high costs per token, so that not only are the OpEx costs covered, but the companies can start to pay down the initial CapEx. But, there’s just no justification for that yet. And the ruthless competition between all the AI companies means that if one of them starts trying to jack up costs to cover their OpEx, the others will keep theirs low to grab market share.
This is why the AI companies are doing all the things they’re doing. They’re talking about their models “escaping containment” and “hacking” other companies. Why? Because that makes it sound like these things are so powerful that they can’t be contained, rather than it being that the AI companies are incompetent and building a locked-down test environment, and how they are just running dumb scripts that they’re not even looking at before the execute. They’re boosting stories about the AIs being so powerful that they’ll destroy the world so that CEOs think they need to buy subscriptions to this powerful machine god for their companies. They’re inviting regulations and laws so that no new AI companies can enter the business, and so that they’re all forbidden from building new models, which is a massive CapEx (sorta) cost.
They can’t admit that the attempt to build a machine god has failed, because that will cause the bubble to pop. What they want to do is survive long enough to go public so that the costs they’ve spent can be foisted on the dumb retail investors – and at this point on pension funds and anybody holding index funds, because these companies are so huge that index fund managers would be obligated to buy them. So, they need to keep scaring people about how incredibly powerful and unstoppable their word-guessing-machines are until their investors have safely grabbed their profits and everything can be allowed to explode.
Another comparison, they’ll need to make token cost 100x to get those numbers. That’s because almost anyone who’s the target demographic of these AI tools is already using it. I don’t see what market is even left to cover. But let’s say their user base is 2 billion ( open AI has 1 billion, I’m extrapolating the rest based on market share) and they’re trying to get almost everyone on the planet with an internet connection to use these products, which is 6 billion, that still means at current prices, they’re only 3-4℅ of the way there.
I don’t really believe that. Have 1 billion people used it at least once? Maybe? Maybe part of that 1 billion is the same people on different accounts. I definitely don’t think there are 1 billion regular users.
Just to add a soupcon of detail: both Codex (OpenAI) and Claude Code (Anthropic) have had significant price increases this year. Eg:
The goal (clearly) has always been B2B sales… with consumer tiers slowly being tightened or transitioned. At the moment, OpenAI is stupidly, unsustainably generous with their $20/month tier (which includes separate pools for chat and Codex). As we’ve seen with Anthropic, that will slowly winnow down to the point of non-utility.
IOW, the plan is proceeding as “intended”. See: Airbnb, Uber, etc.
IOW, the plan is proceeding as “intended”. See: Airbnb, Uber, etc.
That’s where I disagree. Uber maybe has a viable business as long as they keep finding gullible or desperate people to drive for them. Their OpEx costs are tiny, it’s nothing more than a system that receives a message that someone wants a ride and sends out a bid to take that customer. Then it’s a pricing algorithm that drops the price that they pay to drivers as low as possible, while driving the cost of the ride as high as possible. They get whatever slim margin is left.
AirBnB is similar, virtually no OpEx costs, a very simple set of algorithms to match places for rent with people wanting to rent them, then fiddle with the prices and extract a middle-man fee. As long as they keep staying ahead of government regulations, there’s a business there.
But, nobody had to go out and explain to drivers why they might want to drive for Uber. “You drive people, we pay you money”, it’s a simple sales pitch. Same with AirBnB. Hotels and taxis were annoying enough that it was easy for consumers too. But, nobody has yet found a long-term justification for chatbots.
Sure, some companies are trying to use them. But, not successfully. Air Canada replaced customer service reps (presumably in a call centre in India or something) with a chatbot. But, when that chatbot hallucinated a policy when talking to a customer, the courts found that Air Canada had to honour that policy. That’s a massive risk long term, especially once people get good at figuring out how to talk to them.
People are using them to generate vast amounts of code… but code is a liability, not an asset. The things code can do might be an asset, but you have to be able to understand and maintain the code for it to work. If people are using AI to generate the code, and other people are using AI to review it, nobody actually understands it. This is just a time bomb waiting to blow up.
If there really were some kind of guaranteed money making thing that chatbots could do (other than online scams), the AI companies wouldn’t be out there trying to sell AI in general, they’d be buying companies and/or starting divisions that did that one thing.
IMO, the AI companies intended to hit AGI, and hand everything over to the machine god. Now they realize that it really just is a clever word-guessing machine with some vague capabilities that niche users might want (but not at the price they can meet), and they’re scrambling to find a seat before the music stops.
I think you’ve answered a different question to the one I was making. I’m not claiming chatbots are a sound business. I’m saying the pricing path follows the Uber/Airbnb playbook: subsidise hard to build the user base, then tighten the consumer tier once the real money is elsewhere. That’s the “as intended” bit.
Uber’s also a shaky example for “virtually no OpEx”. It lost money for the better part of a decade, running on investor-funded rides and driver incentives, before it squeezed either side. That’s the pattern I was pointing at: generous now, worse later.
