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:

1. I enjoyed reading an article posted somewhere else (Lemmy, etc.) so I sought out the feed of that publisher.
2. Sometimes news outlets enter into agreements to republish each others articles. When they do this, the re-publisher will usually include a little blurb at the end giving credit to the original publisher. If a feed I’m already subscribed to has an article re-published from elsewhere then I click through and check out the original source to see if I want to follow them as well.

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 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.

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.

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.

Are there any viable alternative sites you’re aware of?

I’m a big fan of upgradable hardware, but lately I’ve found that the bigger problem with Android phones is the lack of software support. I had my last phone for 5 years and finally upgraded not because there were any major hardware problems, but because the android version was so far out of date that I was starting to feel the pain of missing out on some major improvements, plus some apps actually were starting to break. I picked my current phone specifically because Samsung was promising to support four major version upgrades which is, unfortunately, industry leading among Android OEMs despite lagging hugely behind Apple’s software support for their older models.

Fairphone seems to have a mixed track record on this. According to their website the Fairphone 2 got 5 major updates (great!). But the Fairphone 3 got only one update (bad). And the fairphone 4 has received one update so far with a second one promised. After that they say that they’ll try to provide two more updates, but they’re not making any promises because the processor will be out of support with Qualcomm by then.

This is, unfortunately, a very understandable position to take. The fact that Android OEMs rely on third parties like Qualcomm to design and support their processors is definitely the major problem here. Big guys like Samsung and Google can throw their weight around and squeeze a year or two of extra support out. But for small players like fairphone it’s not surprising that they find themselves in this position.

The fact is that any sane company would prefer to make money selling new chips, rather than spending it to support old ones. This problem will persist until consumers start demanding longer software support on their devices and making it a major part of their buying decision.