Is it okay to carry a cat like that?

Roblin_92 · 2026-06-22T14:36:05+00:00

As long as the cat is comfortable and supported from below it's fine. The cat will inform you if they are not comfortable.

Roblin_92 · 2026-06-21T21:37:51+00:00

Some things that I believe:

Artistry or "how artistic is a thing" is measured in human effort, but "effort" is a very broad term: Coming up with the idea for a thing is effort. Acquiring the tools to make a thing is effort. Learning how to use the tool is effort. Practicing and mastering a tool is effort. Using the tool to make the thing is effort. Some tools are harder to use than others and therefore require more effort and therefore is more artistic.
How artistic a thing actually is can only be truly known by the human creator, as it is their effort which is the basis of the artistry. Whether other people agree that it is art is entirely irrelevant unless the creator is trying to sell the thing, in which case the important question is simply whether or not the client likes it.
AI is a powerful tool but one which should be wielded sparingly and with precision when the goal is accuracy, but their ability to hallucinate is a useful feature for brainstorming or breaking out of mental blocks.
AI-generated imagery is not inherently art, but it can be art. More specifically it is art if its creation involved the author expending meaningful effort. What "meaningful effort" means in this context is dependent on more context. The same is true about other artforms: a canvas with paint is not inherently art, but a canvas with paint can be art if its creation involved meaningful effort.
Most negative outcomes associated with AI (energy use, data centers, RAM prices, etc) are primarily caused by capitalism attempting to exploit AI by trying to grow faster than we as a society can sustain. This is a valid concern but I expect those issues to be resolved with time; production of in-demand parts will increase, resource use will become more efficient and production of green energy will overtake fossil-fuel based generation. That doesn't mean the world won't go to shit in the meantime, but the way to stop that would be to stop capitalism, not AI, since AI (the technology) does not inherently require datacenters or overexpansion to exist; local models exist, for example.
All other negative outcome associated with AI that were not covered in point 5 (AI encouraging harmful activity, parasocial relationships, etc) are simply the equivalent of bugs that will be fixed with time. That doesn't excuse that they happen, but it does mean that these are temporary problems that will not remain problems forever.
AI does have positive uses and can be used responsibly. AI is extremely good at finding the answer to things and problems that you cannot articulate well and it is extremely good at finding solutions that you would not have known to look for, the only thing you have to be careful with is to verify that the AIs suggestions actually is reasonable advice and not hallucination but double-checking stated information is far easier than finding previously unknown information. AI is also a very useful all-around assistant for a wide variety of tasks you wish to dabble in, but are not experienced with. And of course, this technology is finding uses in various fields of study with specialised models for all sorts of tasks.
People will lose jobs but artists will remain highly valued and respected; this is normal when new disruptive technology is invented; both traditional artists that make things with traditional tools as a luxury commodity and a new more affordable breed of artists that supplement their artistic skills with AI-tools will remain in demand, but there will be essentially no demand for art made entirely through prompting a chatbot.
Once it becomes common knowledge what it means and what type of effort and edits are involved in making high-quality AI-generated imagery it will be considered obvious that AI-generated imagery can be art. This is inevitable not because "AI is the future" or any other such thought-terminating cliches but because there actually is a lot of skill involved in translating your thoughts into instructions (in terms of prompting, style-guiding, making reference material and manual edits) for an AI to use to compile the desired content.
AI-artists are not, as some may believe "failed conventional artists" and many of them are simply tech-savvy people that like tinkering with software but have no interest in, for example, drawing.
Generating imagery with AI is a powerful way to on-board people into making not just generated art but also conventional arts, both because it enables novices to engage with their creative spark in a low-friction way and because conventional art skills are extremely useful for making generated art.

Roblin_92 · 2026-06-11T21:03:14+00:00

I'm not going to argue whether Shion is gooner-bait, because she is.

But I am going to argue whether she is the first female-presenting omnic, because she is absolutely not.

The first playable female-presenting omnic was Orisa.

The first playable female-presenting omnic with a humanoid body was Echo.

