Edit: Brave in reading mode also works.
They plan to pay for most of it through excess cash flow, aka profits.
Follow on question: "they make $100s of billions per year? what did they do with all that previously?"
Answer: share buybacks, nothing (aka put it in the bank), acquisitions.
These companies make a ton of money and have a ton of margin over expenses.
If you doubt me they have openly stated this multiple times in their think tanks.
It's a really weird analogy.
They use it as an analogy with a supernova:
> And now this massive star is about to blow.
> (...) it runs out of the fuel that keeps the monster from collapsing in on itself under its own insanely powerful gravity.
> An imploding star crushes itself into a tiny ball, and the rebound instantly triggers a colossal explosion that lights up the entire galaxy. A bursting AI bubble threatens the entire American economy.
> The gravity inside the bubble is investor expectations.
> In a physics thought experiment, all it takes is tossing a pinch of iron into the furnace of a massive star teetering on the edge of explosion to trigger an instant implosion.
The last one isn't even wrong, since iron is the last element a star can fuse (iron core collapse)
Is this meant to make it easier to understand or harder?
This seems like a complicated way of saying that the AI bubble is hundreds of times bigger than the economy of one of the Baltic states.
Is the idea of a star hundreds of times bigger than the sun more "normal" than the idea of an economy hundreds of times bigger than one of the Baltic states?
> And now this massive star is about to blow.
> (...) it runs out of the fuel that keeps the monster from collapsing in on itself under its own insanely powerful gravity.
> An imploding star crushes itself into a tiny ball, and the rebound instantly triggers a colossal explosion that lights up the entire galaxy. A bursting AI bubble threatens the entire American economy.
> The gravity inside the bubble is investor expectations.
> In a physics thought experiment, all it takes is tossing a pinch of iron into the furnace of a massive star teetering on the edge of explosion to trigger an instant implosion.
I guess the last one isn't even wrong, since iron is the last element a star can fuse (iron core collapse)
I don't like the state of affairs either, this deluge of crash predictions are probably going to increase the irrationality of the market and make the bubble worse.
But brushing aside the irrationality for a moment, another problem is that there's not a lot of agreement about what constitutes the bubble popping. I think a lot of normal people would generally call it "the day the NASDAQ drops 20% or something like that", or maybe the week, and if that hasn't happened yet then it isn't "popped". There's two problems with that, though, the first of which is that there isn't guaranteed to be a huge down day or week at all, and the second is that such an event is usually a hugely lagging indicator. It is, one might say, the end of the end, but there is usually a beginning of the end before that.
It's kind of funny... sometimes the stock market is living so far in the future it boggles the mind, but sometimes it is the last thing to know, as everyone simultaneously banks on being able to get out before everyone else and grabbing every last penny from the money fountain while they can, even though they may all individually know the party is ending.
Or it could be massive -- it could be the straw that breaks the camel's back in a stock market that seems massively over-inflated given recent interest rate rises.
Oracle just made a step towards existing less, reverberating a negative wave through the entire system.
> First, their margins. They’re nowhere near enough to cover the cost of building models, running operations, and paying back investment commitments.
This is the same kind of thing that has been said about every growth company until they stop investing in growth and turn on profits. Nobody investing in AI companies want AI companies to be profitable right now.
> Second, as it turns out, businesses aren’t exactly eager to switch from older models to newer ones. The old models cover most of their needs, and switching is too complex and too risky to justify.
This just offered without evidence, and there is no reason at all to believe this is true.
> Third, there’s growing competition from open-weight models. The problem is obvious: why pay for expensive proprietary models when you can get by with much cheaper ones? This way, you control not just what you spend on the model but the model itself. You can run it on your own server, and nobody on “the other side” of the API can change a thing.
Two problems with this argument -- First, there are some tasks that cheaper models _cannot do_ and that newer models do easily. Second, you will not be able to run models locally cheaper than the big labs can run them at scale. If open weight models commoditize, OpenAI and Anthropic will _both_ be able to run them cheaper than almost any competitor, or than you can running them in your own data center.
Lucasoato•37m ago
No, I won’t. End of the story.
djoldman•36m ago
braiamp•33m ago
rwmj•24m ago
nathanaldensr•15m ago