hedgehog

It’s incredibly compatible. Capitalists want laborers to work hard. It encourages laborers to work hard so they can one day be capitalists themselves.

It also encourages them to vote for politicians who don’t serve them, but politicians, because someday they’ll benefit from their pro-business policies.

The American Dream is capitalist propaganda, not anticapitalist.

The products currently on the marketplace have architectures that are far more sophisticated than just an LLM. Even something as simple as “Deep Research,” which both Anthropic and Claude have available, is using multiple interconnected systems to provide a single response.

Consider Agentic AI, like Claude Code, where they’re using tools, analyzing the results of those tools, iterating, possibly calling out to MCP servers to do other things, etc.. The tools allow them to do things like read or modify files in the working directory, execute programs (i.e., your linter, installing dependencies, running your app), querying against your app itself, and so on.

And of course note that the single “Claude” box in that diagram has an architecture that’s more sophisticated than just being an LLM. At minimum, consumer facing LLMs generally have a supervisor that censors problematic inputs and outputs; this doesn’t make the system more competent but the same concept can be applied to any other sort of transparent wrapper.

It seems to me that we already have consumer systems that are doing what you described, and we’re already working on enhancing their architectures further.

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.