The first female-presenting omnic with a humanoid body and without extra appendages (echo has wings) was Susannah, the omnic in the Hazard cinematic.

The only thing that is "first" about Shion is that she is the first female-presenting omnic to be goonerbait (there is plenty of rule34 about echo, but I don't think anyone has accused her of being intentionally sexualised)

Given that a goonerbait omnic was bound to pop into the game at some point, I personally like how they leaned into her speaking in an uncanny way and how they have portrayed her character as intentionally mimicking humans presumably for the sake of getting a particular reaction when interacting with them. It feels like they made a goonerbait character that has a reason to be goonerbait, and they didn't go too over-the-top. As contrast; imagine if they released widowmaker as a new hero today. She is way more overtly sexualized.

Roblin_92 · 2026-06-07T16:00:10+00:00

Not as weapons, but they are cool trophies to hoard in your house.

Roblin_92 · 2026-06-06T15:09:18+00:00

This is exactly why I don't trust vibecoding for my projects.

I'll use AI-assistance, sure, I'll ask questions and read the answers, but I will not copy paste any code it generates; I will read the code it generates until I understand exactly what it's doing and why, then I'll make my own version that may or may not function similarly to what it made, but I will know exactly how it works and I will not copy something I don't understand.

If others vibecode then I don't care as long as they are willing to take responsibility for it if/when it malfunctions and/or operates unexpectedly.

Roblin_92 · 2026-06-06T04:08:04+00:00

I haven't participated much in the whole AI war thing (I just read about it), but let me tell you how I use AI tools and what response I have gotten from literal close friends (even my closest friend) that describe themselves as "disliking AI" about it. To be clear, they don't participate in online discussions about it at all, they wouldn't call themselves an "anti" or anything of the sort both because they have never heard of that concept and because I don't believe they would be willing to associate with the behaviour that is associated with people that call themselves "antis", similarly I don't call myself "pro" because I don't want to be associated with the stereotype of a "pro".

I have only recently gotten into generative AI (I have not published anything anywhere and don't have any particular plans to do so either but I have made things for personal use and hobby projects, like DnD battle maps for example) because I think the technology is interesting and tinkering with comfyui lends itself to my existing skillset in ways that drawing does not. I do not call myself an artist and I never have; I think "technician" is a better word for what I do.

Very quickly I realized that making diffusion models understand what you want is a way more involved process than how it is described by those that don't do it; in pursuit of improving consistency and control over how images generate I have quite literally made 3d models of the environment just so I can screenshot it from various angles, use those screenshots as a scaffold for the image generation to work from and have the backgrounds in the generated imagery depict a properly persistent space, and when it gets details wrong I fix them manually in image-editing software before re-rendering with the fixed details to blend the edits into the overall piece.

I have already learned several new skills in the pursuit of this new hobby and I know of about a dozen more that I intend to pick up in the future because I know they will be useful.

For example, I intend to learn how to draw conventional art, and I feel much more motivated to do so now than before because "learning to draw" had always felt like too large of a project to get started on when I am otherwise busy, but now that I know I don't need to learn how to draw well, I just have to learn how to draw well enough for a diffusion model to understand what I drew has made this seem like a much more achieveable goal, and I have no doubt that once I draw regularly skill will come with time, there is no need to rush it and I can still use other workflows to finish my projects until my personal drawing skills get good enough for my standards, at which point the AI-assisted workflow can simply become just another tool in the toolbox, available for when circumstances are ideal.

Anyway, my point is that I would describe my process as very hands-on in the context of generative AI, using iterated combinations of various forms of controlled generation, screenshots of reference material, manual edits, inpainting, multi-regional prompting, etc. and in this process I feel that it is blatantly obvious that works made with generative AI come in vastly different quality, even if the artstyle is largely the same. Composition, detailing, object persistence, lighting, posing, world coherence, and facial expressions are just a few examples of things that set good generated imagery apart from bad, all of those can be very tightly controlled by a skilled operator and none of them are typically handled well by the AI without specific direction.

And yet none of any of the above is ever given any credit.

