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Cake day: June 15th, 2023

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  • Apple tried to allow clones, but ran into the same problem because the clone makers could make cheaper machines by slapping together parts.

    Yeah, this is exactly what happened, although some of the clone brands were perfectly high-quality (Power Computing in particular made great machines, usually the fastest on the market). In the Mac community at the time, a lot of people (myself included) wished Apple would just exit the hardware business and focus on what they were good at: software.

    Then Steve Jobs came back and did exactly the opposite of that. First order of business was to kill cloning. Then came the iPod.

    To be fair, the next generation of Power Macs after that were about half the price of the previous gen.


  • GenderNeutralBro@lemmy.sdf.orgtoMemes@lemmy.mlCosts Less? When That Happened?
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    22 days ago

    Most of Apple’s history, actually.

    Macs have a reputation for being expensive because people compare the cheapest Mac to the cheapest PC, or to a custom-built PC. That’s reasonable if the cheapest PC meets your needs or if you’re into building your own PC, but if you compare a similarly-equipped name-brand PC, the numbers shift a LOT.

    From the G3-G5 era ('97-2006) through most of the Intel era (2006-2020), if you went to Dell or HP and configured a machine to match Apple’s specs as closely as possible, you’d find the Macs were almost never much more expensive, and often cheaper. I say this as someone who routinely did such comparisons as part of their job. There were some notable exceptions, like most of the Intel MacBook Air models (they ranged from “okay” to “so bad it feels like a personal insult”), but that was never the rule. Even in the early-mid 90s, while Apple’s own hardware was grossly overpriced, you could by Mac clones for much cheaper (clones were licensed third-parties who made Macs, and they were far and away the best value in the pre-G3 PowerPC era).

    Macs also historically have a lower total cost of ownership, factoring in lifespan (cheap PCs fail frequently), support costs, etc. One of the most recent and extensive analyses of this I know if comes from IBM. See https://www.computerworld.com/article/1666267/ibm-mac-users-are-happier-and-more-productive.html

    Toward the tail end of the Intel era, let’s say around 2016-2020, Apple put out some real garbage. e.g. butterfly keyboards and the aforementioned craptastic Airs. But historically those are the exceptions, not the rule.

    As for the “does more”, well, that’s debatable. Considering this is using Apple’s 90s logo, I think it’s pretty fair. Compare System 7 (released in '91) to Windows 3.1 (released in '92), and there is no contest. Windows was shit. This was generally true up until the 2000s, when the first few versions of OS X were half-baked and Apple was only just exiting its “beleaguered” period, and the mainstream press kept ringing the death knell. Windows lagged behind its competition by at least a few years up until Microsoft successfully killed or sufficiently hampered all that competition. I don’t think you can make an honest argument in favor of Windows compared to any of its contemporaries in the 90s (e.g. Macintosh, OS/2, BeOS) that doesn’t boil down to “we’re used to it” or “we’re locked in”.




  • Probably ~15TB through file-level syncing tools (rsync or similar; I forget exactly what I used), just copying my internal RAID array to an external HDD. I’ve done this a few times, either for backup purposes or to prepare to reformat my array. I originally used ZFS on the array, but converted it to something with built-in kernel support a while back because it got troublesome when switching distros. Might switch it to bcachefs at some point.

    With dd specifically, maybe 1TB? I’ve used it to temporarily back up my boot drive on occasion, on the assumption that restoring my entire system that way would be simpler in case whatever I was planning blew up in my face. Fortunately never needed to restore it that way.



  • Both.

    The good: CUDA is required for maximum performance and compatibility with machine learning (ML) frameworks and applications. It is a legitimate reason to choose Nvidia, and if you have an Nvidia card you will want to make sure you have CUDA acceleration working for any compatible ML workloads.

    The bad: Getting CUDA to actually install and run correctly is a giant pain in the ass for anything but the absolute most basic use case. You will likely need to maintain multiple framework versions, because new ones are not backwards-compatible. You’ll need to source custom versions of Python modules compiled against specific versions of CUDA, which opens a whole new circle of Dependency Hell. And you know how everyone and their dog publishes shit with Docker now? Yeah, have fun with that.

    That said, AMD’s equivalent (ROCm) is just as bad, and AMD is lagging about a full generation behind Nvidia in terms of ML performance.

    The easy way is to just use OpenCL. But that’s not going to give you the best performance, and it’s not going to be compatible with everything out there.