Wow, there isn’t a single solution in here with the obvious answer?

You’ll need a domain name. It doesn’t need to be paid - you can use DuckDNS. Note that whoever hosts your DNS needs to support dynamic DNS. I use Cloudflare for this for free (not their other services) even though I bought my domains from Namecheap.

Then, you can either set up Let’s Encrypt on device and have it generate certs in a location Jellyfin knows about (not sure what this entails exactly, as I don’t use this approach) or you can do what I do:

1. Set up a reverse proxy - I use Traefik but there are a few other solid options - and configure it to use Let’s Encrypt and your domain name.
2. Your reverse proxy should have ports 443 and 80 exposed, but should upgrade http requests to https.
3. Add Jellyfin as a service and route in your reverse proxy’s config.

On your router, forward port 443 to the outbound secure port from your PI (which for simplicity’s sake should also be port 443). You likely also need to forward port 80 in order to verify Let’s Encrypt.

If you want to use Jellyfin while on your network and your router doesn’t support NAT loopback requests, then you can use the server’s IP address and expose Jellyfin’s HTTP ports (e.g., 8080) - just make sure to not forward those ports from the router. You’ll have local unencrypted transfers if you do this, though.

Make sure you have secure passwords in Jellyfin. Note that you are vulnerable to a Jellyfin or Traefik vulnerability if one is found, so make sure to keep your software updated.

If you use Docker, I can share some config info with you on how to set this all up with Traefik, Jellyfin, and a dynamic dns services all up with docker-compose services.

Look up “LLM quantization.” The idea is that each parameter is a number; by default they use 16 bits of precision, but if you scale them into smaller sizes, you use less space and have less precision, but you still have the same parameters. There’s not much quality loss going from 16 bits to 8, but it gets more noticeable as you get lower and lower. (That said, there’s are ternary bit models being trained from scratch that use 1.58 bits per parameter and are allegedly just as good as fp16 models of the same parameter count.)

If you’re using a 4-bit quantization, then you need about half that number in VRAM. Q4_K_M is better than Q4, but also a bit larger. Ollama generally defaults to Q4_K_M. If you can handle a higher quantization, Q6_K is generally best. If you can’t quite fit it, Q5_K_M is generally better than any other option, followed by Q5_K_S.

For example, Llama3.3 70B, which has 70.6 billion parameters, has the following sizes for some of its quantizations:

• q4_K_M (the default): 43 GB
• fp16: 141 GB
• q8: 75 GB
• q6_K: 58 GB
• q5_k_m: 50 GB
• q4: 40 GB
• q3_K_M: 34 GB
• q2_K: 26 GB

This is why I run a lot of Q4_K_M 70B models on two 3090s.

Generally speaking, there’s not a perceptible quality drop going to Q6_K from 8 bit quantization (though I have heard this is less true with MoE models). Below Q6, there’s a bit of a drop between it and 5 and then 4, but the model’s still decent. Below 4-bit quantizations you can generally get better results from a smaller parameter model at a higher quantization.

TheBloke on Huggingface has a lot of GGUF quantization repos, and most, if not all of them, have a blurb about the different quantization types and which are recommended. When Ollama.com doesn’t have a model I want, I’m generally able to find one there.

I recommend a used 3090, as that has 24 GB of VRAM and generally can be found for $800ish or less (at least when I last checked, in February). It’s much cheaper than a 4090 and while admittedly more expensive than the inexpensive 24GB Nvidia Tesla card (the P40?) it also has much better performance and CUDA support.

I have dual 3090s so my performance won’t translate directly to what a single GPU would get, but it’s pretty easy to find stats on 3090 performance.

The above post says it has support for Ollama, so I don’t think this is the case… but the instructions in the Readme do make it seem like it’s dependent on OpenAI.

Are you saying that NAT isn’t effectively a firewall or that a NAT firewall isn’t effectively a firewall?

Is there a way to use symlinks instead? I’d think it would be possible, even with Docker - it would just require the torrent directory to be mounted read-only in the same location in every Docker container that had symlinks to files on it.

Depending on setup this can be true with Jellyfin, too. I have a domain registered, use dynamic DNS, and have Traefik direct a subdomain to my Jellyfin server. My mobile clients are configured using that. My local clients use the local static IP.

If my internet goes down, my mobile clients can’t connect, even on the LAN.

On the other hand it is a conduit for censorship. If an admin doesn’t like what you post on another instance, then they can censor you everywhere.

Such a user can

• Create an account on a different instance
• Spin up their own instance

OP: “Zen 5 CPU”

You: “Unpatched Zen 1 through Zen 4 CPUs are vulnerable”

You: Is it vulnerable?

???

PSN had 129 million MAU in December 2024. Source. That’s less than Steam had in 2021 - 132 million MAU. Source.

Across all platforms, including Xbox and PC, Microsoft reported 500 million MAU in the fiscal quarter ending June 2024. Source.

Under notes, where you said my name, did you mean “Hedgedoc?”

It doesn’t read like AI to me, but their takeaways about copyright made me think the author had read an AI summary rather than the actual source material.