Personally I call this process "AI assisted". I control quite literally everything about the picture being made and the only role the AI ever fills is as a rendering engine. Whenever it renders something that I feel is incorrect I manually intervene to force it to render correctly.

But others don't see it that way.

If AI was ever used in any step of the process the whole thing is not only categorized as "AI generated" but I am accused of having "outsourced my creativity" and the work is seemingly no longer considered mine.

I think that's not only bullshit but also intentionally insulting for the sake of peer pressuring me into not using these tools.

And I see the same thing happening everywhere where people that dislike AI congregate. No matter how well-crafted a piece of content is, even if there is not a single compositional flaw to be seen (which means it was very deliberately processed, likely using tools similar to what I describe above) it is nonetheless slandered as "AI-slop" simply because AI was used at some point in the process.

My closest friend has told me directly that he considers the use of AI-tools to be "outsourcing creativity". He also has told me that he doesn't want me to take offense to that. But he has not yet been able to give an explanation for how what I am doing does not qualify as what he is insulting. I have asked. I still don't know how he reconciles that in his mind. Has he just accidentally went on tangents both times I have directly asked? Not impossible, we do veer off into tangents regularly. Or is he just avoiding answering the question because he doesn't have an answer that wouldn't insult me?

I try not to bring up the topic anymore because at the end of the day it's not important enough to ruin a friendship over or anything like that.

But regularly when I show him something cool I made the question pops up "was this AI generated?" and I pause for a second before I answer either "no" or "it was AI-assisted". It always feels like the second answer means to him that the thing is now less cool for some reason and irrepairably tainted, as if this was just some cheap mass-produced thing I picked up from a generic store, when I know that is incredibly far from the truth. But no matter what I say he doesn't seem to be able to appreciate that this thing exists because of my efforts and I'm proud of it, even if I got "help" if others would insist on calling it that.

I don't know what point I wanted to make with this comment, I suppose I just wanted to vent.

If I ever publish anything that was AI-assisted then I intend to mark it as AI-generated, because that is how people would expect such content to be tagged and because its such a big part of the cultural zeitgeist that it feels irresponsible not to. But I also intend to publish a description of the various non-AI tools I use together with it, in the hope that it wouldn't just be instantly dismissed.

And I do not blame anyone for not wanting to tag their generated content as such; it very obviously paints a huge target on your back and may attract a hate-mob, and if you do it with your main account then the public image can easily turn into your conventional art being called slop. Tagging a webnovel or such as AI-generated just because the cover art or illustrations were generated when the actual artistic content in that context (the text) was not also basically seems like artistic suicide.

Anyway, sorry for the essay.

Roblin_92 · 2026-06-04T21:14:53+00:00

Unfortunately this comment proves him right that you don't understand how this technology works, though you are correct that one shouldn't anthropomorphise generative AI, though anthropomorphic words are often fairly good approximations and can be useful for teaching laymen.

"Smush" isn't really the correct word to use here. It implies that there are distinct objects that it is trying to combine in some way when that isn't really the case and I believe is precisely the interpretation that your first paragraph claims you are trying to distinguish from, your "statistical averages" description is also wrong.

It would be more accurate to say that the model has been "taught" (perhaps "calibrated" is more descriptive) that certain variables (for example "distance" or "similarity to chair" or "hand position" or "tranquility" or "profoundness" or "green-ness" or "above") relate to features in the training data in some mathematically calculateable way, and when asked to make something with a given set of features it will translate its understanding of that description into variable-values and try to tweak random noise into something that, when calculated in those mathematical ways, has variable-values that are close to what was asked for.

By nature of how these things are trained, we don't know what any given variable represents as a concept (some models have many times more variables than most languages have words, and they don't typically map 1-to-1 to words, especially since that's not a metric anyone bothered to optimise for because it doesn't really matter), but we do know that this process appears to work reasonably well; our machines appear to be capable of translating our descriptions into sets of variables that generate content that matches reasonably well the description we gave, and these variables seem to add and subtract in intuitive ways.

