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Joined 3 years ago
Cake day: June 25th, 2023
  • Smartwatch: Garmin (Fenix 6 gen and above if you want sleep monitoring) with gadgetbridge on android (preferably GrapheneOS) and selfhosted Endurain. Seeing as this is c/Selfhosted you can also roll your own dashboards with Grafana.

    You’re thinking Garmin, really? Privacy? Actually Garmin’s T&Cs are IMO the best of the big names privacy wise, especially if you’re in the EU, but they’re publicly traded and subject to the ‘I have altered the deal, pray I don’t alter it any further’ changing terms at their whim, or just getting bought out and drained dry.

    You know what’s better than OK T&Cs? Not giving them any data at all. On gOS I can pull the network permissions for Garmin Connect and still use it to set up the watch, do custom activities and so forth. When finished disable it and enable GadgetBridge. If you want watch faces do that with Connect IQ and then uninstall. Without gOS it’s just a little clunkier, but GB will pull the files off the watch so that when you fire up Connect there’s not data to report. If you didn’t make an account there’s nowhere for it to go anyway.

    There are other gadgetbridge compatible devices but none with the build quality, feature set and quality health data. It’s been running for GB for more than a year and they haven’t sicced their lawyers on it.

    Also, given their spectacular battery lift (14-20 days or so without hammering music or GPS), 500 charges for the battery to decay takes 10 years+, so secondhand ones are good value. The battery can even be replaced fairly easily (4 screws and a bit of glue), although you might not want to go diving afterwards.

    You can also just connect it via USB and use any software that handles GPX etc. files.

  • You know what’s harder than debugging? Maintenance, especially of someone else’s code, keeping up to date with security exploits, revamping UX etc. which is why github is full of write only (as in never read, never changed) slop projects. That’s a critical part of a software project with any lifespan.

    And then there’s integrating new functionality.

    Without a solid architecture (which AI sucks at), strict code readability standards (ditto, but improving) and nuanced reviewing of potential additions to the codebase (ditto) what you get is a spagettified mess. It ends up costing more to maintain and improve than just starting fresh.

    The promise of the AI bros was that by the time you needed to maintain or extend, you could just get the next version of Claude or whatever to do it, as it’s capabilities would have improved. That was a lie, and LLMs have hit a logarithmic wall where throwing more compute and bigger training sets at it produces diminishing returns. No AGI for you (unless some genius finds a new architecture). Frameworks / harnesses are still improving, but there’s only so far that can go.

    The amount of technical debt that has been racked up by the last two years of AI coding is staggering to contemplate, and the industry will be dealing the fallout for years. Companies will collapse, and god help you if you’ve used it liberally in a codebase as large as an OS - looking at you Microslop.

  • It’s been obvious for a while that scaling has hit diminishing returns (‘let’s voluntarily slow down’ like they can actually go faster) and the ‘just one more datacenter bro’ has stopped working.

    Much smaller models have proven adequate for what the technology does well and the only thing stopping people moving to them wholesale is (probably illegal) market cornering. There is no moat but what they make.

    At least it’s looking like there’s a good chance they won’t get to IPO and steal pension funds and crash economies as badly as they might have. SpaceX actually has worthwhile technology mixed in but xAI still managed to drag it down. Anthropic and OpenAI would go over like a lead balloon now and it’s only going to get worse as they continue to bring nothing new to the table.