OnlyOffice is available on Android already.

“any linux app” - I don’t think any nontechnical users want GParted on their Android phones, and it wouldn’t work anyway.

Android has its own games, same as iOS. Nontechnical users are way more likely to want Windows games than Linux games anyway.

Wine used to be developed natively for Android but they stopped a few years back. You can still download it at winehq though. I think Box64 with wine is a decent option?

Overall the thing I’m confused about is why you think Google or any major Android phone manufacturer have a motivation to make native Linux apps more accessible. Google certainly doesn’t want to make it easier for you to use the better versions of their competitors’ apps. Google is moving further away from Linux, not closer. Providing a usable, good enough desktop experience that’s still Android underneath makes far more sense for them.

Fortunately, like I said earlier, there are workarounds to get access to those Linux apps.

The thing that is more likely to change is for the creators of Android apps to build apps that function better when used in a phone-as-desktop format. And even if they don’t, there are enough competent web apps out there that just being able to use your browser full screen on a monitor solves 90% of people’s actual use cases - and probably over 95% when you include the other apps that have decent desktop experiences that can be run alongside them.

The Steam Deck approach is much closer to what you seem to want. The Steam Deck is an actually competent Linux machine that has a Valve-supported compatibility layer in Proton for running non-Linux games. It plugs into a USB-C hub connected to a monitor, mouse, and keyboard just fine, can install any Linux app, etc… It’s completely usable handheld as well. But it isn’t a phone, and even though it’s quite portable, it’s not “stick into your pocket” portable.

I don’t expect a major manufacturer to make a Linux phone any time soon, and I don’t think the Linux phones that are out already have - or will have in the next 5 years - a smooth enough experience to convince any nontechnical user to switch.

There are mobile versions for all of those?

What are the gaps in functionality for nontechnical people? And “apps that exist on Linux but not Android” doesn’t count, because such people are unlikely to have ever even used a Linux desktop in the first place. The improvement that matters won’t be Linux apps; it’ll be Android apps that are more usable in desktop mode.

That said, what are the issues with the apps that are currently available?

If a user installed Chrome, an office suite (whether that be Google Docs, Sheets, and Slides, the Microsoft equivalent, or something else), an email client, and other commonly available apps, what tasks would they be unable to complete, if any?

Are these, or other commonly used apps, substantially less usable than on desktop? If so, how so?

Can’t you just use GNURoot Debian and XServer SDL to get a Linux desktop env on any Android phone?

There’s an xda-developers guide on this and the two apps are still in the Google Play Store, so I assume it’s still feasible.

I’m not sure how well it plays with DeX and other similar solutions, though.

That’s assuming the apps aren’t capable enough to handle being used on a desktop on their own, of course. What sorts of gaps did you see, and in which sorts of apps?

From the article:

The court documents don’t indicate that any rare books were destroyed in this process—Anthropic purchased its books in bulk from major retailers

This is already a thing

Samsung DeX was the first big one but there are a bunch of competing ones that do similar things now.

One thing Ubuntu users should know is that the change will only provide performance boosts when GPUs are handling workloads running the OpenCL framework or the OneAPI Level Zerointerface. That likely means that people using games and similar apps will see no benefit.

Did he implement two different variations? OP said he used two different tools, not that his solutions were any different.

That said… how so?

There are many different ways two different brute force approaches might vary.

A naive search and a search with optimizations that narrow the search area (e.g., because certain criteria are known and thus don’t need to be iterated over) can both be brute force solutions.

You could also just change the search order to get a different variation. In this case, we have customer, price, meat, cheese, and we need to build a combination of those to get our solution; the way you construct that can also vary.

The comparison to your SO’s approach is a bit sloppy. He didn’t reason out a solution himself; he wrote a program to solve the puzzle.

How do you define “reasoning?” Maybe your definition is different than mine. My experience is that there is a certain amount of reasoning going on, even with non-reasoning LLMs. Being able to answer “What is the capital of the state that has Houston in it?” for example, is something I would classify as very basic reasoning. And now, LLM-powered chat bots are much more capable.

