To be clear, fuel cells are considered "low air pollution" because they eliminate certain nasty combustion products (NOx), but they still produce as much CO2 per kWh as a gas turbine.
Arguably that CO2 stream is concentrated and a candidate for capture/sequestration, but no one is doing that in practice.
I think the right comparison would be a vertically integrated Neocloud like Oracle (insofar as they own some/most of their own datacenters, unlike a CoreWeave).
Given the $10k price tag for tokens and high rate of bugs (several per minute) they mention, it'd be very interesting to see this experiment run with cheaper models too.
I wonder if we get to a world where a full repo sweep like this is a default Github action after commit.
and in the meantime, just a sweep of the committed code (or the to-be-committed code for lots of us) and the code it interacts with, is increasingly catching lots of problems.
The wild thing to me, is that they're serving $47B run rate worth of requests on maybe 2-3 GW of compute currently [1], of which only a fraction goes to inference, vs R&D and training. Obviously there have been complaints on token limits and such so they're stretched a bit thin, but nonetheless.
Hard to imagine what a world with 100GW of compute looks like.
It gets better; most of their incoming requests don't actually require a frontier model to handle. There's a huge potential for future optimization in this space. Anthropic, OpenAI, Google and a few other companies are going to be well positioned to scale in the few years. A 65$ billion round to finance operations over the next few years isn't that controversial if you look at the growth and profit potential.
I think token counts and GW are a gross over simplification here. Not all tokens are the same in the amount of GPU time they consume or the size of the GPUs they require or the amount of energy they consume. There's a huge optimization potential here once these companies get serious about consolidating the business they have and executing much more efficiently. Given enough time, these companies can heavily optimize their operations. Short term growth and not slamming the brakes on that is their primary concern.
I have been trying Claude Code with DeepSeek 4 apis, and the experience is barely different. In fact the margin of error is so small that harness and prompting account for the most impact in output quality.
But, here's the catch: I spend barely more than a handful of dollars per day of regular usage. In fact DS4 via api is cheaper than Claude 100$ subscription.
I really think that very soon many will start realizing that the alternatives are extremely close in performance but dramatically different in pricing.
Claude includes or at least promises ZDR in some situations, whereas DeepSeek is explicitly using output to train models. The subsidising might be done with your data.
Lately I've been thinking that UI really needs to include the equivalent of a screenshare meeting. Ideally you could click through an example of a software flow Claude's never seen before, with a few quick notes, and have it reliably work.
These narrow integrations with specific software suites seems like a dead end.
I had a similar, really great prof, who would always ask for what the next variable would be, so we'd end up with trees and smiley faces. His point was to not make assumptions (c is always a constant etc), but it made the classes more engaging too.
And, somehow every example ended along the lines of "then you hand this to your boss, kick up your feet and have a nice glass of scotch."
I think the water is difficult to traverse, in that it slows you down when 'swimming'.
It's really interesting how it still feels grounded even though you can fly all around. Having the cursor disappear underneath bridges and behind buildings really helps the illusion.
Do we know the breakdown of revenue from API vs subscriptions for OAI/Anthropic? That seems very relevant, since this entire article seems to be on the premise that users are only willing to pay for a subsidized subscription and would never pay the 'true' token cost.
The internet seems to be saying that 70%+ of Anthropic revenue is per-token metered API, which would largely invalidate the article, but I can't find a solid source.
Arguably that CO2 stream is concentrated and a candidate for capture/sequestration, but no one is doing that in practice.
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