For the usability of the clock, likely nothing.
I did mention In another comment that there are a number of advantages a round clockface provides to the creation of the clock, however.
For the usability of the clock, likely nothing.
I did mention In another comment that there are a number of advantages a round clockface provides to the creation of the clock, however.
Yea that’s kind of what I was thinking when I said eventually handwriting will go the same way.
If people never encounter it and do all their writing on keyboards, it’ll eventually be a useless skill as well.
From a practicality standpoint, a round clockface is easier to create a mechanical drive system for.
You can create a digital mechanical face (see: Flipboard style numerical displays) but they usually require more gears and are more susceptible to wear and tear than the gears of a round clock face.
The simplest designs for mechanical digital displays actually just take 24 hour and 60 minute/second circular displays and hide the other numerals as the clock face spins around. Technically this I suppose counts as both analog and digital?
Example:
As for electronic displays? Nah not much of a reason to use a round display unless again, you have an electric-mechanical drive and want to save on gears and parts.
It floors me just how many people in this thread feel like analog clock reading is a useless/outdated skill.
But I’m of the opinion that there’s no such thing as a truly outdated and useless skill, so I’m not sure I have the capability to empathize with those people…
How so?
I genuinely don’t understand the clock-face-reading-is-a-useless-skill opinion so both seem equally important to me.
There’s nothing stopping an analog clock face from representing 24h time:
I wonder how many people feel this way about writing when everyone just types/texts everything.
You can use nix alongside guix, it’ll just double-up the dependencies on disk:
services (append (list (service nix-service-type))
%base-services)))
Services are, in guix terms, any configuration change to a computer, so creating your own service 99% of the time is just extending etc-service-type
and creating a variable interface to fill in the config file text yourself
Creating a service as in a daemon of some kind uses shepherd and involves extending shepherd-service-type
or home-shepherd-service-type
with your service description, depending on whether the service runs in root or user space.
Shepherd service configurations aren’t actually part of the guix spec(https://www.gnu.org/software/shepherd/manual/shepherd.html#Defining-Services), but still use Guile, so you can interoperate them super easily.
It’s important in guix to understand lisp pretty thoroughly, and knowing how to program lisp is still a very useful skill to have so I’d recommend learning it even if you never touch guix.
I use guix because, while it has a small community, the packaging language is one of the easiest I’ve ever used.
Every distro I’ve tried I’ve always run into having to wait on packages or support from someone else. The package transformation scheme like what nixos has is great but Nixlang sucks ass. Being able to do all that in lisp is much preferred.
Plus I like shepherd much more than any of the other process 0’s
One of the few practical things AI might be good at:
NewPipe can do peertube as well
I’d say mostly energy savings and CPU usage efficiency
Ah, no not the template files for the individual containers, but the project descriptors are just compose files.
They’re 1-1 compose files.
The app just saves them as compose files and then runs docker compose in the backend.
it is EXTREMELY barebones
There’s also Yacht.
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Let them Fight
Yes of course, there’s nothing gestalt about model training, fixed inputs result in fixed outputs
I suppose the importance of the openness of the training data depends on your view of what a model is doing.
If you feel like a model is more like a media file that the model loaders are playing back, where the prompt is more of a type of control over how you access this model then yes I suppose from a trustworthiness aspect there’s not much to the model’s training corpus being open
I see models more in terms of how any other text encoder or serializer would work, if you were, say, manually encoding text. While there is a very low chance of any “malicious code” being executed, the importance is in the fact that you can check the expectations about how your inputs are being encoded against what the provider is telling you.
As an example attack vector, much like with something like a malicious replacement technique for anything, if I were to download a pre-trained model from what I thought was a reputable source, but was man-in-the middled and provided with a maliciously trained model, suddenly the system I was relying on that uses that model is compromised in terms of the expected text output. Obviously that exact problem could be fixed with some has checking but I hope you see that in some cases even that wouldn’t be enough. (Such as malicious “official” providence)
As these models become more prevalent, being able to guarantee integrity will become more and more of an issue.
I think I remember a site like that existing in the 2010s, where you had to apply to join and it only let in equal numbers of genders.
It was the 2010s so the waiting list for dudes joining was way longer than the one for women. It was like trying to get in a dance club.