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Cake day: June 14th, 2023

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  • (6.9-4.2)/(2024-2018) = 0.45 “version increments” per year.

    4.2/(2018-1991) = 0.15 “version increments” per year.

    So, the pace of version increases in the past 6 years has been around triple the average from the previous 27 years, since Linux’ first release.

    I guess I can see why 6.9 would seem pretty dramatic for long-time Linux users.

    I wonder whether development has actually accelerated, or if this is just a change in the approach to the release/versioning process.



  • You can restrict what gets installed by running your own repos and locking the machines to only use those (either give employees accounts with no sudo access, or have monitoring that alerts when repo configs are changed).

    So once you are in that zone you do need some fast acting reactive tools that keep watch for viruses.

    For anti-malware, I don’t think there are very many agents available to the public that work well on Linux, but they do exist inside big companies that use Linux for their employee environments. For forensics and incident response there is GRR, which has Linux support.

    Canonical may have some offering in this space, but I’m not familiar with their products.




  • rho50@lemmy.nztoTechnology@beehaw.orgBut Claude said tumor!
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    8 months ago

    I don’t think it’s necessarily a bad thing that an AI got it wrong.

    I think the bigger issue is why the AI model got it wrong. It got the diagnosis wrong because it is a language model and is fundamentally not fit for use as a diagnostic tool. Not even a screening/aid tool for physicians.

    There are AI tools designed for medical diagnoses, and those are indeed a major value-add for patients and physicians.



  • Exactly. So the organisations creating and serving these models need to be clearer about the fact that they’re not general purpose intelligence, and are in fact contextual language generators.

    I’ve seen demos of the models used as actual diagnostic aids, and they’re not LLMs (plus require a doctor to verify the result).


  • There are some very impressive AI/ML technologies that are already in use as part of existing medical software systems (think: a model that highlights suspicious areas on an MRI, or even suggests differential diagnoses). Further, other models have been built and demonstrated to perform extremely well on sample datasets.

    Funnily enough, those systems aren’t using language models 🙄

    (There is Google’s Med-PaLM, but I suspect it wasn’t very useful in practice, which is why we haven’t heard anything since the original announcement.)



  • I know of at least one other case in my social network where GPT-4 identified a gas bubble in someone’s large bowel as “likely to be an aggressive malignancy.” Leading to said person fully expecting they’d be dead by July, when in fact they were perfectly healthy.

    These things are not ready for primetime, and certainly not capable of doing the stuff that most people think they are.

    The misinformation is causing real harm.


  • I saw a job posting for Senior Software Engineer position at a large tech company (not Big Tech, but high profile and widely known) which required candidates to have “an excellent academic track record, including in high school.” A lot of these requirements feel deliberately arbitrary, and like an effort to thin the herd rather than filter for good candidates.







  • It’s an interesting idea! I think there are many such applications for federation protocols.

    A few thoughts/questions:

    • Ideally you’ll need a stable identifier for each specific product. Most small online stores I use have product names riddled with typos, so a way to tackle that would be nice.
    • What’s the data model? Would each store be an ActivityPub Actor? Like each one would have a username and publish inventory updates?
    • Where do these updates go (maybe something akin to a Lemmy “community”)?
    • If you’re just relying on stores’ self-reported stock levels, where’s the benefit of using a federated model? Could you just build an open source app that scrapes retailers’ websites and collates that information?
    • Is the eventual goal that this competes with Amazon et al? I.e. it becomes an actual marketplace, perhaps with a “buy” and “sell” Action, and where vendors’ instances are effectively web stores?