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'm going to say that every layoff has a cover story. The goal, reduce the workforce make/save money, is really the only justification needed. Everything else is PR, and an attempt to stay out of legal hot water.

I wish I could create playlists on Nebula.

the package managers for linux that i know of are great because you can easily control everything they do

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

Sure. Efficiency isn't everything, though. At the end of the article there are a few people to get you started. Then you can go to your favorites in that list, and follow some of the people THEY are following. Rinse and repeat, follow boosted folks. You'll have 100 souls in no time.