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Cake day: June 14th, 2023

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  • Want something faster? Look into business small PCs they are about the size of the small ps2 and will have Intel i3s to i7s. I’d just recommend looking for one that is at least the 8th gen Intel if you care about power efficiency. If using eBay search for used auctions and use a bid sniper that uses the official api

    Are they still available? When I looked recently, most of it was Haswell/4th gen, and/or the seller had taken nearly all the parts out, like the memory, drives, and CPU.




  • Hardware is used way more efficiently in the data center, and any sort of deficit is best resolved in a centralized system due to more efficient resource allocation. The same setup could be used like 2 hours a day for your personal needs, or 24 hours a day to serve many people.

    Only for a rather narrow definition of efficiency, though. For raw compute power, yes, but you’d also be adding a whole bunch of overhead from all the network traffic and routing that would be necessary for that sort of thing to work in the first place.

    If people used their desktops like in the old days where you’d connect to a mainframe or master computer, you’d end up needing computing hardware on both ends anyway, since the user side would need to be enough to be able to connect and send all the interactions to the master computer. At that point, you could just buff up the client computer, and do all that in the user’s home.

    There’s also an argument that some of the basic problems would still apply anyway. A data centre does not fully utilise 100% of its capacity. There’d always be some reserve to have failover if a server dies, or there’s a sudden spike in load, like with a home machine.





  • Probably the pollution. A lot of AI companies are trying to find ways around it, by including watermarks in their model output that their tools can detect, and so on.

    We already know that training models on themselves causes model collapse, so OpenAI deciding that they’ve had quite enough wouldn’t be surprising.

    On top of that, a lot of websites are clamping down on access because of scraping concerns. Reddit shut down a lot of their third-party APIs, and nicer features, like RSS, Old Reddit (if you haven’t used it in 6 months, you lose access to it, and you need an account for it), etc. Google seems to want a captcha on every search. Twitter famously ramped up the price of its API immensely,.and now has ridiculously stringent measures for accounts, like needing users to download the app, and give hand-scans. It wouldn’t be at all surprising for OpenAI to decide its not worth the effort at this point to try and get around all that, nor pay for it, when they’ve already got all the previous data. Training doesn’t destroy the data used.

    A lot of AI training data these days is generated synthetically anyway, and that can be done in-house, whether by their own models, or downloading an open weights model and running it themselves.



  • There’s also a practical element, where Steam is not in a position to vet every game and developer. They could have the community do it, but that then opens up a whole bunch of abuse risks.

    There’s also an argument that it wouldn’t stop some of the issues in the article. Where do you draw the line with asset flip, or AI generated? If the developer used AI to make placeholders in the early access of a game, and then swapped it with removed it later on, is the game still AI generated? What if they used assets that were unknowingly AI generated, like stock sound effects?

    Or if someone is ESL and used a translator that turned out to be AI powered/they just write with a similar style.

    It also won’t stop people doing it.maliciously. if you’re threatening to clone someone’s game off a demo, and release it before they do, you’re probably not going to stop because you need to put a little “AI generated” flag on your game, if the rest of it didn’t stop you.