So true. In my career (anecdotally), I’ve never encountered a data problem where the answer was ‘you didn’t choose this tech/language/product over another.’ It always comes down to decisions of governance and ownership. It’s Conway’s Law all the way down.
Fair point. I suspect if you priced that workload out on per-token API costs, it would be completely unviable for a bootstrapped business. The flat-rate subscription is really the only thing making it accessible right now.
> The flat-rate subscription is really the only thing making it accessible right now.
So this paragraph from the "Welcome To Gas Town" article [0] suggests to me that real, sustained users of a Gas Town instance are paying far, far more than -say- 600USD per month:
Gas Town is also expensive as hell. You won’t like Gas Town if you ever have to think, even for a moment, about where money comes from. I had to get my second Claude Code account, finally; they don’t let you siphon unlimited dollars from a single account, so you need multiple emails and siphons, it’s all very silly. My calculations show that now that Gas Town has finally achieved liftoff, I will need a third Claude Code account by the end of next week. It is a cash guzzler.
200 USD per month is something that I -as a working programmer- wouldn't think twice about spending for a fantastically useful tool (even if I had to spend it from my own pocket). If I had to pay 600 USD/month out-of-pocket, it would have me thinking for a bit to see if it was really worth it, but if the company was footing the bill, I'd expense it without a second thought.
Compared to USian programmer pay (especially Yeggie-level pay), 600 USD/month absolutely does not qualify as "a cash guzzler". Hell, that's less than the cost of the sort of health insurance you usually get at nice software companies.
I suppose that there's an alternative interpretation where Yeggie is concerned about the actual cost to the LLM company for the queries that Gas Town makes... but that seems unlikely to me. First, why would he care? Second, why would he say "You won’t like Gas Town if you ever have to think, even for a moment, about where money comes from."? I would give zero shits about where my LLM company's money comes from... that's not my problem.
He would care because the 200/m relies on users not using the whole allotment and is likely heavily subsidized. What if the true cost is 4x? (Feel free to add api pricing numbers and correct). Is a programmer willing to spend 2400/month?
If he did care, then why would he advertise and widely make the tool available? Wouldn't he keep it a secret closely held between him and his friends and colleagues?
After all, if folks that make real, sustained use of Gas Town are permitted to do it for 200, 400, or 600 USD per month, then widespread use of Gas Town absolutely destroys the heavy subsidy that his use of Gas Town theoretically relies on.
>Maia 200 is an AI inference powerhouse: an accelerator built on TSMC’s 3nm process with native FP8/FP4 tensor cores, a redesigned memory system with 216GB HBM3e at 7 TB/s and 272MB of on-chip SRAM, plus data movement engines that keep massive models fed, fast and highly utilized. This makes Maia 200 the most performant, first-party silicon from any hyperscaler, with three times the FP4 performance of the third generation Amazon Trainium, and FP8 performance above Google’s seventh generation TPU.
Anyone know what happened to the first gen chip that they announced at Ignite in 23?
>"As AI models get better at writing code, more and more people are asking the age-old question: where, and how, do I run my applications?" said Jake Cooper, Railway's 28-year-old founder and chief executive, in an exclusive interview with VentureBeat. "The last generation of cloud primitives were slow and outdated, and now with AI moving everything faster, teams simply can't keep up."
You'd have to ask the author or editor or whoever wrote the title, I can't say I get what that phrase means either. Broadly the primitives we're building are all aimed at shortening the distance between generating code and deploying it
ANN is an attempted model/ripoff (turned out to be extremely simplified but still) of a brain, why not go further? Continuous autonomous learning (which requires continuous feedback in a way of good/bad stimuli) is clearly what makes it work.
The current approach of guided pre-training and inference on essentially a "dead brain" clearly causes limitations.
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