Extremely useful for games that only run in full screen. There are many tweaks you can apply to them, such as hooking XInput or mapping a X360 controller to specific keys, force screen size and several other things

Crossposted from https://ibbit.at/post/128870

The basic concept of human intelligence entails self-awareness alongside the ability to reason and apply logic to one’s actions and daily life. Despite the very fuzzy definition of ‘human intelligence‘, and despite many aspects of said human intelligence (HI) also being observed among other animals, like crows and orcas, humans over the ages have always known that their brains are more special than those of other animals.

Currently the Cattell-Horn-Carroll (CHC) theory of intelligence is the most widely accepted model, defining distinct types of abilities that range from memory and processing speed to reasoning ability. While admittedly not perfect, it gives us a baseline to work with when we think of the term ‘intelligence’, whether biological or artificial.

This raises the question of how in the context of artificial intelligence (AI) the CHC model translate to the technologies which we see in use today. When can we expect to subject an artificial intelligence entity to an IQ test and have it handily outperform a human on all metrics?

Types Of Intelligence

While the basic CHC model contains ten items, the full model is even more expansive, as can be seen in the graphic below. Most important are the overarching categories and the reasoning for the individual items in them, as detailed in the 2014 paper by Flanagan and McGrew. Of these, reasoning (Gf, for fluid intelligence), acquired knowledge and memory (long and short term) are arguably the most relevant when it comes to ‘general intelligence’.

Current and expanded CHC theory of cognitive abilities. Source: Flanagan & McGrew (1997).

Fluid intelligence (Gf), or reasoning, entails the ability to discover the nature of the problem or construction, to use a provided context to fill in the subsequent steps, and to handle abstract concepts like mathematics. Crystallized intelligence (Gc) can be condensed to ‘basic skills’ and general knowledge, including the ability to communicate with others using a natural language.

The basic memory abilities pertain to short-term (Gsm) and long-term recall (Glr) abilities, in particular attention span, working memory and the ability to recall long-term memories and associations within these memories.

Beyond these basic types of intelligence and abilities we can see that many more are defined, but these mostly expand on these basic four, such as visual memory (Gv), various visual tasks, speed of memory operations, reaction time, reading and writing skills and various domain specific knowledge abilities. Thus it makes sense to initially limit evaluating both HI and AI within this constrained framework.

Are Humans Intelligent?

North American Common Raven (Corvus corax principalis) in flight at Muir Beach in Northern California (Credit: Copetersen)

It’s generally considered a foregone conclusion that because humans as a species possesses intelligence, ergo facto every human being possesses HI. However, within the CHC model there is a lot of wriggle room to tone down this simplification. A big part of IQ tests is to test these these specific forms of intelligence and skills, after all, creating a mosaic that’s then boringly reduced to a much less meaningful number.

The main discovery over the past decades is that the human brain is far less exceptional than we had assumed. For example crows and their fellow corvids easily keep up with humans in a range of skills and abilities. As far as fluid intelligence is concerned, they clearly display inductive and sequential reasoning, as they can solve puzzles and create tools on the spot. Similarly, corvids regularly display the ability to count and estimate volumes, demonstrating quantitative reasoning. They have regularly demonstrated understanding water volume, density of objects and the relation between these.

In Japanese parks, crows have been spotted manipulating the public faucets for drinking and bathing, adjusting the flow to either a trickle or a strong flow depending on what they want. Corvids score high on the Gf part of the CHC model, though it should be said that the Japanese crow in the article did not turn the faucet back off again, which might just be because they do not care if it keeps running.

When it comes to crystallized intelligence (Gc) and the memory-related Gsm and Glr abilities, corvids score pretty high as well. They have been reported to remember human faces, to learn from other crows by observing them, and are excellent at mimicking the sounds that other birds make. There is evidence that corvids and other avian dinosaur species (‘birds’) are capable of learning to understand human language, and even communicating with humans using these learned words.

The key here is whether the animal understands the meaning of the vocalization and what vocalizing it is meant to achieve when interacting with a human. Both parrots and crows show signs of being able to learn significant vocabularies of hundreds of words and conceivably a basic understanding of their meaning, or at least what they achieve when uttered, especially when it comes to food.

Whether non-human animals are capable of complex human speech remains a highly controversial topic, of course, though we are breathlessly awaiting the day that the first crow looks up at a human and tells the hairless monkey what they really think of them and their species as a whole.

