A bit of napkin math: NVIDIA claims 0.4J per token for their latest generation 1GW plant with 80% utilisation can therefore produce 6.29 10^16 tokens a year.
There are ~10^14 tokens on the internet. ~10^19 tokens have been spoken by humans… so far.
Don't know what the source is, but it feels missing a few orders of magnitude. Surely it only counts text? I can't imagine there are only so few data on the internet if you count images and videos.
Does that include image tokens? My bet is with image tokens you are off by at least 5 orders of magnitude for both.
There were recent observations that rendering the text as an image and ingesting the image might actually be more efficient than using text embedding.
(6.29 10^16 tokens a year) * ($10 per 10^6 tokens)
= $6.29 10^11
= $629,000,000,000 per year in revenue
Per the article
> "It's my view that there's no way you're going to get a return on that, because $8 trillion of capex means you need roughly $800 billion of profit just to pay for the interest," he said.
$629 billion is less than $800 billion. And we are talking raw revenue (not profit). So we are already in the red.
But it gets worse, that $10 per million tokens costs is for GPT-5.1, which is one of the most expensive models. And the costs don't account for input tokens, which are usually a tenth of the costs of output tokens. And using bulk API instead of the regular one halves costs again.
Realistic revenue projections for a data center are closer to sub $1 per million tokens, $70-150 billion per year. And this is revenue only.
To make profits at current prices, the chips need to increase in performance by some factor, and power costs need to fall by another factor. The combination of these factors need to be, at minimum, like 5x, but realistically need to be 50x.
Aren't they comparing annual revenue to the annual interest you might have to pay on $8T? Which the original article estimates at $800B. That seems consistent.
But it looks like the investments are $80MMM for 1GW. Which, if true, would have the potential to be profitable, depending on depreciation and electricity costs.
Note that if we're including GPU prices in the top-line capex, the margin on that $70-150B is very healthy. From above, at 0.4J/T, I'm getting 9MT/kWh, or about $0.01/MT in electricity cost at $0.1/kWh. So if you can sell those MT for $1-5, you're printing money.
The IF is doing a lot of heavy lifting there.
I understood the OP in the context of "human history has not produced sufficiently many tokens to be sent into the machines to make the return of investment possible mathematically".
Maybe the "token production" accelerates, and the need for so much compute realizes, who knows.