Whether the underlying business holds up is a separate argument, and you’ve got a fair point there (Air Canada is a good example of the liability risk). It just isn’t the argument I was making.
I think part of that is because Uber’s version of “AI companies chasing AGI” was self-driving cars. They were pretty obviously just relying on human drivers until they could replace them with self-driving cars. When it turned out that was going to take too long, that was when they really started raising prices and lowering pay. They also had to get into delivering food, competing with Doordash etc. I think the AI companies will try to follow this model: raise prices, lower services, and pivot to an alternative market that uses similar tech. I don’t know what that would be for AI, though. Ultimately, the real difference between Uber/Airbnb and the newer AI companies is that Uber and Airbnb worked on a technical level. This AI shit does not.
Well put. This is just another version of the same old game. Over-leverage on hype, cash out, push the losses on the public, and the government cleans up the mess. 😡
To put that in context, Alphabet (Google’s parent) is the biggest software company in the world. It’s the 3rd biggest company in the world after nVidia and Apple, but they’re mostly hardware companies.
Google’s annual revenues are creeping up towards $500b/year. So, the AI companies (Google included I suppose) would need 12x Google’s annual revenue just to break even.
There are 2 companies that have over $1b in annual revenue, Amazon and Wal*Mart. But, those are companies that sell goods to consumers, they’re not just digital services businesses. But, even then, you’d need 3x the revenue of Amazon and Wal*Mart combined to hit $6t.
Google, Apple, nVidia, Wal*Mart and Amazon each took decades to grow enough to capture hundreds of millions of dollars in revenue. So, somehow OpenAI and Anthropic are going to need to grow faster than any other company on earth to hit these trillion dollar targets.
Also putting this number into scale, there are about 8.3 billion people on the Earth. But, most of them are poor goat herders, subsistence farmers, sweatshop employees, and AI model trainers / reviewers living in Asia and Africa. These aren’t the kinds of people who are going to be buying a subscription to ChatGPT. There are maybe 1 billion people globally who have disposable cash they can spend on AI. So, to hit 6 trillion annually, each person living in a developed country would need to personally hit $6000 in AI spending on a yearly basis. Note, that includes children and the elderly. If you limit it to working-age people, that’s more like $10k per person per year.
Now, it doesn’t have to be that this is down to consumers. Maybe this is so valuable that Wal*Mart, the US government, and every other large employer pays for a ChatGPT subscription for each of their millions of employees. But, really, despite the fact that there have been very few actual successful AI deployments that saved companies money, or generated more profits, they’re suddenly going to be spending a significant fraction of each worker’s wage on AI subscriptions?
I think it’s pretty obvious that the AI companies thought that they were about to invent AI jesus. They thought they were just a few datacentres away from the machine god coming to life. They thought that AGI would change the world to such a degree that it might make the entire economy obsolete, so there was no limit on how much they should spend so either they would get there first (and maybe be seen as the god’s parents?) or out of some kind of altruism-type-feeling so that they could make a machine god which would align with their beliefs. But, that didn’t happen.
I saw a comment the other day about AI firms and CapEx vs OpEx. CapEx is Capital Expenditures – basically one-time costs for setting up a business. OpEx is Operational Expenses, basically ongoing costs for running a business. A good way to generate money from a business is to have a high CapEx and low OpEx. It’s hard for someone to set up a competing business because of the high initial costs, but once it’s up and running you can provide services for a low ongoing cost, and you can make a high profit on each customer. If CapEx is low but OpEx is high, sometimes it can work as a luxury business. Think an artist who hand-carves furniture. If both CapEx and OpEx are low, it’s basically a commodity business, think something like a nail salon. Cheap to set up, cheap to run, hard to fight off competitors.
The AI companies are stuck in a world where they have incredibly high CapEx (building DCs and training new models), and incredibly high OpEx (inference queries – basically talking to the chatbot, is also very expensive). Right now to try to hook customers they’re subsidizing the OpEx side of things, so each new customer costs them more money. Their paid tiers are even worse because people actually start really using the chatbots once they pay for them, and the money lost per customer goes way up for the paid tiers.
The only thing that would work is if the companies can somehow manage to get customers to pay incredibly high costs per token, so that not only are the OpEx costs covered, but the companies can start to pay down the initial CapEx. But, there’s just no justification for that yet. And the ruthless competition between all the AI companies means that if one of them starts trying to jack up costs to cover their OpEx, the others will keep theirs low to grab market share.
This is why the AI companies are doing all the things they’re doing. They’re talking about their models “escaping containment” and “hacking” other companies. Why? Because that makes it sound like these things are so powerful that they can’t be contained, rather than it being that the AI companies are incompetent and building a locked-down test environment, and how they are just running dumb scripts that they’re not even looking at before the execute. They’re boosting stories about the AIs being so powerful that they’ll destroy the world so that CEOs think they need to buy subscriptions to this powerful machine god for their companies. They’re inviting regulations and laws so that no new AI companies can enter the business, and so that they’re all forbidden from building new models, which is a massive CapEx (sorta) cost.