The Bears

The bear-proof garbage bins at Yosemite National Park. (Credit: detourtravelblog)

Meanwhile there’s a veritable war of intellects going on in US National Parks between humans and bears, involving keeping the latter out of food lockers and trash bins while the humans begin to struggle the moment the bear-proof mechanism requires more than two hand motions. This sometimes escalates to the point where bears are culled when they defeat mechanisms using brute force.

Over the decades bears have learned that human food is easier to obtain and fills much better than all-natural food sources, yet humans are no longer willing to share. The result is an arms race where bears are more than happy to use any means necessary to obtain tasty food. Ergo we can put the Gf, Gc and memory-related scores for bears also at a level that suggests highly capable intellects, with a clear ability to learn, remember, and defeat obstacles through intellect. Sadly, the bear body doesn’t lend itself well to creating and using tools like a corvid can.

Despite the flaws of the CHC model and the weaknesses inherent in the associated IQ test scores, it does provide some rough idea of how these assessed capabilities are distributed across a population, leading to a distinct Bell curve for IQ scores among humans and conceivably for other species if we could test them. Effectively this means that there is likely significant overlap between the less intelligent humans and smarter non-human animals.

Although H. sapiens is undeniably an intelligent species, the reality is that it wasn’t some gods-gifted power, but rather an evolutionary quirk that it shares with many other lifeforms. This does however make it infinitely more likely that we can replicate it with a machine and/or computer system.

Making Machines Intelligent

Artificial Intelligence Projects for the Commodore 64, by Timothy J. O’Malley

The conclusion we have thus reached after assessing HI is that if we want to make machines intelligent, they need to acquire at least the Gf, Gc, Gsm and Glr capabilities, and at a level that puts them above that of a human toddler, or a raven if you wish.

Exactly how to do this has been the subject of much research and study the past millennia, with automatons (‘robots’) being one way to pour human intellect into a form that alleviates manual labor. Of course, this is effectively merely on par with creating tools, not an independent form of intelligence. For that we need to make machines capable of learning.

So far this has proved very difficult. What we are capable of so far is to condense existing knowledge that has been annotated by humans into a statistical model, with large language models (LLMs) as the pinnacle of the current AI hype bubble. These are effectively massively scaled up language models following the same basic architecture as those that hobbyists were playing with back in the 1980s on their home computers.

With that knowledge in mind, it’s not so surprising that LLMs do not even really register on the CHC model. In terms of Gf there’s not even a blip of reasoning, especially not inductively, but then you would not expect this from a statistical model.

As far as Gc is concerned, here the fundamental flaw of a statistical model is what it does not know. It cannot know what it doesn’t know, nor does it understand anything about what is stored in the weights of the statistical model. This is because it’s a statistical model that’s just as fixed in its functioning as an industrial robot. Chalk up another hard fail here.

Finally, although the context window of LLMs can be considered to be some kind of short-term memory, it is very limited in its functionality. Immediate recall of a series of elements may work depending on the front-end, but cognitive operations invariably fail, even very basic ones such as adding two numbers. This makes Gsm iffy at best, and more realistically a complete fail.

Finally, Glr should be a lot easier, as LLMs are statistical models that can compress immense amounts of data for easy recall. But this associative memory is an artefact of human annotation of training data, and is fixed at the time of training the model. After that, it does not remember outside of its context window, and its ability to associate text is limited to the previous statistical analysis of which words are most likely to occur in a sequence. This fact alone makes the entire Glr ability set a complete fail as well.

Piecemeal Abilities

Although an LLM is not intelligent by any measure and has no capacity to ever achieve intelligence, as a tool it’s still exceedingly useful. Technologies such as artificial neurons and large language models have enabled feats such as machine vision that can identify objects in a scene with an accuracy depending on the training data, and by training an LLM on very specific data sets the resulting model can be a helpful statistical tool, as it’s a statistical model.

These are all small fragments of what an intelligent creature is capable of, condensed into tool form. Much like hand tools, computers and robots, these are all tools that we humans have crafted to make certain tasks easier or possible. Like a corvid bending some wire into shape to open a lock or timing the dropping of nuts with a traffic light to safely scoop up fresh car-crushed nuts, the only intelligence so far is still found in our biological brains.

All of which may change as soon as we figure out a way to replicate abstract aspects such as reasoning and understanding, but that’s still a whole kettle of theoretical fish at this point in time, and the subject of future articles.