All that “reasoning” or “thinking” really is, though, is a way to get additional semantic connections in place without:

• giving an answer in the wrong format
• filling up context with noise

There are limits to how well reasoning these char bots can reason. One of those limits is specifically related to the context size. As the context becomes larger, the model’s capabilities become worse. By asking it to show all its work, you exacerbated that weakness.

That still doesn’t mean LLM-powered chat bots can’t reason, just that there are limits.

I used to do puzzle books with these sorts of problems when I was younger, and they always came with multiple sets of grids with row and column labels filled out to facilitate the elimination approach. I don’t know that most people would think “Hey, it would be helpful to build a grid for each way of setting up these constraints.” One grid, sure, but I don’t think one grid is sufficient for this sort of problem.

I don’t think I am - or that most people are, for that matter - capable of reasoning through all of the necessary steps in my head and aloud, without use of, at minimum, pencil and paper. I hope you wouldn’t say that I and most people aren’t capable of reasoning as a result.

I just asked Claude Opus 4 (with extended thinking and analysis tools enabled) “Given the freedom to use any tools of your choice, design an approach to solve this problem. Feel free to use any tools that are necessary, including writing code in a language of your choice.” followed by pasting your problem text. It wrote and ran some code to solve it, gave me an answer that violated constraint 7, and when I pointed that out, ran some more code and gave me a correct solution on its second attempt.

You are absolutely correct. I apologize for the error. Let me revise the solution to ensure constraint 7 is satisfied.​​​​​​​​​​​​​​​​

Thank you for catching that error. Here is the corrected solution that satisfies all nineteen constraints:

Final Solution:

The key correction was recognizing that since ham cannot be paired with swiss cheese (constraint 7), and Henrietta must have swiss cheese based on the process of elimination, Henrietta cannot have ham. Through careful analysis of the remaining constraints, I determined that Carol has ham with her colby jack cheese, which satisfies all requirements.

This solution demonstrates the importance of thorough verification when solving complex constraint satisfaction problems. Even when a solution appears complete, each constraint must be individually validated to ensure accuracy.​​​​​​​​​​​​​​​​

This all took 5-10 minutes - and most of that time was spent verifying its solutions - so a third of the time your SO took.

LLMs, even those with image analysis abilities, are lacking when it comes to spatial awareness, so your critique regarding using a grid to implement a systematic elimination approach is valid.

What’s been stopping them?

A big part of the reason that Republicans are more able to pass legislation is that smaller states have a larger impact than they should, based on their populations.

Each state has a number of members in the House of Representatives in proportion to their population - 52 for California. Each state has two members in the Senate, so CA has the same amount of power in the Senate as Wyoming, which has a population of under 600k to CA’s 39 million.

Beyond the impact on Congress, the sum of those counts determines the number of electoral votes a state has in presidential elections. So California has 54 electoral college votes.

If California split up into 12 different states, each would end up with 6 electoral votes. The total count in the House would decrease from 52 to 48, and some other state would get the remaining 4 (though even that could be avoided by just having some sub-states be large enough to get 5 Representatives) but the total count of Senators would increase from 2 to 24 and the total electoral vote count would increase from 54 to 72.

Many of the smallest US states are firmly red, which means Republicans don’t need as much popular support to make policy changes. This would help reverse that. Heck, if California went all the way and split into 65 states, each with the population of Wyoming, they’d end up with 195 electoral college votes.

I feel like the US would take over California again if that was the case.

I’m not sure how you think the US would take over CA again, or what the impact would be, if it continued to be part of the US and just split into several different states. Could you elaborate?

I’d much rather California split into 12 different states, each with roughly the population of Nevada.

No offense taken, but thanks for the comment! If someone was offended and they saw your comment, I think it would probably help

I thought it was like the way one’s brain is wired that causes them to have slightly different perception than the rest.

I’m no expert, either, but this is a solid explanation IMO. It’s why autistic people are prone to sensory overload; their brains don’t filter out noise (like the hum of the refrigerator, the sounds of people chewing, or background conversations) the way that most allistic people’s brains do. It also definitely could have been the reason, or at least contributed to, why the woman from your post was confused - particularly if she was trying to figure out why allistic people did something.

