I’m aware that pine64 sells a smart watch that they encourage flashing your own OS onto. I wonder how hard it’d be to just port the pebble code onto that hardware (a lot harder than I just made it sound, no doubt.) It could be a good way to get a pebble-like experience for people who prefer not to support this guys new company.
Man, I feel you on the affiliate link fluff. I actually ended up unsubscribing from the Popular Mechanics and Popular Science feeds because the signal to noise ratio was so bad.
The creator of Nunti provided a very good primer on the algorithm design here. Basically, you indicate to the app whether you like or dislike an article and then it does some keyword extraction in the background and tries to show you similar articles in the future. I suppose you might be able to dislike a bunch of the fluff and hope the filter picks up on it, but it isn’t really designed to support the kind of rules that would completely purge a certain type of content from your feed.
Most of the feeds I subscribe to came to me in one of two ways:
It can be as simple as just putting an app on your phone. I use feeder which is fine. Pretty bare bones, but in that way it’s easy to learn and use.
I’ve also been meaning to try out an app called Nunti, which I heard about a while ago from this Lemmy post. It claims to be an RSS reader with the added benefit of an (open source and fully local) algorithm to provide some light curation of your feed. It looks interesting, but I haven’t actually tried it out yet because I’m still deciding whether I want any algorithm curating my feed, even one as transparent as Nunti’s. It’s also only available through F-Droid right now, which is a bit of a barrier to entry.
I’ve been trying to solve this problem for a while. I’ve not yet found a really good solution, but I can summarize what I’ve learned, partly for your information but mostly in the hope that Cunningham’s law will finally put me out of my misery. Here are suggestions I’ve seen, organized roughly along some axis of easiest/most popular to hardest/least popular:
As for remotes, there are some decent options on Amazon that connect via bluetooth or a USB dongle and basically act like a mouse and/or keyboard packaged in a remote control form factor. I bought this one a while ago and it’s been fine. Nothing special, but fine. The play/pause/volume buttons on the front read on the receiving end like the media buttons on a keyboard. The air-mouse functionality isn’t for everyone, but this model is one of the few with a little track pad on the back if you prefer using that. Honestly just get anything with a full keyboard. So much easier than using the arrow keys to click-click-click your way through an onscreen keyboard.
I’m just gonna leave this right here: https://shop.m5stack.com/products/m5stack-dial-esp32-s3-smart-rotary-knob-w-1-28-round-touch-screen
I feel the same way about AI as I felt about the older generation of smartphone voice assistants. The error rate remains high enough that i would never trust it to do anything important without double checking its work. For most tasks, the effort that goes into checking and correcting the output is comparable to the effort I would have spent to just do it myself, so I just do it myself.
Remember kids: the only difference between screwing around and science is writing it down.
Actual quote from Adam Savage on an episode of Mythbusters.
For me, probably Big Fat Liar. “Starring” Frankie Muniz and Amanda Bynes, but the real highlight is Paul Giamatti as the villain chewing the absolute shit out of the scenery for an hour and a half as the kids subject his character to a series of increasingly elaborate pranks.
If anyone actually manages to get Plasma Bigscreen working decently, please let me know how you did it. I was really excited when I first learned about it, but after considerable time tinkering, I gave up.
My first attempt was to install it on an old laptop. It boots up and looks good, but a large number of the built-in apps hang forever on their splash screen when you try to run them. I also couldn’t figure out how to customize what apps appear in the carousels on the homepage. I’m not sure if that’s because there truly is no way to do it or if the functionality is locked behind one of the apps that I can’t launch.
The Plasma Bigscreen website indicates that it was designed to run on a Raspberry Pi 4, so I gave in and bought one in hopes that using the preferred hardware would work better. I followed the provided links to the latest Manjaro build of Bigscreen (which is over a year old) and installed it on my pi. Unfortunately, that build apparently suffers from a bug that prevents you from even getting past the login screen on first boot up. I don’t remember the details, but I think it was some kind of “can’t log in without setting a password” / “can’t set a password until you log in” loop. Anyway, I found a forum post discussing the problem with no solutions found, so I gave up on the manjaro build.
My final attempt was to install an ordinary desktop Linux distribution on the pi and then use the package manager to install Plasma Bigscreen as an alternative desktop. This got me in, but there were still a bunch of broken apps. It was about this time that I also realized that the original Bigscreen concept seemed to lean heavily into voice control via Mycroft AI. Mycroft has gone through some major changes since the project launched, and I think these changes have resulted in basically all Mycroft related code in Plasma Bigscreen being broken. That may or may not be related to the other problems I had. I never got to experience a fully functional version of the software, so I have a hard time knowing what exactly is broken in what ways.
Anyway, that’s my experience with Plasma Bigscreen. I hope this doesn’t come across as hating on the project. It should be evident from the amount of effort put in that I really wanted it to work, but in the end I had to conclude that in its current state, it’s badly broken with no sign of improvement or repairs.
If you were actually hoping to buy one but the rounded corners are a dealbreaker, then you may be interested to know that the DIY edition lets you mix and match the older display with the newer motherboards. Looks like opting for the older display even saves you $130 on the purchase price.
I second weawow. It’s got everything I want in a weather app: clean UI, customizable homescreen widget, and you can pick which provider it uses for the weather data.
Out of curiosity, what software is normally being run on your clusters? Based on my reading, it seems like some companies run clusters for business purposes. E.g. an engineering company might use it for structural analysis of their designs, or a pharmaceutical company might simulate the interactions of new drugs. I assume in those cases they’ve bought a license for some kind of high-end software that’s been specifically written to run in a distributed environment. I also found references to some software libraries that are meant to support writing programs in this environment. I assume those are used more by academics who have a very specific question they want to answer (and may not have funding for commercial software) so they write their own code that’s hyper focused on their area of study.
Is that basically how it works, or have I misunderstood?
This actually came up in my research. Folding@Home is considered a “grid computer” According to Wikipedia:
Grid computing is distinguished from … cluster computing in that grid computers have each node set to perform a different task/application. Grid computers also tend to be more heterogeneous and geographically dispersed (thus not physically coupled) than cluster computers.
The primary performance disadvantage is that the various processors and local storage areas do not have high-speed connections. This arrangement is thus well-suited to applications in which multiple parallel computations can take place independently, without the need to communicate intermediate results between processors.
I’ll have to look a little more into the AI stuff. It was actually my first thought, but I wasn’t sure how far I’d get without GPUs. I think they’re pretty much required for Stablediffusion. I’m pretty sure even LLMs are trained on GPUs, but maybe response generation can be done without one.
I’m not sure what you’d want to run in a homelab that would use even 10 machines, but it could be fun to find out.
Oh yeah, this is absolutely a solution in search of a problem. It all started with the discovery that these old (but not ancient, most of them are intel 7th gen) computers were being auctioned off for like $20 a piece. From there I started trying to work backwards towards something I could do with them.
I was looking at HP mini PCs. The ones that were for sale used 7th gen i5s with a 35W TDP. They’re sold with a 65W power brick so presumably the whole system would never draw more than that. I could run a 16 node cluster flat out on a little over a kW, which is within the rating of a single residential circuit breaker. I certainly wouldn’t want to keep it running all the time, but it’s not like I’d have to get my electric system upgraded if I wanted to set one up and run it for a couple of hours as an experiment.
Searx is a search aggregator. It masks your identity from the search providers, but under the hood it’s still just a middle man for google/bing results. I don’t see how this helps if the results themselves are getting worse.
The sample data shared in the article includes
"c": "ES", // Country code,ES is usually used for Spain, so it looks like these tests were run from within the EU.