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  • 21 comments
Joined 1 year ago
Cake day: June 8th, 2025
  • While SO is toxic, it’s mostly about the failure of the supplicant to do the fucking research (RTFM or equivalent these days goddammit, and is usually backed by ppl with actual knowledge, Chat GPT / LLMs., not so much.

  • Eh, Syncthing-Fork is basically feature complete, it’s not even a significant exploit threat (on gOS and constrained to local network and storage spaces in my case, but probably in general). I just pinned it at v2.0.11.2 in F-Droid and will wait for things to shake out. If things go badly there’ll be a Syncthing-Fork-Fork, it’s too critical to too many peoples workflows.

  • Zeroth, consider GrapheneOS on that Pixel.

    First, Syncthing on the PC and Syncthing-Fork. Now you can sync (and anything else) your photo files from phone to PC and vice versa. Congrats, you have photo storage backup.

    Second, either a vpn to your home network so you can backup on the road, or Immich (as elsewhere suggested) for your own google photos experience.

    Third, whichever of second you didn’t choose.

    Fourth, get ye an offsite backup (search 3-2-1 backup). rclone is your friend, but encrypt first locally with Cryptomator, then you don’t have to trust your storage provider.

  • but I wish podlet could handle translating external networks. Right now, it just fails, and needs manual intervention. Also, afaik, there’s no way to preserve comments when translating.

    Yeah, valid, it always needs an eye on the output, but it gets you at least 90+% of the way, often 100%.

    I like that the syntax is systemd derived, YMMV I guess.

  • Podman is great, but I only found it useful after learning quadlets and how to use podlet to generate quadlets (or quadlet pods) from dockerfiles. Now all my containers run with nice systemd commands in rootless podman containers instead of rooted dockerfiles (coz docker requires root unless you jump through hoops, when I started you couldn’t). Quadlet syntax is so much cleaner than docker too.

  • Sure, I was doing genome compression for tree comparison in the late 90s for in memory analysis and the speed up was very significant. The idea of a universal specification format and a universal decoder is IMO bloody brilliant, hell with a bit of training I’d be unsurprised if you could point a LLM at a format and get 90+% of the way there with the specification for most simple-ish formats, and probably have a manual crack at simple relational databases. Potentially you could also switch out huffman for encryption for efficient zero-knowledge proofs as well.

  • It’s PCIe 4.0 :(

    Boo! Silly me thinking DDR5 implied PCIe5, what a shame.

    Feels like they’re testing the waters with Halo, hopefully a loud ‘waters great, dive in’ signal gets through and we get something a bit fitter for desktop use, maybe with more memory (and bandwidth) next gen. Still, gotta love the power usage, makes for one hell of a NAS / AI inference server (and inference isn’t that fussy about PCIe bandwidth, hell eGPU works fine as long as the model / expert fits in VRAM.