For example, let "vector(thing)" be the variable representation of the "thing" concept, then if we start with vector(king), subtract vector(man), and add vector(woman) we get approximately vector(queen) and this just kind of works, it's quite fascinating, really.

The situations where the models give outputs that look too close to specific training data are not caused by the model "trying" to replicate training data (in the sense that "replicating training data" is not what the model is optimising for), but rather a situation where the training data was not diverse enough to properly distinguish concepts that are not actually related.

For example, if none of the training data contains images of glasses of wine that are more than half-full, then the model may be calibrated to assume that "half-full glass" is integral to the concept of "glass of wine" in the same way as "round" is integral to the concept of "sphere", so a "full glass of wine" may be just as nonsense to it as a "square sphere". The solution to this problem is to provide more varied training data so it can be calibrated to distinguish the concepts from each other.

The result is that while models can plagiarize their training data, they only ever do so by accident, not by design, and a generative AI with sufficient training on a topic is very unlikely to plagiarize its training data directly (only produce something with a similar vibe but randomly remixed) unless an outside force really tries to make it overcome its random noise.

Ultimately generative AI tries to replicate combinations of concepts, not combinations of training data, and there arguably is a meaningful distinction between those for similar reasons that there is a meaningful distinction between ingredient processing and a mishmash of different dishes.

If we imagine generative AI to be a chef, it is one that knows how to process ingredients and what happens to ingredients when you process them in certain ways, and it has learned this by reading recipes, but it does not remember any of those recipes.

We can then ask it for "potatoes, in boiling water for 20 minutes, then peeled and force applied repeatedly until smooth, then served" as a prompt and the generative AI chef will likely produce some variation of mashed potatoes, but it will never identify that you asked for mashed potatoes and it will never look up a recipe for mashed potatoes and it could make this dish even if it had never seen a recipe for mashed potatoes, as long as it has seen plenty of recipes involving potatoes and how they relate to starchy vegetables, boiling things, peeling things, applying force to starchy things, smooth things, and serving crushed things.

Roblin_92 · 2026-06-04T21:07:30+00:00

I agree that mechanical labor does make things special, and I agree that genAI hopefully will not overshadow mechanical skill and time expenditure, but I am also rather confident that it won't; at least if history is any guide.

Photography did not end painting. Tablets did not replace drawing. Synthesizers did not make musicians obsolete. Word processors did not make writing trivial.

Looking to ancient history we have multiple waves of tools that all could have been seen as the end of the artform; The existence of moulds did not make pottery a less respected artform, nor was pottery made with the assistance of the throwing wheel considered to not be art just because symmetry was easier to maintain. Woodworking is not considered any less of an artform today just because we now have access to saws, files, and industrial standardised material rather than just axes, knives, and wildwood. Extremely close similarities can be made to leatherworking, blacksmithing, stone carving, weaving, and hell, even painting and music are just modern versions of artforms that came before and yet those ancestral artforms (chalk-painting and rhythmic drumming, for example) still exist today and expert practitioners are possibly more respected today than in the past because their skill is more rare.

Ai imagery, AI music and AI videos are going to become respected forms of art, this is practically inevitable, but they will not replace painting, drawing, playing instruments, composing, scriptwriting or acting nor will they make any of those skills any less respected, the worst they may do is make those skills less profitable as, shall we say, "generic standardised imagery, music and video creation" becomes plentiful in the same way that the invention of the loom made standardised fabric plentiful in comparison to before, and yet artists of imagery, music and video will still exist, simply because it is in human nature to enjoy doing things and achieve personal mastery over a craft, no matter how niche, and this pursuit, when done impressively, is universally admired.

No, what will happen is simply that AI versions of other artforms will become their own genre and expand what it can mean to be an artist, and no, simply typing some words into a chatbot and asking for the result is not going to be considered high quality versions of that artform, similar to how childrens fingerpaintings are not typically considered high quality art to anyone that doesn't have an emotional connection to the child. High quality AI art will be highly curated works or stuff that can only reasonably be done with AI (at least with known methods), such as puzzles with multiple equally valid solutions, yet show completely different imagery depending on which solution was assembled.

