This is an interesting parallel, but I feel like I missed some key part of it.

In the US, at least, we historically killed off a lot of deer’s natural predators - mostly wolves - and as a result, the deer population can get out of control, causing serious problems to the ecosystem. Hunters help to remedy that. The relatively small violences that they perform on an individual basis add up to improving the overall ecosystem.

That isn’t the same as being a bigot, or a sexist, or a fascist… and I don’t know why anyone would assume that a person holds those views because they’re mean and petty. They hold those views for a variety of reasons - sometimes because they’re a child or barely an adult and that’s just what they learned, and they either don’t know any better or haven’t cared enough to think it through; sometimes because they’ve been conditioned to think that way; sometimes because they’re sociopaths who recognize that it’s easier to oppress that particular group.

It doesn’t really matter what their reason is. Either way, they’re a worse person because of it, and often they’re overall a bad person, regardless of the rest of their views, actions, and contributions.

Being a hunter, by contrast, is neutral leaning positive.

It makes sense that a rational person who loves being in nature, who loves animals, who wants their local ecosystem to be successful, would as a result want to help out in some small way, even if that means they have to kill an animal to do so. It doesn’t make sense that a rational person who loves all people, who wants their local communities to be successful, would as a result want to oppress and harm the people in already marginalized groups.

I don’t think equating being bigoted with holding unjustifiable opinions does it justice. The way we use the word opinion generally applies to things that are trivial or unimportant, that don’t ultimately matter, e.g., likes and dislikes. Being a bigot is a viewpoint; it shapes you. For many bigots, their entire perspective is warped and wrong. And there’s a common misunderstanding that you can’t argue with someone’s opinions; because it’s just how they “feel.” But being a bigot, whether you’re sexist, racist, transphobic, queerphobic, homophobic, biphobic, etc., is a belief, and it’s one that, in most cases, the bigot chooses (consciously or not) to keep believing.

If an adult with functioning cognitive abilities refuses to question their bigoted beliefs, then they’ve made a choice to be a bigot.

Assuming you’re using ollama (is there another reason to use ollama.com?), you can use compatible files from huggingface directly in ollama. The model page will give you the instructions for the command to run; I always change ollama run to ollama pull , though. Instructions: https://huggingface.co/docs/hub/ollama

You should be able to fit Qwen3 32B at Q4_K_M with an acceptable context, and it did very well on math benchmarks (with thinking enabled). You can disable thinking by including /no_think at the end of your prompt to speed up responses, but I’m not sure how well it handles math under those circumstances. I wouldn’t even consider disabling thinking unless you were grading one question per prompt.

The ollama Qwen3 page is https://ollama.com/library/qwen3:32b and the default 32B quant is Q4_K_M. I personally am using the Q6_K quant by unsloth, and their quants have been great (when supported by ollama), often being the first to fix bugs impacting other quantizations.

I’m not sure if Q4_K_M is the optimal quant style for Intel Arc, but the others that might be better are not supported by ollama, anyway, as far as I know.

Qwen3’s real world knowledge is bad, so if there are questions that rely on that you may need to include the relevant facts as part of the prompt or use an ollama frontend that supports web searches.

Other options: This does seem like something Gemma3 27B would be good at, so it’s too bad you can’t use it. Older Gemmas may be good, but I’m not sure. Llama3.3 70B is also out, unless you have a decent amount of system RAM and are okay with offloading less than half to GPU. I could see it outperforming my recommendation below but I would be very surprised for the 8B version to outperform it. Older Qwen2.5 is decent at math but unless you grab QwQ doesn’t include thinking.

I’d just like to interject for a moment. What you’re referring to as Alpine Linux Alpine Linux is in fact Pine’s fork, Alpine / Alpine Linux Pine Linux, or as I’ve taken to calling it, Pine’s Alpine plus Alpine Linux Pine Linux. Alpine Linux Pine Linux is an operating system unto itself, and Pine’s Alpine fork is another free component of a fully functioning Alpine Linux Pine Linux system.

According to https://www.nextdiffusion.ai/blogs/hidream-the-new-top-open-source-image-generator it’s an uncensored image generation model developed by Vivago. In the benchmarks they highlighted - DPG-Bench, GenEval, and HPSv2.1 - it was ranked number 1. It’s said to be very good at following complex prompts.

