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Joined 1 year ago
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Cake day: July 10th, 2023

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  • It’s complicated. The main issue is, I live on a remote farm without cell coverage, except in the tiny zone under my 50’ tower with booster.

    However I now have Starlink, and wired and wireless APs covering a large area with high speed, low latency data.

    So, port my number to VoIP.ms, which supports SMS, and make all my calls/texts through Wifi using SIP. On the road, use a basic cell plan with unlimited slow data that is still fast enough for voice. Tested, working, so far fairly simple.

    Now the issues. RCS won’t work with my now VoIP provisioned number, because there’s no SIM for it. The SIM in the phone has a different number, that of the new plan which will be unreachable at the farm by voice/SMS just like the old number used to be.

    This would all be a non-issue if my provider supported VoWifi on anything other than iPhones, but sadly this is not an option. So I’ve got service everywhere now, but am stuck with voice and SMS, no RCS or MMS.




  • Right, we need to come up with better terms for talking about “AI”. Personally at the moment I’m considering any transformer-type ML system to be part of the category, as you stated none of them are any more “intelligent” than any others. They’re all just a big stack of tensor operations. So if one is AI, they all are.

    Remember long ago when “fuzzy logic” was all the hype and considered to be AI? Just a very early form of classifier network but everyone was super excited at the time.


  • I’m just stating that “AI” is a broad field. These lightweight and useful transformer models are a direct product of other AI research.

    I know what you mean, but simply stating “Don’t use AI” isn’t really valid anymore as soon these ML models will be a common component. There are even libraries and hardware acceleration support for tensor operations on the ESP32-S3.


  • It’s possible for local AI models to be very economical on energy, if used for the right tasks.

    For example I’m running RapidOCR which uses a modern transformer architecture, and absolutely blows away traditional OCR at capturing data from character displays.

    Doesn’t even need a GPU and returns results in under a second on a modern CPU. No preprocessing needed, just feed it an image. This little multimodal transformer is just as much “AI” as bloated general purpose GPTs, but it’s cheap, fast and useful.


  • Look at Saskatchewan, Canada. We’re the only province with a public telecom, SaskTel.

    Most people in the cities and even larger towns have fiber, and our cell plans are significantly cheaper than anywhere else in Canada despite being a rural province with a large coverage area to population ratio.

    We also have decent electricity rates considering we have no hydro, and the cheapest natural gas in Canada. Thanks to SaskPower and SaskEnergy.

    Public utilities are the only way to do it, I’m always shocked to see people defend privatization in any way.


  • probably the best optical character recognition by far

    I’ve actually just been working with OCR this week, trying to capture data off of the screen of a stupid proprietary Schneider device as that’s the only way to get at it.

    Long story short Tesseract stinks at this task.

    The Chinese designed PaddleOCR seems significantly superior as it runs a more modern neural net and requires a lot less preprocessing. I would class it as more of a “full service AI” and not just a simple recognition system like Tesseract, it can correct for skew and do its own normalization and thresholding internally while Tesseract wants a perfect boolean raster fed to it.

    Unfortunately, the barrier to entry is a lot higher due to trying to understand their text vomit website and the fact that it seems prone to random segfaulting.







  • evranch@lemmy.catoLinux@lemmy.mlIs DNS Bloat too?
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    6 months ago

    Really annoying is when recent devices don’t respect the DNS you’re advertising or allow configuration (Android…)

    My site is behind CGNAT on IPv4 with recently added fully routed IPv6. There are legacy control devices all over it that don’t speak IPv6, with local DNS records that allow them to be readily accessed while walking around with a mobile device… Allowed them to be accessed that is, until IPv6.

    The Android IPv6 stack ignores the RA for my local DNS and also resolves via v6 by default, forwarding local queries upstream and returning no results. Then it doesn’t bother to fall back to v4. Unrooted Android has no exposed configuration for IPv6 of any sort to modify its behaviour, no hosts file to override or any way I can see to fix this. I can’t even disable IPv6 on my phone.

    So to access my local devices from Android I need to use their full IPv4 address or VPN back into my own network… Oh wait, the stack is so broken that despite setting DNS in Wireguard, it still tries to resolve through upstream v6 first!

    Apparently recent smart TVs are doing similar even on IPv4, hard-coded to 1.1.1.1 or 8.8.8.8 to dodge ad blocking, which is plain malicious and ignores all standards…

    So anyways this is why DNS is dragon #3


  • For free tier, Google Cloud is more transparent about what you get than AWS IMO.

    The only catch is to make sure your persistent disk is “standard” to make it totally free as it defaults to SSD.

    However if you do mess up the disk you’ll still only be paying $1-2/mo. Been using GC for years, and recently they finally started offering dual stack so you can do your own 6to4 tunneling or translation if you want, depends on your usage case.

    AirVPN also are legit and will let you forward ports to expose your local services if you’re worried about DMCA type issues.

    I finally got IPv6 here through Starlink, it’s nice to have full access to the internet again after a decade behind CGNAT




  • We’re talking about replacing lost content here though. And as such you can use the streaming services as a “backup” by re-ripping your whole collection if you lose it.

    I’m actually doing this now as part of a library cleanup. Zotify + beets are a great combo to pull down vast quantities of music and properly sort and tag it.

    Then I stream it to my phone in my truck using ampache and ultrasonic, which does have a local buffering option.

    However if you have some exotics that you ripped from rare discs, demos or prerelease, live recordings with sentimental value etc. I would suggest keeping those properly backed up. I don’t have many of these, but the ones I do have are backed up both cloud and offsite.