Sorry, that’s incorrect.

Autism is commonly comorbid with mental health disorders (aka “mental illnesses”) like anxiety, depression, ADHD, etc., as well as with intellectual developmental disorders, but autism is still considered, at worst, a neurodevelopmental disorder, regardless of where an individual falls on the spectrum.

Both the DSM-V and ICD-11 are in agreement about this, for what that’s worth, but you could also just do a search for “Is autism a mental illness?” on Duckduckgo, Kagi, Searx, Bing, Google, or whatever, if you want to confirm.

The lady was autistic if I remember collectly. She had a boyfriend who also had a mental ilness.

Autism isn’t a mental illness.

OP is also in the allegedly ultra rare camp of “successfully configured Jellyfin and lived to tell the tale.” Not what I’d expect of someone unable to configure Plex correctly. I’ve not set up a Plex server myself but my guess is it wasn’t clear that it was misconfigured - it did work previously, after all.

If they’re calling it remote streaming when you’re on the same (local) network, that’s not exactly intuitive. I’d say OP’s phrasing was fair.

You got the idea!

We’re in c/showerthoughts. “What if my grandma was a bike?” would fit right in

To be clear, I agree that the line you quoted is almost assuredly incorrect. If they changed it to “thousands of deepfake apps powered by open source technology” then I’d still be dubious, simply because it seems weird that there would be thousands of unique apps that all do the same thing, but that would at least be plausible. Most likely they misread something like https://techxplore.com/news/2025-05-downloadable-deepfake-image-generators.html and thought “model variant” (which in this context, explicitly generally means LoRA) and just jumped too hard on the “everything is an open source app” bandwagon.

I did some research - browsing https://github.com/topics/deepfakes (which has 153 total repos listed, many of which are focused on deepfake detection), searching DDG, clicking through to related apps from Github repos, etc…

In terms of actual open source deepfake apps, let’s assume that “app” means, at minimum, a piece of software you can run locally, assuming you have access to arbitrary consumer-targeted hardware - generally at least an Nvidia desktop GPU - and including it regardless of whether you have to write custom code to use it (so long as the code is included), use the CLI, hit an API, use a GUI app, a web browser, or a phone app. Considering only apps that have as a primary use case, the capability to create deepfakes by face swapping videos, there are nonetheless several:

• Roop
• Roop Unleashed
• Rope
• Rope Live
• VisoMaster
• DeepFaceLab
• DeepFaceLive
• Reactor UI
• inswapper
• REFace
• Refacer
• Faceswap
• deepfakes_faceswap
• SimSwap

If you included forks of all those repos, then you’d definitely get into the thousands.

If you count video generation applications that can imitate people using, at minimum, Img2Img and 1 Lora OR 2 Loras, then these would be included as well:

• Wan2GP
• HunyuanVideoGP
• FramePack Studio
• FramePack eichi

And if you count the tools that integrate those, then these probably all count:

• ComfyUI
• Invoke AI
• SwarmUI
• SDNext
• Automatic1111 SD WebUI
• Fooocus
• SD WebUI Forge
• MetaStable
• EasyDiffusion
• StabilityMatrix
• MochiDiffusion

If the potential criminals use easier ready-made (commercial) web-services instead of buying a RTX 5090, learning ComfyUI, dealing with the steep learning curve etc, we’d know we have to primarily fight those apps and services, not necessarily the generative AI tools.

This is the part where, to be able to answer that, someone would need to go and actually test out the deepfake apps and compare their outputs. I know that they get used for deepfakes because I’ve seen the outputs, but as far as I know, every single major platform - e.g., Kling, Veo, Runway, Sora - has safeguards in place to prevent nudity and sexual content. I’d be very surprised if they were being used en masse for this.

In terms of the SaaS apps used by people seeking to create nonconsensual, sexually explicit deepfakes… my guess is those are actually not really part of the figure that’s being referenced in this article. It really seems like they’re talking about doing video gen with LoRAs rather than doing face swaps.