They didn’t say it was a Linux problem; they said it was a mobile problem

It’s okay, the author of the article didn’t actually read (or understand) the Copyright Office’s recommendations. They are:

Based on an analysis of copyright law and policy, informed by the many thoughtful comments in response to our NOI, the Office makes the following conclusions and recommendations:

• Questions of copyrightability and AI can be resolved pursuant to existing law, without the need for legislative change.
• The use of AI tools to assist rather than stand in for human creativity does not affect the availability of copyright protection for the output.
• Copyright protects the original expression in a work created by a human author, even if the work also includes AI-generated material.
• Copyright does not extend to purely AI-generated material, or material where there is insufficient human control over the expressive elements.
• Whether human contributions to AI-generated outputs are sufficient to constitute authorship must be analyzed on a case-by-case basis.
• Based on the functioning of current generally available technology, prompts do not alone provide sufficient control.
• Human authors are entitled to copyright in their works of authorship that are perceptible in AI-generated outputs, as well as the creative selection, coordination, or arrangement of material in the outputs, or creative modifications of the outputs.
• The case has not been made for additional copyright or sui generis protection for AI- generated content.

Pretty much everything the article’s author stated is contradicted by the above.

local docker hub proxy

Do you mean a Docker container registry? If so, here are a couple options:

• Use the official Docker registry: https://www.docker.com/blog/how-to-use-your-own-registry-2/
• Self-host forgejo or gitea and use the included package registry, which is automatically enabled. Details: https://forgejo.org/docs/latest/user/packages/

Every system in an RPG should be designed and tailored to max the possible immersion you can get from the game.

Having to deal with inventory management doesn’t always improve immersion. Inventory optimization doesn’t immerse me; rather, it gives me a puzzle to solve.

Giphy has a documented API that you could use. There have been bulk downloaders, but I didn’t see any that had recent activity. However you still might be able to use one to model your own script after, like https://github.com/jcpsimmons/giphy-stacks

There were downloaders for Gfycat - gallery-dl supported it at one point - but it’s down now. However you might be able to find collections that other people downloaded and are now hosting. You could also use the Internet Archive - they have tools and APIs documented

There’s a Tenor mass downloader that uses the Tenor API and an API key that you provide.

Imgur has GIFs is supported by gallery-dl, so that’s an option.

Also, read over https://github.com/simon987/awesome-datahoarding - there may be something useful for you there.

In terms of hosting, it would depend on my user base and if I want users to be able to upload GIFs, too. If it was just my close friends, then Immich would probably be fine, but if we had people I didn’t know directly using it, I’d want a more refined solution.

There’s Gifable, which is pretty focused, but looks like it has a pretty small following. I haven’t used it myself to see how suitable it is. If you self-host it (or something else that uses S3), note that you can use MinIO or LocalStack for the S3 container rather than using AWS directly. I’m using MinIO as part of my stack now, though for a completely different app.

MediaCMS is another option. Less focused on GIFs but more actively developed, and intended to be used for this sort of purpose.

Both devices have integrated memory, so that 16 GB will look more like a 11/5, 12/4, or maybe even 14/2 split. The Steam Deck is also $400 for an LCD model or $550 for the OLED, not $800. It’s reasonable to expect more performance when you pay more.

Because the Steam Deck has a lower native resolution, that means that less of the RAM will be used for the integrated GPU. Downscaling from 1080p to 720p doesn’t look good, either - and you could downscale to 540p if supported, but if you need to do that (vs choosing to for an emulated game) it probably won’t be pretty, either.

This device is also running Windows, rather than a streamlined Linux-based launcher, meaning that more of that RAM will be taken up by OS processes by default.

The article talks about how the 8840U benefits from more, fast RAM. You won’t get near the 8840U’s full potential gaming with 16 GB. 24 GB, on the other hand, would have been enough that games expecting 16 GB of system RAM would have been able to get it, even while devoting 6-7 GB to the GPU and 1-2 GB to the OS.

As it is, you only see new comments if you scroll past the post again (and your client has refreshed it) or if you open it directly. If your client hasn’t updated the comment count or if you refresh your feed and the post falls off, you’ll never see it anyway.

A “Watch” feature would solve this better. If you watch a post, you get aggregated notifications for edits and comments on the post. If you watch a comment, you get aggregated notifications for replies to it or any of its children.

By aggregated notifications, I mean that you’d get one notification that said “The post you watched has been edited; 5 new comments” rather than a notification for each new comment.

Then, in addition to exposing a “Watch” action on posts and comments, clients could also enable users to automatically hide posts that are watched, either by marking them as hidden or by hiding watched posts without updates.

If the latter approach were taken, notifications might not even be necessary - the post could just get added back into the user’s feed when changes were made. It would result in a similar experience to forums, where new activity in a topic would bump it to the front, but it would only impact the people who were watching it.

You can kinda get that behavior by sorting your feed by Active, but this could be used with other sorting methods.

No, game mechanics aren’t subject to copyright law. Game mechanics can be patented in the US, so long as they’re unique and nonobvious (to someone with ordinary skill in the field).

Monopoly and Magic: The Gathering both had patents on their mechanics, for example.

And of course, patents in Japan are a completely different animal than patents in the US.