Off-and-on trying out an account over at @tal@oleo.cafe due to scraping bots bogging down lemmy.today to the point of near-unusability.

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Joined 3 years ago
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Cake day: October 4th, 2023

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  • Funnily enough, Microsoft built WSL so developers could use Linux without leaving Windows. Instead, it turned a growing number of Windows PCs into functional Linux development machines, with Windows serving as little more than the launcher.

    I mean, I get using Windows if you’re actually doing Windows development work, but if not, I’d just put Linux proper on the thing.

    The appeal for developers is that even if their employer issues a Windows laptop, and even when their development stack expects Linux, WSL removes the need to dual-boot.

    With WSL, they don’t have to fight their employer’s hardware policy to get it.

    Any employer that is employing someone to do Linux development work and takes issue with them having a Linux box to do dev work isn’t a place that I’d want to bother to work.





  • CloudFlare having that outage a while back was bigger, I’d say. GitHub is only used by a small percentage of people out there.

    If you want to go by “percentage of the Internet taken down”, the biggest outage ever has probably been the Morris Worm, since a lot of major insitutions quarantined themselves by closing down their network links to other sites until they could identify the problem, purge it, and secure their systems against reinfection.

    https://en.wikipedia.org/wiki/Morris_worm

    The Morris worm or Internet worm of November 2, 1988, was a malicious self-replicating computer program that affected VAX computers and SUN-3 workstations running the 4.2 and 4.3 Berkeley UNIX code.[1] It is one of the oldest computer worms distributed via the Internet, and the first to gain significant mainstream media attention.

    The Internet was partitioned for several days, as regional networks disconnected from the NSFNet backbone and from each other to prevent recontamination while cleaning their own networks.

    The Morris worm has sometimes been referred to as the “Great Worm”, named after the devastating “Great Worms” of Tolkien. The Morris worm had a devastating effect on the Internet at that time, both in overall system downtime and in psychological impact on the perception of security and reliability of the Internet.[17]






  • So, I’d just use Samba or whatever to share it too. It’ll do a number of things better, like letting software render for an appropriate page size in the printer automatically.

    However, OP is specifically trying to avoid using this route, because he’s concerned about people having trouble with setting it up on their client devices, so he just wants to bypass all that and to have a Web UI where one uploads the document after it’s been rendered to a PDF or similar.


  • Microsoft is simultaneously promising to make Windows 11 run better on 8GB PCs while pushing Windows toward more local AI. If 8GB becomes the norm again, how exactly does Microsoft expect Windows PCs to become the platform for on-device AI?

    From a purely mechanical hardware side, if I’m Microsoft, I’d say that they’d need to get existing computers, mostly laptops, upgraded when memory prices drop. That won’t get you local AI compute immediately, but it’ll be the fastest route to doing so. As things stand:

    • Much memory is soldered to achieve higher throughput.

    • Computer systems generally cannot run memory at different speeds, so the lowest speed stuff bounds the perfoemance of the system. Sticking any slower memory in hurts system perfoemance.

    • People probably will not entirely replace laptops until the whole system ages out, which will take years. If that’s what it requires to move to higher memory systems, it’s going to

    So:

    Stage 1: Get existing laptops upgradeable. “CoPilot+ ready”, say.

    • Get CAMM2 sockets in laptops. Preferably an entirely free slot.

    • Have Windows tell a user when they need an upgrade to use given functionality.

    • Have some mechanism in Windows to direct people to a nearby PC shop or vendor that can do upgrades.

    Stage 2: Get hardware and OS support for non-uniform speed memory. This will take longer.

    • CPUs and motherboards need to be able to handle different memory speeds on different memory chips.

    • Start adding functionality to Windows to heuristically make use of higher-speed memory in systems with multiple speeds.

    Another option: “Local cloud”. This won’t help some users — part of what Microsoft wants to leverage is their control of the local device, versus someone like OpenAI running in the cloud. That means they provide features that need to be always available, even when no other comouting devixes are available.

    But IMHO, there’s also the possibility that some people just don’t want to rely on a remote service. If you have, basically, plug-and-play support for pairing that laptop to a more-capable computer on the network or USB-attached parallel compute node, then that box could do the heavy compute lifting. My suspicion is that laptops are always going to be constrained on parallel compute because of power and heat limitations. So making it easy for Joe User endow them with that capability with an external box, the way he can add printing to his laptop by having a printer attached via USB or on the network…that’s got a lot of long-term potential for heavier compute capability. EGPUs, probably the closest current analog, don’t have phenomenal latency, but current AI compute tasks aren’t particularly latency-sensitive.