Retrieval-Augmented Generation (RAG) is probably the tech you’d want. It basically involves a knowledge library being built from the documents you upload, which is then indexed when you ask questions.

NotebookLM by Google is an off the shelf tool that is specialized in this, but you can upload documents to ChatGPT, Copilot, Claude, etc., and get the same benefit.

If you self hosted, Open WebUI with Ollama supports this, but far from the only one.

Most anti-car people are in favor of improving public transit options.

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.

Why should we know this?

Not watching that video for a number of reasons, namely that ten seconds in they hadn’t said anything of substance, their first claim was incorrect (Amazon does not prohibit use of gen ai in books, nor do they require its use be disclosed to the public, no matter how much you might wish it did), and there was nothing in the description of substance, which in instances like this generally means the video will largely be devoid of substance.

What books is the Math Sorcerer selling? Are they the ones on Amazon linked from their page? Are they selling all of those or just promoting most of them?

Why do we think they were generated with AI?

When you say “generated with AI,” what do you mean?

• Generated entirely with AI, without even editing? Then why do they have so many 5 star reviews?
• Generated with AI and then heavily edited?
• Written partly by hand with some pieces written by unedited GenAI?
• Written partly by hand with some pieces written by edited GenAI?
• AI was used for ideation?
• AI was used during editing? E.g., Grammarly?
• GenAI was used during editing?E.g., “ChatGPT, review this chapter and give me any feedback. If sections need rewritten go ahead and take a first pass.”
• AI might have been used, but we don’t know for sure, and the issue is that some passages just “read like AI?”

And what’s the result? Are the books misleading in some way? That’s the most legitimate actual concern I can think of (I’m sure the people screaming that AI isn’t fair use would disagree, but if that’s the concern, settle it in court).

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.

You said, and I quote “Find a better way.” I don’t agree with your premise - this is the better way - but I gave you a straightforward, reasonable way to achieve something important to you… and now you’re saying that “This is a discussion of principle.”

You’ve just proven that it doesn’t take a moderator to turn a conversation into a bad joke - you can do it on your own.

It’s a discussion of principle.

This is a foreign concept?

It appears to be a foreign concept for you.

I don’t believe that it’s a fundamentally bad thing to converse in moderated spaces; you do. You say “giving somebody the power to arbitrarily censor and modify our conversation is a fundamentally bad thing” like it’s a fact, indicating you believe this, but you’ve been given the tools to avoid giving others the power to moderate your conversation and you have chosen not to use them. This means that you are saying “I have chosen to do a thing that I believe is fundamentally bad.” Why would anyone trust such a person?

For that matter, is this even a discussion? People clearly don’t agree with you and you haven’t explained your reasoning. If a moderator’s actions are logged and visible to users, and users have the choice of engaging under the purview of a moderator or moving elsewhere, what’s the problem?

It is deeply bad that…

Why?

Yes, I know, trolls, etc…

In other words, “let me ignore valid arguments for why moderation is needed.”

But such action turns any conversation into a bad joke.

It doesn’t.

And anybody who trusts a moderator is a fool.

In places where moderator’s actions are unlogged and they’re not accountable to the community, sure - and that’s true on mainstream social media. Here, moderators are performing a service for the benefit of the community.

Have you never heard the phrase “Trust, but verify?”

Find a better way.

This is the better way.

Then why are you doing that, and why aren’t you at least hosting your own instance?

Yes, I know, trolls etc. But such action turns any conversation into a bad joke. And anybody who trusts a moderator is a fool.

Not just trolls - there’s much worse content out there, some of which can get you sent to jail in most (all?) jurisdictions.

And even ignoring that, many users like their communities to remain focused on a given topic. Moderation allows this to happen without requiring a vetting process prior to posting. Maybe you don’t want that, but most users do.

Find a better way.

Here’s an option: you can code a fork or client that automatically parses the modlog, finds comments and posts that have been removed, and makes them visible in your feed. You could even implement the ability to reply by hosting replies on a different instance or community.

