The Memory Police - Yōko Ogawa

It’s interesting, I still don’t know what to think of it. I put it down a few months ago and picked it up again, planning to finish it. Any readers around? What did you think?

i for one can’t be bothered to remember, for example, the syntax to add a new gitlab project to the allowed list of a hashicorp vault policy :) - i use zsh with fzf and ag, so i ctrl+r to find the last time i used this, adjust, execute.

there are many use cases for checking out your shell’s command history…

This is what I do. Shared folder via NFS, mounted inside the VM (fstab), added to the volumes of the docker container in the compose file…

Ctrl+R

adevăr, măria ta!

Client availability is valid. I use an android tv, that’s been easy for me. There are mobile clients for every phone and tablet.

• I don’t know what smart collections are, but I do get automatic collections for franchises (like all “28 x later”) via a plugin. I don’t have playlists, but I guess I never felt the need for one… What would you use them for, binge watching franchises?
• skip intro and credits is a thing, built in since a few versions (used to be a plugin)
• the UI is subjective, and I don’t know any other one… I personally like how it looks, I customized quite a bit, easy to do via CSS.

I’ve never used Plex. What are some of the features that you’re missing in Jellyfin? Genuinely curious.

Emma Finestone is the curator for this 2.6 milion year stone tools collection :)

It’s really popular in the server world, and it’s the foundation of many other distros, maybe that’s why?

Parable of the Sower, Octavia E. Butler.

It started a bit slow, but it’s really picking up.

Some more info, like some error messages or logs would help people help you.

Also, stick with one distro while troubleshooting, and start by giving us the distro used, kernel, nvidia drivers, steam, wine and proton versions / variants, other packages used…

When you switched distro, did you do a full clean install for everything, including steam?

No Bias, No Bull AI I’ve spent my career grappling with bias. As an executive at Meta overseeing news and fact-checking, I saw how algorithms and AI systems shape what billions of people see and believe. As a journalist at CNN, I even hosted a show briefly called “No Bias, No Bull”(easier said than done, as it turned out). Trump’s executive order on “woke AI” has reignited debate around bias and AI. The implication was clear: AI systems aren’t just tools, they’re new media institutions, and the people behind them can shape public opinion as much as any newsroom ever did. But for me, the real concern isn’t whether AI skews left or right, it’s seeing my teenagers use AI for everything from homework to news without ever questioning where the information comes from. Political bias misses the deeper issue: transparency. We rarely see which sources shaped an answer, and when links do appear, most people ignore them. An AI answer about the economy, healthcare, or politics, sounds authoritative. Even when sources are provided, they’re often just footnotes while the AI presents itself as the expert. Users trust the AI’s synthesis without engaging sources, whether the material came from a peer-reviewed study or a Reddit thread. And the stakes are rising. News-focused interactions with ChatGPT surged 212% between January 2024 and May 2025, while 69% of news searches now end without clicking to the original claiming neutrality while harboring clear bias. We’re making the same mistake with AI, accepting its conclusions without understanding their origins or how sources shaped the final answer. The solution isn’t eliminating bias (impossible), but making it visible. Restoring trust requires acknowledging everyone has perspective, and pretending otherwise destroys credibility. AI offers a chance to rebuild trust through transparency, not by claiming neutrality, but by showing its work. What if AI didn’t just provide sources as afterthoughts, but made them central to every response, both what they say and how they differ: “A 2024 MIT study funded by the National Science Foundation…” or “How a Wall Street economist, a labor union researcher, and a Fed official each interpret the numbers…”. Even this basic sourcing adds essential context. Some models have made progress on attribution, but we need audit trails that show us where the words came from, and how they shaped the answer. When anyone can sound authoritative, radical transparency isn’t just ethical, it’s the principle that should guide how we build these tools. What would make you click on AI sources instead of just trusting the summary? Full transparency: I’m developing a project focused precisely on this challenge– building transparency and attribution into AI-generated content. Love your thoughts.

- Campbell Brown.

That looks really unmaintained, the last update was yeas ago. I wouldn’t just run random shell scripts from the Internet without understanding what they do first.

Here’s a pretty decent Wiki to get you started with the *arr ecosystem: https://wiki.servarr.com/

My “servers” are headless, in the basement, so even if I’m home, it’s still remote :D

It’s always good to read the docs, but I often skip them myself :)

They have this nifty tool called pve8to9 that you could run before upgrading, to check if everything is healthy.

I have a 3 node cluster, so I usually migrate my VMs to a different node and do my maintenance then, with minimal risks.

From Proxmox themselves: https://www.proxmox.com/en/about/company-details/press-releases/proxmox-virtual-environment-9-0

That sounds oh so familiar:)

Having 30+ people over for her birthday was horrifying, but I was in the kitchen most of the time, with the occasional person dropping by…

Luckily it wasn’t a dinner party but a buffet & fire pit outside situation. I even came out after dark, to sit by the fire with her and a few people that stayed late :D

Thanks for that! ☺️ That’s some helpful info.

Thanks, I appreciate that!