Yes, you are correct. Many companies, especially in the tech industry, lose money for the first three to five years after opening.
What you have below are people who do not understand basic business concepts, such as the difference between revenue and profit, let alone capital investment.
You are also contending with people who hate something they do not understand. They call LLMs “AI,” dislike Sam Altman and OpenAI, and often do not even realize there are other companies and models that, depending on the metric, can outperform ChatGPT. They are hating for the sake of hating while disguising it as enlightenment. It is quite frustrating, and I push back against it whenever I can.
At the end of the day, people need something to hate, and right now LLMs and data centers have become convenient targets.
That is not to say there is nothing wrong with the industry. There is. Data centers consume enormous resources, and the constant drive for profit creates plenty of legitimate concerns.
My point is simply that many of these people do not actually understand what they are arguing against in the first place.
The amount of money that’s been invested in this will require 100 million people to pay $10,000 per year so they can have a 5% return on investment.
Who is actually going to be paying that kind of money for AI services? Has anyone ever actually worked for a company before? You need to go through layers of red tape to requisition a new office chair. Are companies actually going to spend hundreds of thousands of dollars per year for AI?
I’ve asked people that have used AI to alter photos (currently free to them, paid for by investors) how much they’d for such a service. Nothing, just would leave the photo as-is. There’s a big market for “free AI” but the market for AI where the users pay the cost + profit margin is a small fraction of that.
So why is this stuff valued in the trillions? Simply because the greater fool will buy shares so line goes up. Once the pension funds buy in, then a bunch of billionaires get together and short it simultaneously. They’ll make money and everyone else loses. That’s how it worked in the dot com bubble, there’s no reason to expect it will go any differently for AI.
Of course you might have gotten confused because there’s real tech in the story. Same as there was in the dot com bubble. We’re having this conversation on the internet right now. But seeing tech, using the tech doesn’t mean the tech isn’t overvalued. One of the “ridiculous” claims of the dot com bubble was that you’d be able to pet food over the internet. Today we most definitely can do that. Just because that eventually proven correct, it didn’t make sense in 1999, and having billions invested in something that wouldn’t have results for more than a decade isn’t a good investment. Equipment depreciates, and high-tech equipment depreciates rapidly. Buying networking equipment for an online retailer ten years before the logistics needed are in place is just throwing away money.
Buying GPUs before there’s a data center built to put them is throwing away money. Facebook is putting them in tents, Samsung wants to put them on ships. Obviously these GPUs aren’t going to last long operating in these conditions, but it’ll take years before there’s data centers built and even longer before there’s enough power generation needed to run them. They’re just milking every last dollar from investors by doing these things.
Many of the things promised are straight up lies (Halting Problem, anyone?) and it’ll be years before the the infrastructure is built. Right now they’re maxing the hype and making as much as they can before the bubble bursts. And why not? Fraud is effectively decriminalized in the US.
Right. Corporations do not pay taxes on income; they pay taxes on profits, and the tax code gives them significant flexibility in determining what counts as profit. Loans are not taxed. “Buy, borrow, die” is legal. We have weak antitrust enforcement. Politicians can trade stocks despite occupying positions that give them access to information the public does not have. Competition in many industries has declined, reducing incentives to prioritize consumers. We even have private healthcare.
So what is your point?
Companies, especially in the tech industry, have historically operated at a loss during their first several years. Even after becoming established, a 4% profit margin is often considered respectable. Revenue and profit are not the same thing, and investing heavily for growth is a normal business practice.
I was talking about people criticizing LLMs while clearly knowing very little about them. The bandwagon effect on this platform is strong. Many people dislike LLMs, call everything “AI,” and often do not understand the underlying technology, the economics behind it, or the fact that there are multiple companies competing in the space. I push back when I see criticism based on misunderstandings rather than facts.
There are definitely many companies willing to throw millions a year at AI, and are currently doing it, but as it stands today, it doesnt sound like they’re getting the return on investment they expected.
It can change if the models actually got better, but how much of it is inherint to how LLMs are made, and/or how much more can they be improved before this all falls apart
Yes, you are correct. Many companies, especially in the tech industry, lose money for the first three to five years after opening.