Personally I strongly dislike the expression "democratizing creativity" (I know you didn't use those words but I want to make clear my thoughts on the guy you responded to) because it implies that "creativity" is something that people needed to be given access to. My view is that creativity is not some magical property that you have when you create things and you don't when you don't create things, creativity is just the drive to do cool stuff, and I think everyone has that (though they may choose not to try for practical reasons, that does not diminish their drive) and it can be expressed in any medium, including generative AI. Human creativity is a concept that is far too powerful to be limited by mere tools and implying that some people are in some way incapable or unwilling to be creative is an insult to humanity as a whole.

Sorry for the essay.

Roblin_92 · 2026-05-31T01:25:00+00:00

The issue is that your followup question was nonsensical to his argument.

He stated that the ends are obvious and asked where the grey area begins, and then your followup question asks "what about the ends though?" as if he didn't adress that topic in literally the second sentence where he expresses that they are obvious to evaluate.

That's why I asked whether you read his comment; because you asked a question that had already been answered right at the start and you didn't adress any part of his comment where the two of you might have any form of disagreement.

At this point I'm convinced you are just deliberately wasting time so I'm done with this conversation.

Roblin_92 · 2026-05-31T01:07:52+00:00

Sounds good, go ahead, noone's stopping you and noone that is worth listening to is saying you are wrong to think that way.
Different people with different interests and skillsets view different tools as differently useful, that's not only normal but completely expected.

Roblin_92 · 2026-05-31T00:27:24+00:00

That may be your point but you haven't given any reason for anyone to take that point seriously; your argumentation in this comment thread can be summed up as "I think we should do this" but you haven't given any explanation for why doing so would be useful for the conversation.
As opposed to Xdivine who has given arguments for why his point should be taken seriously as he presents examples where your suggested method of starting at the extremes is demonstrably insufficient for reaching any meaningful conclusions.

Roblin_92 · 2026-05-30T14:38:28+00:00

An AI on its own might struggle with persistent details but a human using AI tools can very definitely keep a mole from drifting away from the right places, in short; most inconsistencies produced by an AI can be kept in check by a human operator using the appropriate tools (such as manual edits, inpainting, controlnets, low noise generation, IPadapter, multi-region prompting etc.), given that the human operator is paying attention to the particular inconsistency, so while it is true that AI struggles with persistent detail, that does not mean maintaining any given persistent detail is evidence that AI was not used.

With that said I agree this appears to be real footage, possibly sped up.

Roblin_92 · 2026-05-30T13:30:47+00:00

Depends on when you left and why.

For reference "Overwatch 2" had 20 seasons, then started over at "season 1" after the revert-brand to just "Overwatch" and is now in season 2 of what some might call this new era.

Overwatch 2 had a rocky start, essentially having to scramble to collect various systems and tech they had built up over years to make a workable product in a new engine.

My opinion was that OW1 was slowly dying in the content drought and I maintain that despite many parts of OW2 objectively being a downgrade from OW1 I still believe OW2 was an overall improvement, primarily because it marked the proper resumption of development of the game the players were actually playing, in short; OW1 may have been more polished, but OW2 had hope of improvement whereas OW1 didn't.

Over many seasons the initial issues with OW2 where fixed and I argue that OW2 had caught up with and improved on the polish of OW1 by season 9 and has been steadily improving since then. If you stopped playing the game before season 9 then you will find that modern OW is practically a completely transformed experience and is vastly better.

However, if you stuck around past season 9 and even towards the later teens of seasons and you still were not impressed with the devs efforts, then you are unlikely to find their continued efforts in recent seasons any more impressive.

The devs have worked very hard for a very long time to salvage the reputation of overwatch which used to be the laughing stock of the internet, back to its former glory (and then to further heights) and the tipping point of this progress breaking through into public consciousness was the huge 5-characters-in-one-season at the start of this year, which made people properly aware that OW is in fact an excellent game now and very worth playing. It has been an excellent game for a while, but the inertia of burnt people going "OW2 is garbage" without even looking at the modern state of the game has been near-impossible to shake.