  • CUPS didn’t work for me as I can’t see an upload option on the web UI.

    CUPS is really intended as the backend. Whatever software you run will talk to CUPS.

    I’ve never used it, but Savapage appears to be such a frontend.

    EDIT: It may be more elaborate than what you want. It looks like this thing is capable of being set up to run a commercial printing service. It can probably also do what you want, but it’s going to have a lot of functionality that you wouldn’t use if you’re just running an unauthenticated, anyone-can-use-it system.



  • GPU-based imaging

    Sounds like a good idea. The original engine was written for mostly CPU-based processing, and parallel compute has become much more of a thing since then.

    They won’t be able to do everything on a GPU, but they can optimize the system for GPU compute and have graceful fallback for operations that a GPU can’t do.

    considers

    They might also consider adding distributed support. My understanding is that Photoshop is cloud-based these days. I haven’t used Photoshop in decades, never seen the cloud-based product, but if most of the compute happens server-side, I imagine that that’s a lot more amenable to selling higher-end services where you loop more hardware in for more compute capability.

    That’d be an area where they could legitimately bill cloud-based operation as a plus versus local stuff like Gimp.


  • In fairness, it’d have theoretically been possible to predict the 2025 AI boom and start construction on new factories back in 2021, and prediction is one aspect of what an economy does.

    I mean, I didn’t see it, or I’d have bought memory maker stock and/or memory. :-)

    The memory makers got blindsided, as did most of the industry. I don’t think that a command economy would have done better, mind.

    Back during COVID, the memory makers were losing money because nobody wanted the surplus of memory they had, and had started suspending their build-out plans and were contracting rather than expanding:

    https://boisedev.com/news/2022/12/21/micron-workforce-cuts/

    Boise-based Micron Technology said it would cut its workforce by 10% next year while reporting a decline in earnings – swinging to a loss in the latest quarter.

    The technology giant has roughly 48,000 employees around the world, according to its latest SEC filing. The job cuts would come through both voluntary employee departures, as well as layoffs.

    “On December 21, 2022, we announced a restructure plan in response to challenging industry conditions,” the company wrote in a filing with the SEC. “Under the restructure plan, we expect to reduce our headcount by approximately 10% over the rest of the fiscal year 2023, through a combination of voluntary attrition and personnel reductions.”

    “In the last several months, we have seen a dramatic drop in demand,” he said in a statement. He said profitability for the rest of the year will continue to be challenging but could recover later in the fiscal year, which runs through August.

    Anyone who could have predicted the boom could have rolled up and bought up all that excess production. There wouldn’t have been those layoffs, and the person who bought all that supply would have been in possession of a rather valuable cargo as of winter 2025–2026. Could have gone to PNY or someone like that that turns those memory chips into DIMMs and sold them for a bundle.



  • I mean, internal CI and version control systems go down too. Like, if GitHub has substantially worse downtime than an whatever internal system one runs, fair enough.

    Git’s distributed, so downtime isn’t usually a huge deal compared to a non-distributed version control system.

    I think that the largest issue is actually that GitHub provides a centralized commit review system (and, to be fair, so are many internal systems) that one uses to review pull requests. Like, a CI run being deferred usually isn’t a huge deal. Version control is probably distributed these days. But code review is something that you’d like to keep going.

    If you do code review in email or something, it’s distributed. You can keep working. If your email server goes down, it might prevent new messages from reaching other users, but all of the review requests you have can be worked on and any review you’ve already received can be read. But if people are using some centralized Web-based code review system, and that goes down, then that kinda halts a lot of stuff.

    Same centralized problem for issue tracking.

    EDIT: I’ve never used a distributed issue tracker, but apparently they are indeed out there:

    https://github.com/git-bug/git-bug

    EDIT2: A lot of issue trackers involve people attaching large files to issues, so there might be some fundamental scalability issues in that regard for distributed operation; might need to centralize that part. That being said, I’d rather temporarily lose access to just a large-file-hosting server than to that and all of the other issue data.