The AI Demand Bubble
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The AI Demand Bubble
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Re: The AI Demand Bubble
#2This is a bit of a doomer article, but quite honestly, 200 billion dollars a year on a 30 billion dollar a year business that is growing does not really sound as bad as the author makes it out to be, especially when that business consists of growth startups that are currently primarily concerned with completely automating your current revenue stream.
The obvious way to recoup spend is to grow, rugpull by cranking up costs 6x and reducing inference cost by half (highly achievable with improved silicon and technology), then simply fire a large percentage of software engineers. From that perspective the current behavior is a bit wicked but downright logical.
And having two whale customers is not really out of the ordinary for any software company... it's just the scale that is staggering.
The actual risk that the author does not even broach upon for investors... the thing that will actually torpedo this massive investment are the open source open weight chinese models that commoditize the entire endeavor. If you don't have a monopoly, you cannot rugpull and 6x the costs on the consumer.
Ironically, the actual thing that will likely kill OpenAI is ACTUAL OPEN AI.
Re: The AI Demand Bubble
#3This is a bit of a doomer article, but quite honestly, 200 billion dollars a year on a 30 billion dollar a year business that is growing does not really sound as bad as the author makes it out to be, especially when that business consists of growth startups that are currently primarily concerned with completely automating your current revenue stream. The obvious way to recoup spend is to grow, rugpull by cranking up…
> The actual risk that the author does not even broach upon for investors... the thing that will actually torpedo this massive investment are the open source open weight chinese models that commoditize the entire endeavor.
So much this. I've never touched the Chinese models (no particular reason) but it is having an impact as the frontier companies are pushing the price down as a defensive measure. Is this pulling forward what would have happened eventually? No idea.
It is unclear how effective anyone beyond China and Mistral have been at developing cheaper, capable models. It is an expensive business. I'd be curious if anyone had any thoughts on that
Re: The AI Demand Bubble
#4[flagged]
Re: The AI Demand Bubble
#5This is a bit of a doomer article, but quite honestly, 200 billion dollars a year on a 30 billion dollar a year business that is growing does not really sound as bad as the author makes it out to be, especially when that business consists of growth startups that are currently primarily concerned with completely automating your current revenue stream. The obvious way to recoup spend is to grow, rugpull by cranking up…
> The actual risk that the author does not even broach upon for investors... the thing that will actually torpedo this massive investment are the open source open weight chinese models that commoditize the entire endeavor.
OpenAI and Anthropic investors yes, however open weight models are good for cloud providers. They can turn the two large customers into direct ai services that can be spread across many customers and reduce the cloud providers overhead on ai services.
Re: The AI Demand Bubble
#6I'm seeing this guy everywhere. He was on Bloomberg a day ago and then on another channel and now here. I'm curious why there are not more people like him voicing their concerns. Makes you wonder if he is completely wrong.
Re: The AI Demand Bubble
#7This is a bit of a doomer article, but quite honestly, 200 billion dollars a year on a 30 billion dollar a year business that is growing does not really sound as bad as the author makes it out to be, especially when that business consists of growth startups that are currently primarily concerned with completely automating your current revenue stream. The obvious way to recoup spend is to grow, rugpull by cranking up…
unironically sama is probably one of the most honest players here after all, he is burning money and if/when they have achieved AGI they will ask it in how to make money. its a different investor incentive story than trying to monetize into profitability right now that is indeed doomed to fail against china. Having no idea but a vision achieved is rrquired to be met to have those returns is actually the honest part here.
Re: The AI Demand Bubble
#8This is a bit of a doomer article, but quite honestly, 200 billion dollars a year on a 30 billion dollar a year business that is growing does not really sound as bad as the author makes it out to be, especially when that business consists of growth startups that are currently primarily concerned with completely automating your current revenue stream. The obvious way to recoup spend is to grow, rugpull by cranking up…
> The actual risk that the author does not even broach upon for investors... the thing that will actually torpedo this massive investment are the open source open weight chinese models.
The monopoly will likely then shift from the model to the compute, i.e. who has the GPUs to serve inference at scale from the open weight models. The cloud compute giants have basically bought everything that Nvidia, Broadcom etc. have to offer. Currently, the inference margins are shared between the cloud giants and OpenAI/Anthropic. But if training great models becomes easier for some reason, the cloud giants benefit. Then they'll have used the OpenAI/Anthropic revenue and spending commitments to grow their cloud business, and then can serve other models and make even more money.
Given that OpenAI and Anthropic are private, I don't think there is any risk to retail investors in this scenario. AI not turning out to be so useful, and OpenAI/Anthropic not being able to pay their bills is the correct failure scenario i think, as identified by the author.
Re: The AI Demand Bubble
#9I'm seeing this guy everywhere. He was on Bloomberg a day ago and then on another channel and now here. I'm curious why there are not more people like him voicing their concerns. Makes you wonder if he is completely wrong.
His history of predictions about LLMs is not great and he generally seems ideologically committed to pretending they're almost useless and teetering on the edge of collapse.
For example, this article claims: "Every single story you’ve read about the “incredible growth” of these cloud platforms is an embarrassing misread of three companies that are misleading investors that will more than likely be forced in the next year or two to have to restate revenues, cut remaining performance obligations, and admit that they’ve drastically overbuilt capacity. "
In july 2024, Zitron wrote at length about how the economics of OpenAI were likely to collapse in the next 1 to 2 years [1].
It seems like the nearly inevitable collapse of generative AI is always 1 to 2 years away, but it's just the details of the intricate financial argument that change.
Re: The AI Demand Bubble
#10This is a bit of a doomer article, but quite honestly, 200 billion dollars a year on a 30 billion dollar a year business that is growing does not really sound as bad as the author makes it out to be, especially when that business consists of growth startups that are currently primarily concerned with completely automating your current revenue stream. The obvious way to recoup spend is to grow, rugpull by cranking up…
> that is growing
It seems like user numbers are stagnating, and the ad play isn't working out so far. Where is the revenue growth coming from? I don't think API can be the answer, because API has absolutely no switching costs.
> The obvious way to recoup spend is to grow, rugpull by cranking up costs 6x
Presumably, that was the plan, but I don't see how that can possibly work with how quickly the Chinese models caught up.