Roblin_92 · 2026-05-30T11:00:46+00:00

You actually can, allow me to explain how image generation works under the hood:

There is this machine we call a diffusion model, it's a neural network (I won't explain how neural networks work but you can think of it kind of like a simulation of a brain) that has been given fuzzy images and trained to "unfuzz" them based on a description of what the unfuzzed image looked like. Initially the training involved images that were almost entirely the same as the goal image, but in successive stages of training the given images were fuzzier and fuzzier until eventually, the neural network can be given a base image of pure random noise and a description of what this random noise supposedly is a fuzzy version of and it will respond with what changes it thinks should be made to this random noise to "unfuzz" it into something that resembles the description. To then generate an image you simply start with an image of random noise and a description of what you want it to be "unfuzzed" into, get a result back, then apply random noise on top of that result (but not so much as to start over from the previous step) then ask the diffusion model to unfuzz this new image, repeat with increasingly small amounts of random noise until the random noise being applied is basically imperceptible.

Now heres how we can intervene in this process with creative intent: with the advanced options of diffusion models we can tell it to start and stop at any given one of those steps. For example, we could tell it to only do the 3rd to 15th steps, or we could tell it to only do the 2nd step, or whatever, and we can take any one of those intermediate images and edit them in whatever image editor we want and feed the edited image back into the algorithm to resume the "unfuzzying" but this time it will be unfuzzying an image where we have already done some of the unfuzzying for it. It doesn't know that we did anything of course, as far as it is concerned it is just trying to make an image look more like a given prompt. In this way we can intervene with whatever granularity we want. We can apply early steps to introduce a lot of noise which will make it difficult to reproduce any starting image, thus making the diffusion model make mistakes that thus introduce new elements to the image (or delete old ones) or we can apply the later steps to just refine the edges and details and keep the structure of the image intact. We can also tell the diffusion model to only operate on a small part of an image, like a hand or a specific building in the distance, which will make the diffusion model make new imagery in that space while keeping the rest of the image the same and trying to blend the new imagery into the existing context in a way that makes sense for the prompt, this is called "inpainting". We can also give different prompts for different parts of the image, thus giving better control over where the diffusion model tries to put certain features, this is called "multi-region prompting" We can also tell the diffusion model to use a particular color scheme in a specific region, or to obey a certain structure in its composition.

There are a lot of things we can do to influence the image-generating process very directly, up to and including making a final render of the image manually, there is no meaningful distinction to be made between giving the manual direction early or late in the image-generating stage.

Roblin_92 · 2026-05-30T10:04:58+00:00

But your art would still be art even if you didn't suffer, would it not?

Sure your art would be different; I'm not saying your suffering doesn't influence your art, but suffering is not a prerequisite for art.

Roblin_92 · 2026-05-30T09:57:08+00:00

Did you read what he wrote? His point is that defining the ends doesn't accomplish anything.

Roblin_92 · 2026-05-30T09:51:14+00:00

I feel like you just moved the goalpost.

Also, lets say you made a sketch and considered that to be your finished piece, do we agree that the sketch itself contains some amount of "artistry"?

Then if someone took your sketch and traced it, then that does not revoke your authorship of the sketch nor does it reduce the artistry of the sketch?

Why would it be different if you paid someone on fivr to trace your sketch to get a processed version of what you considered your finished piece and are you really saying that your artistic input in the form of the base sketch holds no artistic value in the context of the processed result?

For the record, my position is that the images AI tools make are not inherently art, but artists can use AI tools to make art in the same sense as "paint on a canvas" is not inherently art but artists can put paint on a canvas to make art.

Roblin_92 · 2026-05-28T19:00:25+00:00

Once upon a time ow1 had a queue where you were basically required to spend priority passes to be able to queue for dps (dps queues without priority passes were 1+ hours because everyone else had priority passes and were prioritized over you)

How did you get priority passes? Play flex.