What you have below are people who do not understand basic business concepts, such as the difference between revenue and profit, let alone capital investment.
You are also contending with people who hate something they do not understand. They call LLMs “AI,” dislike Sam Altman and OpenAI, and often do not even realize there are other companies and models that, depending on the metric, can outperform ChatGPT. They are hating for the sake of hating while disguising it as enlightenment. It is quite frustrating, and I push back against it whenever I can.
At the end of the day, people need something to hate, and right now LLMs and data centers have become convenient targets.
That is not to say there is nothing wrong with the industry. There is. Data centers consume enormous resources, and the constant drive for profit creates plenty of legitimate concerns.
My point is simply that many of these people do not actually understand what they are arguing against in the first place.
The amount of money that’s been invested in this will require 100 million people to pay $10,000 per year so they can have a 5% return on investment.
Who is actually going to be paying that kind of money for AI services? Has anyone ever actually worked for a company before? You need to go through layers of red tape to requisition a new office chair. Are companies actually going to spend hundreds of thousands of dollars per year for AI?
I’ve asked people that have used AI to alter photos (currently free to them, paid for by investors) how much they’d for such a service. Nothing, just would leave the photo as-is. There’s a big market for “free AI” but the market for AI where the users pay the cost + profit margin is a small fraction of that.
So why is this stuff valued in the trillions? Simply because the greater fool will buy shares so line goes up. Once the pension funds buy in, then a bunch of billionaires get together and short it simultaneously. They’ll make money and everyone else loses. That’s how it worked in the dot com bubble, there’s no reason to expect it will go any differently for AI.
Of course you might have gotten confused because there’s real tech in the story. Same as there was in the dot com bubble. We’re having this conversation on the internet right now. But seeing tech, using the tech doesn’t mean the tech isn’t overvalued. One of the “ridiculous” claims of the dot com bubble was that you’d be able to pet food over the internet. Today we most definitely can do that. Just because that eventually proven correct, it didn’t make sense in 1999, and having billions invested in something that wouldn’t have results for more than a decade isn’t a good investment. Equipment depreciates, and high-tech equipment depreciates rapidly. Buying networking equipment for an online retailer ten years before the logistics needed are in place is just throwing away money.
Buying GPUs before there’s a data center built to put them is throwing away money. Facebook is putting them in tents, Samsung wants to put them on ships. Obviously these GPUs aren’t going to last long operating in these conditions, but it’ll take years before there’s data centers built and even longer before there’s enough power generation needed to run them. They’re just milking every last dollar from investors by doing these things.
Many of the things promised are straight up lies (Halting Problem, anyone?) and it’ll be years before the the infrastructure is built. Right now they’re maxing the hype and making as much as they can before the bubble bursts. And why not? Fraud is effectively decriminalized in the US.
Right. Corporations do not pay taxes on income; they pay taxes on profits, and the tax code gives them significant flexibility in determining what counts as profit. Loans are not taxed. “Buy, borrow, die” is legal. We have weak antitrust enforcement. Politicians can trade stocks despite occupying positions that give them access to information the public does not have. Competition in many industries has declined, reducing incentives to prioritize consumers. We even have private healthcare.
So what is your point?
Companies, especially in the tech industry, have historically operated at a loss during their first several years. Even after becoming established, a 4% profit margin is often considered respectable. Revenue and profit are not the same thing, and investing heavily for growth is a normal business practice.
I was talking about people criticizing LLMs while clearly knowing very little about them. The bandwagon effect on this platform is strong. Many people dislike LLMs, call everything “AI,” and often do not understand the underlying technology, the economics behind it, or the fact that there are multiple companies competing in the space. I push back when I see criticism based on misunderstandings rather than facts.
There are definitely many companies willing to throw millions a year at AI, and are currently doing it, but as it stands today, it doesnt sound like they’re getting the return on investment they expected.
It can change if the models actually got better, but how much of it is inherint to how LLMs are made, and/or how much more can they be improved before this all falls apart
It cant go on forever as is today.