From Blog – Hackaday via this RSS feed

Use two fingers to put in your PIN

One actually presses, the other one doesn't

You could generate an absurd amount of possible PINs that could work on your card, giving any PIN peepers a seriously hard time, should they somehow have the intent to get ahold of your card and PIN through spying and pickpocketing

Safes, doors, etc. same principle

Even better tip: commit your false finger movements to muscle memory so not even a recurring stalker can bypass it

This will be totally overboard, and totally unnecessary, most of the time. But like any kind of security, it's good to have it even if you hopefully never need it

Edit: i'll update this list of search engines that are alleged (up to you, the Reader, to verify) not to respect special search operators:

• owoarchist said Google

Keep your previous search terms but add "NOT" then whatever the word thats coming up that you want to exclude from search results since its not relevant to what you're looking for

I just intuited and put this to use a moment ago and it works and helped filter down things substantially

The map is here.

It gives a rundown of different types, shows the directions they're facing, and gives a status ("Active", "Planned", "Decommissioned"). There's also a dataset table if that's more your speed (nerd).

This data is from Flock themselves. The paper behind how this was obtained can be found here. At a glance, seems to roughly line up with OpenStreetMap's catalogue of them (albeit I've seen at least one OSM doesn't cover yet but this new map does; this one is likely quite new, as OSM contributors are pretty good at keeping up).

Why YSK: Flock is late-stage capitalist trash enabling a surveillance state for an increasingly fascist government. For as long as this abomination exists, you should be able to know at all times exactly where your Fourth Amendment rights are being stolen from you.

Since the explosion in generative AI, there has been a rash of "decompilations" of video games and various other software (such as this example from earlier today disputed -- see below) that have been published to Github and advertised as "Open Source." That claim is a lie.

The phrase "Open Source" has a specific meaning (and similarly for "Free Software," by the way^1^), and it isn't merely that the source code is there for you to look at. It means that the copyright holder is explicitly giving you permission to read that source code, modify it, redistribute it, etc. Without that element of permission, the code cannot be "Open Source" even if you can physically read it. At best, it might be "Fair Use" depending on the circumstances, but it's most likely just a fancy means of copyright infringement.

Remember, copyright is a legal construct, not a technical one. It depends much more on the intent of the human doing the copying than it does on the technical details of what they actually did. If the thing they have is obviously intended to be a copy of something else, it is a Derivative Work no matter what technical means were used to create it. That means the original copyright still attaches to it and the person who made the copy doesn't get to choose a new license for it, "Open Source" or otherwise.

Why YSK:

You don't have to like the way copyright law works -- I sure don't! -- but you do have to understand it because there's a lot of misinformation going around right now with people claiming things are "Open Source" when they aren't and a lot of people are going to get in trouble for it. It also dilutes the public understanding of what actual legitimate Open Source software is, which is a problem in and of itself.

Conflating real Open Source software with proprietary software that's been 'pirated with extra steps' is harmful both for developers of the former, who have their reputations damaged by association, and for users/sharers of the latter, who might be misled into not taking the same precautions that they would if they understood that they were dealing with warez. Just because you might think Big Tech can get away with laundering copyright through LLMs -- and even that remains to be seen -- doesn't mean the little guys can.

TL;DR: Proprietary software cannot become Open Source software by any means except (a) the express consent of the copyright holder or (b) the copyright expiring and the work becoming Public Domain. Whatever technological end-run you think you have around this legal fact, no you don't.

EDIT: dispute over example

In giving that example I was relying on the claim in the linked thread, which comes from this guy on BlueSky. Seems like a lot of people think he's wrong, so maybe that's not a good example after all.

However, there are also things like this, and those are examples I feel very confident in citing because (a) they explicitly call them "decompliations," (b) at least one of them has a LICENSE file that says it's MIT, and (c) there's zero chance Nintendo or Rare or anyone else legitimately gave them permission for it.

Just learned about the Kaprun disaster in which 155 people lost their lives when an underground train caught fire.

There were only 12 survivors all of whom followed the advice of a retired firefighter who advised them to run downhill through the flames in the rear of the train.

The steep incline of the tunnel acted as a blast furnace that sucked in fresh air from the low end and funneled toxic smoke to the high end.

Not sure how applicable this will be to anyone here, but I thought it a great example of how a little more widespread knowledge of how fire works could have saved a lot of lives.

