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So Nvidia is basically farming everyone else?
Now use common accounting standard and amortize the cost.

Oh it doesn't fit the narrative. Never mind then.

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Deepseek is really killing it if that's their total spend
For a rapidly growing new line of business, this isn't bad at all.
To be honest whatever author wanted to say there three categories of AI related companies: hardware manufacturers, cloud providers and purely AI companies.

Only the later have something to lose if AI bubble gone by tomorrow. Everyone else will just stay with grown capacity and reuse infrastructure for whatever.

Not listing other hardware companies is just dishinest. AI is not a crypto mining where resources are just burned.

Possibly profitable for New-Gen Labs (DS, Qwen, Kimi, etc) and impossibly unprofitable for the Legacy Labs (OpenAI, Anthropic)
Remember the model:

1. Outspend and outlast your competition until you have market dominance. Win over and lock in your customers with sweetheart deals.

2. Enshittify and squeeze your customers to pay back your debt.

If you're using AI, you're not paying the true cost right now because we're in phase 1. Be ready for phase 2.

It’s weird to me that people here suddenly seem to care about profitability for relatively early stage companies just because they’re “AI”.

I know a traditional SaaS company I worked for that IPO’d years ago and still has no signs that they can be profitable (and many others like it) and nobody seems particularly concerned.

That's pretty funny. For the "yet" part I would have expected a more recent cutoff, rather than the whole history of the companies. (Do they all have some kind of enormous debts they're going to need to pay off for decades once they do become profitable?)
I've received some decent benefits from it without paying anything.
AMD, Alibaba should be on there too. AMD is making good money on AI, with R&D at less than half the AI revenue. Whereas Alibaba's weird financials show it's kinda-sorta-protifable?

I just wanna know how the OpenAI/Anthropic shell game works long-term. So both companies made equity deals with infrastructure providers; OpenAI on Azure, Anthropic on AWS, GCloud, and Colossus. They get a loan of compute credits and then pay for the compute with the credits. So the PaaS are effectively giving them free compute, then book it as revenue; and the AI provider lets them do inference and books that as revenue. So, it's like both types of company have a buffet, and let each other eat there for free. But somebody has to actually buy the pasta salad, with real dollars. Afaict, those real dollars are.... the cash reserves of the PaaS.

How long are they going to eat into that cash? Microsoft and AWS don't really have their own models, whereas Google and SpaceX do. And while Google has tons of cash, SpaceX is perpetually looking for cash. So the only player here that can actually afford to keep doing this, or leave the game entirely, is Google.

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I don't have an MBA or anything but is it common practice to describe "revenue - capex" as "profit"?
This is pretty funny. Now do it without Nvidia and including all costs, not just capex.
How are the Google numbers calculated? I've seen their net income increasing a lot as they've rolled out Gemini. This suggests that Gemini tokens are actually profitable, or at least not extremely unprofitable.

Yet this site suggests that tokens are very unprofitable

Is the "$ Spent on AI since page load" broadly indicative of spend at all, or just a fun animation?
Gemini now remembers you wholesale and makes good analogies and shortcuts knowing youres personal capabilities. You are already hooked and paying starts any day now. Or maybe it starts recommending some marvellous products somewhat related to your query.
nice pkd reference
Yes, I spend my days writing lots of code using AI (I do rigorously review it, it's still much faster than hand typing) and I get paid enough for it to pay mortgage and send kids to college.
Reminds me of the “Has The Turing Test Been Passed” website. It says no, but if you read on they cite “The relatively minimal funding allocated to AI research” as one of the reasons AI hasn’t been achieved “yet”. Website stopped being updated before it became relevant, so you will never see it say “yes”, similarly to how the Loebner prize mysteriously vaporized when GPT-2 came out, just when winning it for real started becoming an interesting possibility
Nvidia making out selling shovels, that's for sure.