• 0 Posts
  • 25 Comments
Joined 2 months ago
cake
Cake day: August 31st, 2026

help-circle
  • You must be confusing the invention of New York-style pizza with the invention of pizza itself?

    Pizza was being eaten in Naples in the 1700s, and the city had established pizzerias decades before Italian immigrants introduced it to New York in the late 19th century.

    New York-style pizza is an American adaptation of an existing Italian dish. How on earth do you think Italian Americans came to be making pizza in New York in the first place? 😂

    It’s quite impressive to be this confidently wrong about something that’s so trivially easy to verify. I assume you read it on a menu. Dont learn facts from menus lmfao.


  • You’re confusing personal preference with objective quality. Your palate is shaped by what you’ve grown up eating, so naturally, if you’re accustomed to American-style pizza, traditional pizza might not be what you imagine pizza should be.

    That doesn’t mean Italians are bad at making pizza. It means you’ve developed a preference for a particular interpretation of it. Someone raised in Naples might have exactly the opposite reaction to American pizza, in fact I imagine that’s very likely give the fat saturated nonsense I’ve experienced there. Deep dish pizzas are a crime, who the fuck wants more bread in their pizza.

    The fact that you’ve managed to visit the birthplace of pizza, discover that it doesn’t cater to your particular tastes, and conclude that an entire country doesn’t know how to make its own food is quite something.




  • The original point was that expanding data centres doesn’t disprove a big increase in efficiency per token. Usage, advsnced models/tokens per query and infrastructure can all grow at the same time as the energy required for an individual token falls. And thats an ongoing process.

    Companies you know cutting token spend, you thinking ubiquitous AI adoption is unrealistic, and newer models using more tokens per query are all arguments about future/total demand. None of them actually tell us whether a token is dramatically cheaper or more energy efficient to produce than it was a year ago. Realistically thats a learning curve problem, if someone is throwing a basic question at a model far more complex than it needs they are creating the inefficiency and that needs to be made more obvious/streamlined.

    I’ve not claimed demand had increased 900x. You inferred that from the existence of new data centres, which was the faulty bit of reasoning I was responding to in the first place.








  • You’re just repeating the same point I’ve just addressed, so I’ll explain in more detail.

    Data centres expanding is perfectly compatible with huge efficiency gains per token. If the cost of inference falls, companies can afford to run vastly more inference, serve more users, use larger models and embed AI into more products.

    It’s the same reason more fuel-efficient cars didn’t eliminate demand for roads or petrol. Efficiency lowers the cost of using something, which can increase total consumption.

    So “if software got more efficient, they wouldn’t need more data centres” is basically backwards. The relevant question is whether total AI demand is growing faster than efficiency is improving.