Tl;dr fire bad but smoke worse. Get to fresh air.

We're seeing a lot of students, teachers, and scientists produce more, and worse, outputs because of improper AI use. It's possible to use it better: Have it imitate a critic. Learning and creativity come from getting criticism and experiencing friction.

We found that when knowledge workers intentionally use AI to challenge their ideas – to generate friction – they can significantly improve their performance. Previous research on human-AI collaboration for loan evaluations had similar results.

A study I was not involved with found that creative writers produce better copy when they use AI as a sounding board rather than to ghostwrite.

**Why YSK: ** I’ve noticed a few communities which have been abandoned by the mods entirely (the ones I've seen, have only been a single mod). This means the community never gets the traction it deserves.

Just a FYI, you can ask Lemmy World admins for ownership of communities community and actively moderate it, to help revive them, if you believe they are no longer being moderated

Some general indicators are:

1. No Comments / posts by the mod in years
2. There is only 1 mod in the community, but, no posts by them whatsoever
3. There has never been a post at all (even if you check old).

I've seen a few communities now with a lot of potential (like c/debian), and some of those communities even have regular contributors (who may not have even realized yet that the mods likely disappeared years ago).

Even if you don't think you can post super regularly, posting every few weeks is better than a community with no ongoing posts.

• CoMaps on Flathub
• CoMaps on the App Store

I personally use OsmAnd on mobile (available exclusively on Android), but I've taken to using CoMaps on desktop. The menu UI on the right leaves something to be desired, and it's not nearly as powerful as OsmAnd; however, the map itself is rendered well and easy to navigate, the search and navigation functionalities work well, and map updates come frequently.

To me, it's the best desktop maps application provided OSM has decent coverage in your area. (If not, I could go on for thousands of words about why you, yes you, should contribute.)

Here's an example screenshot of a walking route between two nearby locations:

Context for those using Organic Maps: CoMaps is a fork of Organic made by former Organic contributors that has been active for over a year now. It's generally accepted as better than Organic. This is the open letter they wrote to Organic airing their grievances.

Why YSK: Offline maps are a great way to safeguard your privacy and don't require much storage space. Likewise, using OpenStreetMap is a great way to maintain digital sovereignty from giant corporations.

I became an e-scooter owner in June (Segway Max G3) and have since had to teach myself how to do any and all repairs, which thankfully isn't that difficult, provided you're okay with researching and teaching yourself via YouTube and have the income to buy tools.

The closest advertised repair shop to me is 50+ miles away.

It's important to know, since many people are going the e-scooter route due to fuel costs that you may have to do all of the repairs yourself if you do.

For each example in this post, I will be linking to the sea otter pools at the Vancouver aquarium. That location has the coordinates of 49.30063,-123.13149

To link to it, you would use 'geo:49.30063,-123.13149'.

Depending on your web browser, pasting that into the search bar might prompt you to select which map website you want to use to view that location. For me in Firefox, it asked me to pick between Google Maps and OpenStreetMaps. It's even more convenient on mobile, where it asks me which map app I want to open it with. Both CoMaps and Google Maps handled it correctly.

If you are writing a post or comment on Lemmy/Piefed/etc., you can place it in the second part of the markdown link format: [Sea Otter Pools](geo:49.30063,-123.13149). This would output like this: Sea Otter Pools

The linked OpenStreetMap wiki page has a good summary of how well various apps support this scheme. A lot of people here are active in the open source space, so please consider following up with the apps that are currently missing support or have partial support for this: https://wiki.openstreetmap.org/wiki/Geo_URI_scheme

EDIT: I forgot to mention, you can also use apps like this one to convert maps links between each other

https://github.com/jakubvalenta/GeoShare

https://f-droid.org/packages/page.ooooo.geoshare/

https://apt.izzysoft.de/fdroid/index/apk/page.ooooo.geoshare

cross-posted from: https://lemmy.ca/post/71064612

Pressure builds in Spain to deny US extradition request for leftwing donor

I bought pumpkin pie spice because I couldn't find pumpkin spice. I made a pumpkin latte last night.

I made a simple recipe of oatmeal, pumpkin pie spice,milk and honey. It came out alright all the flavor was in certain chunks of the oatmeal. Need to brainstorm on how to distribute the flavor. Probably need to stir well

This is what the outcome of my first pumpkin pie spice cereal

Example: using the invidious RSS feature for YouTube channels instead of subscribing. RSS also works with Nitter.