For you and anyone who uses your fork, it’ll be as though they were never removed.

Do you have issues with the above approach?

As a user, you can:

• Review instance and community rules prior to participating
• Review the moderator logs to confirm that moderation activities have been in line with the rules
• If you notice a discrepancy, e.g., over-moderation, you can hold the mods accountable and draw attention to it or simply choose not to engage in that instance or community
• Host your own instance
• Create communities in an existing instance or your own instance

If you host your own instance and communities within that instance, then at that point, you have full control, right? Other instances can de-federate from yours.

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.

That sounds like something someone who’s never heard of gerrymandering or voter suppression would say.

From https://www.yalemedicine.org/news/covid-vaccines-reduce-long-covid-risk-new-study-shows

At the pandemic’s onset, approximately 10% of people who suffered COVID-19 infections went on to develop Long COVID. Now, the risk of getting Long COVID has dropped to about 3.5% among vaccinated people (primary series).

…

Then, the team conducted analyses to uncover the reasons for the observed decline in Long COVID cases from the pre-Delta to Omicron eras. About 70% of the decline was attributable to vaccination, they found.

To be clear, I’m measuring the relative humidity of the air in the drybox at room temp (72 degrees Fahrenheit / 22 degrees Celsius), not of the filament directly. You can use a hygrometer to do this. I mostly use the hygrometer that comes bundled with my dryboxes (I use the PolyDryer and have several extra PolyDryer Boxes, but there are much cheaper options available) but you can buy a hygrometer for a few bucks or get a bluetooth / wifi / connected one for $15-$20 or so.

If you put filament into a sealed box, it’ll generally - depending on the material - end up in equilibrium with the air. So the measurement you get right away will just show the humidity of the room, but if the filament and desiccant are both dry, it’ll drop; if the desiccant is dry and the filament is wet, it’ll still drop, but not as low.

Note also that what counts as “wet” varies by material. For example, from what I’ve read, PLA can absorb up to 1% or so of its mass as moisture, PETG up to 0.2%, Nylon up to 7-8%… silica gel desiccant beads up to 40%. So when I say they’ll be in equilibrium, I’m referring to the percentage of what that material is capable of absorbing. It isn’t a linear relationship as far as I know, but if it were, that would mean that: if the humidity of the air is 10% and the max moisture the material could retain is 1%, then the material is currently retaining 0.1% moisture by mass. If my room’s humidity is kept at 40%, it’ll absorb moisture until it’s at 0.4% moisture by mass.

That said, this doesn’t measure it perfectly, since while most filament materials absorb moisture from the air when the humidity is higher, they don’t release it as easily. Heating it both allows the air to hold more moisture and allows the filament (and desiccant) to release more moisture.

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.

What have you done to clean the bed? From the link to the textured sheet, you should be cleaning it between every print - after it cools - with 90% IPA, and if you still have adhesion issues, you should clean it with warm water and a couple drops of dish soap.

Has the TPU been dried? I don’t normally print with TPU but my understanding is that it needs to be lower humidity than PLA; I use dryboxes for PLA and target a humidity of 15% or lower and don’t use them if they raise above 20%. The recommendation I saw for TPU was to dry it for 7 hours at 70 degrees Celsius, to target 10% humidity (or at least under 20%) and to print directly from a drybox. Note that compared to other filaments, TPU can’t recover as well from having absorbed moisture - if the filament has gotten too wet, it’ll become too brittle if you dry it out as much as is needed. At that point you would need to start with a fresh roll, which would ideally go into a dryer and then drybox immediately.

You should be able to set different settings for the initial layer to avoid stringing, i.e., slower speeds and longer retraction distance. It’s a bit more complicated but you can also configure the speed for a specific range of layers to be slower - i.e., setting it to slow down again once you get to the top of the print. For an example of that, see https://forum.prusa3d.com/forum/prusaslicer/bed-flinger-slower-y-movement-as-function-of-z/

What’s the max speed you’re printing at? My understanding is that everything other than travel should all be the same speed at a given layer, and no higher than 25 mm/s. And with a bed slinger I wouldn’t recommend a much higher travel, either.

In addition to a brim, have you tried adding supports?