They can’t admit that the attempt to build a machine god has failed, because that will cause the bubble to pop. What they want to do is survive long enough to go public so that the costs they’ve spent can be foisted on the dumb retail investors – and at this point on pension funds and anybody holding index funds, because these companies are so huge that index fund managers would be obligated to buy them. So, they need to keep scaring people about how incredibly powerful and unstoppable their word-guessing-machines are until their investors have safely grabbed their profits and everything can be allowed to explode.
Another comparison, they’ll need to make token cost 100x to get those numbers. That’s because almost anyone who’s the target demographic of these AI tools is already using it. I don’t see what market is even left to cover. But let’s say their user base is 2 billion ( open AI has 1 billion, I’m extrapolating the rest based on market share) and they’re trying to get almost everyone on the planet with an internet connection to use these products, which is 6 billion, that still means at current prices, they’re only 3-4℅ of the way there.
Yeah this is going to be a freaking disaster.
I don’t really believe that. Have 1 billion people used it at least once? Maybe? Maybe part of that 1 billion is the same people on different accounts. I definitely don’t think there are 1 billion regular users.
Just to add a soupcon of detail: both Codex (OpenAI) and Claude Code (Anthropic) have had significant price increases this year. Eg:
The goal (clearly) has always been B2B sales… with consumer tiers slowly being tightened or transitioned. At the moment, OpenAI is stupidly, unsustainably generous with their $20/month tier (which includes separate pools for chat and Codex). As we’ve seen with Anthropic, that will slowly winnow down to the point of non-utility.
IOW, the plan is proceeding as “intended”. See: Airbnb, Uber, etc.
That’s where I disagree. Uber maybe has a viable business as long as they keep finding gullible or desperate people to drive for them. Their OpEx costs are tiny, it’s nothing more than a system that receives a message that someone wants a ride and sends out a bid to take that customer. Then it’s a pricing algorithm that drops the price that they pay to drivers as low as possible, while driving the cost of the ride as high as possible. They get whatever slim margin is left.
AirBnB is similar, virtually no OpEx costs, a very simple set of algorithms to match places for rent with people wanting to rent them, then fiddle with the prices and extract a middle-man fee. As long as they keep staying ahead of government regulations, there’s a business there.
But, nobody had to go out and explain to drivers why they might want to drive for Uber. “You drive people, we pay you money”, it’s a simple sales pitch. Same with AirBnB. Hotels and taxis were annoying enough that it was easy for consumers too. But, nobody has yet found a long-term justification for chatbots.
Sure, some companies are trying to use them. But, not successfully. Air Canada replaced customer service reps (presumably in a call centre in India or something) with a chatbot. But, when that chatbot hallucinated a policy when talking to a customer, the courts found that Air Canada had to honour that policy. That’s a massive risk long term, especially once people get good at figuring out how to talk to them.
People are using them to generate vast amounts of code… but code is a liability, not an asset. The things code can do might be an asset, but you have to be able to understand and maintain the code for it to work. If people are using AI to generate the code, and other people are using AI to review it, nobody actually understands it. This is just a time bomb waiting to blow up.
If there really were some kind of guaranteed money making thing that chatbots could do (other than online scams), the AI companies wouldn’t be out there trying to sell AI in general, they’d be buying companies and/or starting divisions that did that one thing.
IMO, the AI companies intended to hit AGI, and hand everything over to the machine god. Now they realize that it really just is a clever word-guessing machine with some vague capabilities that niche users might want (but not at the price they can meet), and they’re scrambling to find a seat before the music stops.
I think you’ve answered a different question to the one I was making. I’m not claiming chatbots are a sound business. I’m saying the pricing path follows the Uber/Airbnb playbook: subsidise hard to build the user base, then tighten the consumer tier once the real money is elsewhere. That’s the “as intended” bit.
Uber’s also a shaky example for “virtually no OpEx”. It lost money for the better part of a decade, running on investor-funded rides and driver incentives, before it squeezed either side. That’s the pattern I was pointing at: generous now, worse later.
Whether the underlying business holds up is a separate argument, and you’ve got a fair point there (Air Canada is a good example of the liability risk). It just isn’t the argument I was making.
I think part of that is because Uber’s version of “AI companies chasing AGI” was self-driving cars. They were pretty obviously just relying on human drivers until they could replace them with self-driving cars. When it turned out that was going to take too long, that was when they really started raising prices and lowering pay. They also had to get into delivering food, competing with Doordash etc. I think the AI companies will try to follow this model: raise prices, lower services, and pivot to an alternative market that uses similar tech. I don’t know what that would be for AI, though. Ultimately, the real difference between Uber/Airbnb and the newer AI companies is that Uber and Airbnb worked on a technical level. This AI shit does not.
Well put. This is just another version of the same old game. Over-leverage on hype, cash out, push the losses on the public, and the government cleans up the mess. 😡