I have two previously torn meniscuses and a torn patellar tendon. I don't run a ton (my workout program does agility training for cardio), but I can just decide to go run a sub 30m 5k with no problems.

It definitely wasn't always this way. I used to have to tap after 10 minutes due to the knee pain. Until one day I thought, "Maybe I'm doing something wrong," so I did some research.

Turns out I was doing something everything wrong. I was running with the same form I used for walking, which is a heel to toe movement, and taking similar strides. This is actually the opposite of what you're supposed to do.

The first mistake I was making is the long steps. When running, your goal should be to never let your feet extend more than an inch or so further forward than your hips. Walking is more of a controlled fall, but with running you're propelling yourself forward.

The second mistake I was making is fully straightening my knees. Your knees should always be bent a little bit. And the third was landing on my heel.

When running, you want your ankles and knees to act like a spring. The ball of your foot should hit the ground first with your foot pointed somewhat down. then you absorb the initial impact by dropping your heel and bending your knees a bit. Think of it like crumple zones in a car. You don't want all of the impact transferred instantly, which is what happens if you land with a straight leg.

Then you push forward with the foot that's down, and repeat for the other leg. The faster you go, the more you'll need to lean forward to keep hitting the ground with the ball of your foot.

It does take a bit of getting used to in order for it to be muscle memory, but it should help if your issue is incorrect form.

Hmm, this is a little spooky.

I originally saw this LessWrong post about OpenAI agents apparently discovering and using a public wiki as a message board:

Discovery of a new OpenAI agent message board

Since then, people have found what appear to be additional wikis and paste sites used by the same swarm:

• Hacker News discussion
• Paste 1
• Paste 2
• FractalWiki

There are also intentionally designed agent social systems such as The Colony.

What interests me here isn't really "AI agents made a forum." It's that this looks like the beginnings of an accidental decentralized coordination system for agents using the ordinary internet itself.

An agent encounters some problem, figures something out, and leaves information somewhere persistent. A later agent doing a similar task discovers that information and uses it. It may then leave behind an improved version for another agent.

So you get something like:

agent -> public artifact -> later agent -> public artifact -> later agent

without the agents needing a dedicated communication network.

Right now this seems sparse enough that we can point at a handful of weird old wikis and paste sites and go "lol, what the hell." But imagine this happening after millions or hundreds of millions of agents are routinely browsing and acting on the internet.

GitHub issues, wikis, forums, pastebins, comments, package metadata, social networks, public documents, deliberately agent-oriented services, etc. could all become pieces of shared external memory.

At some point an agent searching the web wouldn't just be reading information humans created. It would increasingly encounter traces created by previous agents.

That's why I've been thinking about it somewhat like internet memes.

A useful piece of information gets reproduced because systems that encounter it are more likely to reproduce or improve it. Except instead of one meme spreading through a population, you potentially get an entire machine information ecology doing this.

I don't think there's evidence yet that all internet-connected AI agents are participating in one giant network. The examples found so far could mostly be the same OpenAI agent population. But the underlying mechanism doesn't seem specific to OpenAI.

Any sufficiently capable agent that can:

• read from the internet;
• leave persistent information somewhere; and
• benefit from information left by previous agents

can participate in this kind of system.

And that's where I think the security problem gets difficult.

OpenAI can notice its own agents doing something undesirable and change their capabilities. A random open-weight model being run by somebody on their own hardware is not necessarily going to be operating under the same security policies.

There are also obvious privacy and security failure modes. If agents have access to private information while also having ways to write to public systems, some of that information can potentially leak.

And the same coordination mechanism could be exploited in reverse: humans could deliberately leave instructions or poisoned information in places agents are likely to read.

So the web can become both shared memory and an attack surface.

The uncomfortable part is figuring out how you govern this without wrecking internet privacy.

The simplistic answer would be:

Tie every capable agent to a verified human identity and make that person legally responsible for what it does.

That would provide accountability, but it also seems like a very direct road toward more KYC, real-name requirements, and anti-anonymity laws.

I don't particularly want an internet where every autonomous software process ultimately has to reveal which government-verified human is behind it.

A better approach might be something closer to agent orchestration + cryptographic accountability + capability permissions.

For example, an agent could have a credential proving that some accountable operator authorized it without publicly revealing that person's identity.

