Yup, I'm the same way. If I could work in FOSS, I'd be happy to take a pay cut, but FOSS doesn't pay anywhere near good enough. So it'll remain a hobby. As such, I'm pretty reasonable about what needs to be open source, and what's fine being proprietary. For example: OS - must be FOSS games - proprietary is fine, but no privileged access (e.g. kernel level anti-cheat) web browser - must be FOSS web services - proprietary is fine, provided they don't collect a creepy amount of info about me Basically, the more risk there is of a security issue, the more I expect it to be FOSS. And I'm willing to help out too. I've submitted patches to Lemmy and other FOSS projects I use, and I'll donate something similar to what I'd pay for a proprietary app for certain projects.

This video complements the text tutorial at https://trevors-tutorials.com/0004-creating-your-first-game-with-ebitengine/ Trevors-Tutorials.com is where you can find free programming tutorials. The focus is on Go and Ebitengine game development. Watch the channel introduction for more info.

My main concern is that the app isn't open source. I don't trust any software that isn't fully open source.

That has always been the two big problems with AI. Biases in the training, intentional or not, will always bias the output. And AI is incapable of saying "I do not have suffient training on this subject or reliable sources for it to give you a confident answer". It will always give you its best guess, even if it is completely hallucinating much of the data. The only way to identify the hallucinations if it isn't just saying absurd stuff on the face of it, it to do independent research to verify it, at which point you may as well have just researched it yourself in the first place. AI is a tool, and it can be a very powerful tool with the right training and use cases. For example, I use it at a software engineer to help me parse error codes when googling working or to give me code examples for modules I've never used. There is no small number of times it has been completely wrong, but in my particular use case, that is pretty easy to confirm very quickly. The code either works as expected or it doesn't, and code is always tested before releasing it anyway. In research, it is great at helping you find a relevant source for your research across the internet or in a specific database. It is usually very good at summarizing a source for you to get a quick idea about it before diving into dozens of pages. It CAN be good at helping you write your own papers in a LIMITED capacity, such as cleaning up your writing in your writing to make it clearer, correctly formatting your bibliography (with actual sources you provide or at least verify), etc. But you have to remember that it doesn't "know" anything at all. It isn't sentient, intelligent, thoughtful, or any other personification placed on AI. None of the information it gives you is trustworthy without verification. It can and will fabricate entire studies that do not exist even while attributed to real researcher. It can mix in unreliable information with reliable information becuase there is no difference to it. Put simply, it is not a reliable source of information... ever. Make sure you understand that.

I gave you the data, as they say "facts don't care about your feelings."

A private company is selling cheap tablets to inmates to let them communicate with their family. They have to use "digital stamps" to send messages, 35 cents a piece and come in packs of 5, 10 or 20. Each stamp covers up to 20,000 characters or one single image. They also sell songs, at $1.99 a piece, and some people have spent thousands over the years. That's also now just going away. Then you get to the part about the new company. Who already has a system in Tennessee where inmates have to pay 3-5 cents per minute of tablet usage. Be that watching a movie they've bought or just typing a message.

Forgive me for not explaining better. Here are the terms potentially needing explanation. Provisioning in this case is initial system setup, the kind of stuff you would do manually after a fresh install, but usually implies a regimented and repeatable process. Virtual Machine (VM) snapshots are like a save state in a game, and are often used to reset a virtual machine to a particular known-working condition. Preboot Execution Environment (PXE, aka ‘network boot’) is a network adapter feature that lets you boot a physical machine from a hosted network image rather than the usual installation on locally attached storage. It’s probably tucked away in your BIOS settings, but many computers have the feature since it’s a common requirement in commercial deployments. As with the VM snapshot described above, a PXE image is typically a known-working state that resets on each boot. Non-virtualized means not using hardware virtualization, and I meant specifically not running inside a virtual machine. Local-only means without a network or just not booting from a network-hosted image. Telemetry refers to data collecting functionality. Most software has it. Windows has a lot. Telemetry isn’t necessarily bad since it can, for example, help reveal and resolve bugs and usability problems, but it is easily (and has often been) abused by data-hungry corporations like MS, so disabling it is an advisable precaution. MS = Microsoft OSS = Open Source Software Group policies are administrative settings in Windows that control standards (for stuff like security, power management, licensing, file system and settings access, etc.) for user groups on a machine or network. Most users stick with the defaults but you can edit these yourself for a greater degree of control. Docker lets you run software inside “containers” to isolate them from the rest of the environment, exposing and/or virtualizing just the resources they need to run, and Compose is a related tool for defining one or more of these containers, how they interact, etc. To my knowledge there is no one-to-one equivalent for Windows. Obviously, many of these concepts relate to IT work, as are the use-cases I had in mind, but the software is simple enough for the average user if you just pick one of the premade playbooks. (The Atlas playbook is popular among gamers, for example.) Edit: added explanations for docker and telemetry