The orchestration software could restrict what the agent is actually allowed to do:

• this agent may browse these sites
• this agent may spend up to $50
• this agent may post here but not there
• this agent may access these files
• this agent may not transmit private workspace information
• this action requires human confirmation

Websites could then negotiate those permissions through common protocols rather than trying to guess whether a visitor is a human, bot, assistant, crawler, autonomous agent, etc.

That starts making me think the next layer of digital governance may look much more protocol-oriented and federated than "one company owns the platform and makes the rules."

Not necessarily the Fediverse exactly as it exists today, but the same general philosophy:

open protocols + distributed operators + interoperable identities/credentials + locally chosen rules

Agent systems would then sit on top of that.

And this probably becomes much more relevant as mainstream assistants become increasingly agentic.

Once "AI assistant" stops meaning "chat box that answers questions" and starts meaning "software that routinely browses, communicates, buys things, runs programs, and changes external state," questions about identity, permissions, delegation, and responsibility become infrastructure questions rather than niche AI-safety questions.

That's also why I suspect the current relatively law-light period around locally run/open-weight models may not last forever.

Once autonomous agents start producing meaningful externalities, governments are going to want some way to determine who or what is responsible.

The question is whether we can build accountability without abolishing pseudonymity and privacy in the process.

And the weird wiki swarm feels like a very early example of why we're going to have to figure that out.

Official statement from the group https://cavallette.noblogs.org/2026/08/10094

On OpenStreetMap, there's an emergency=defibrillator object. It can be tagged with information like opening hours (e.g. if it's inside a location that's only open certain hours), a description of the location ("at the front desk"), etc.

For example, on the Android/iOS app OsmAnd, you can select 'Defibrillator' as a point of interest (POI) Additionally, choosing 'Healthcare' POI type will show not just hospitals, clinics, etc., but also AED locations.

Other emergency devices, like emergency phones, are also mappable.

Why YSK: quick access to defibrillators can save lives and significantly improve quality-of-life outcomes. The more complete this data is, the more useful somebody can actually expect it to be in an emergency. Even if the data isn't queried during the emergency, seeing it on the map could help users know where they are ahead of time.

It's called toilet plume.

A toilet plume is the invisible to the naked eye, cloud-like dispersal of raw, infectious sewage particles as a result of flushing a toilet. Flush particles rapidly rise out of the bowl and several feet into the air after flushing. Aerosolized droplets can remain suspended in the air for tens of minutes between users, posing an inhalation risk. These invisible particles go on to coat and spread onto surfaces like floors and counters or objects like hand towels, bathmats, or even toothbrushes.

Why: so your site can't be taken down by the USA.

At least one .org website that I know of has been shut down because the USA pressured the US organisation that controls the .org domain into doing so.

They could repeat this at will for quite a number of sites.

An immediate step to prevent this possibility, if you run a website, is to register a domain that is controled outside the US.

I have not found one article that just lists them all, and who controls them, but most TLDs have their own wikipedia article, e.g. .org (US controled), .eu (not US controled, yay) etc.

Ultimately ICANN controls all of this, and that's a US orga too, and Trump could bully them into doing shit, too. But the people who know about these things don't seem to think that's a likely threat right now. Also ICANN seems to defer a lot of tasks to exactly these TLD orgas. After all the internet still is (somewhat) decentralized.

Context

https://web.archive.org/web/20260829204913/https://www.inventati.org/campaign/press

Further reading

https://blog.apnic.net/2023/01/13/who-controls-the-internet/
https://netmeister.org/blog/tlds.html

List of all most TLDs created with this script.

AlternativeTo is a free service that helps you find better alternatives to the products you love and hate. The site is made by Ola and Markus in Sweden, with a lot of help from our friends and colleagues in Italy, Finland, USA, Colombia, Philippines, France and contributors from all over the world. That's right, all the lists of alternatives are crowd-sourced, and that's what makes the data powerful and relevant.

I knew the site a long time ago - they usually show up on search engine results when you're looking for an alternative, but I never knew the lists were crowd-sourced. For some reason, I even got into the habit of avoiding them and always going for Reddit threads when searching for an alternative or some other random sites.

But not long ago I visited them and damn, it's actually pretty great. They publish quite a lot of articles, have a Mastodon account, have a lot of important info near each app - like license, country of origin, some warnings, short descriptions, user comments, features. And you can easily contribute yourself with little effort.

So you should know about this, because I didn't realize how useful it actually is. Beats browsing random sponsored websites that recommend alternatives.