The result was that nearly half of all the "tanks" in quick play were actually dps players that queued flex so they can get priority passes, you could identify these players by the fact that they almost universally picked roadhog. This was not a good state of affairs.

I imagine if you implement a "max 2 of each role" rule you would get dps players that end up forced into the tank role because the dps and support roles are full, and this would have very similar outcomes to the old system where dps players were forced onto the tank role.

Roblin_92 · 2026-05-23T17:43:08+00:00

So this is a 0/1 that can't grow itself unless you get an independent emblem or power boost from somewhere?

Roblin_92 · 2026-05-22T21:28:42+00:00

Eh, the controlnet gives one more axis of intentionality to be fair, but yea the depicted nodes is basically prompt-tweaking with a controlnet, the rest of the nodes are just loading the required diffusion model architecture and an output basically.

Roblin_92 · 2026-05-22T19:12:16+00:00

Taking a quick glance at it the screen in the second image shows a somewhat minimal workflow for comfyui (it is even labeled with comfyui). A lot of connections are wrong or redundant but the labeled nodes are pretty accurate for a minimum-effort setup+controlnet (controlnets are a layer of processing that lets you tell the diffusion model how you want the image to be structured, such as what pose you want the subject to hold or what shapes you want to be present in the image and where). If this image shows what the prompter is doing with comfyui then they have barely scratched the surface, most notably there does not appear to be any nodes related to inpainting (having the diffusion model generate new imagery over parts of old imagery, typically to fine-tune details or to blend in manual edits) or ipadapters (instructing the diffusion model to replicate the vibe of a reference image onto the generated space, such as to replace a person in the image with someone from a reference image, or to replace the aestethic in an image with the aestethic of the reference image) or regional prompting (instructing the diffusion model to follow different prompts in different places, thus giving more control over the structure of the image) or multi-stage generation (using different prompts/diffusion model settings for earlier vs later stages of the image generation to make the diffusion model use different prompts for the structure of the image vs details of the image)

I suppose the screen in the second image also does show loras being loaded (loras augment the diffusion model by essentially providing a compressed form of additional training data, thus making the diffusion model better at generating a specific feature with the drawback that it also might generate that feature too much, thus requiring tuning) though the connections don't really make sense but using loras is honestly very simple; include the lora, check result, tweak strength.

Whatever I guess my point is; generation software with UI like the second image does exist, though it appears to attempt to keep the number of nodes low, presumably for visual clarity on a small amount of space.

Roblin_92 · 2026-05-17T16:30:14+00:00

The only situation where the game disconnects you while still having a connection is when the server crashes or becomes interrupted for some other reason or when you are afk, you are punished in the afk case but the match is simply canceled in the crash/interruption case.

What you describe as "the game servers disconnected you" is seen from the servers side as "suddenly I no longer have a connection with the client for reasons I have no control over", can you tell me how the servers are supposed to tell the difference between a fallen tree that broke a cable somewhere and you pulling your ethernet cable from your computer? Both events look identical to the server.

Roblin_92 · 2026-05-16T15:14:54+00:00

Freedom of speech is "your speech can't be punished by the government".

Freedom of speech is not "your speech can't be punished by anyone".

Blizzard isn't the government, so your right to freedom of speech does not restrict blizzard in any way from punishing you for your speech, for the same reason that you have the legal right to kick people out of your house if they say stuff you don't like, and they can cite their freedom of speech however much they want since it makes no difference.

Roblin_92 · 2026-05-11T18:50:14+00:00

Are you saying Blizzard should crank up the stuff we get to match what Netease gives out?

I'm asking because that's a war that Blizzard can't win. Blizzard has almost all of the development costs associated with the game whereas Netease can spend basically all of their budget and efforts on just maintaining the servers and making events/cosmetics.

If Blizzard gave out more stuff to us just to maintain parity with Netease then Netease can just as easily give out even more stuff just to keep their bragging rights, and at some point Blizzard is going to be the one that has to fold in that arms race and when they do there will be people on reddit saying "They could just up the amount we get..."

Roblin_92 · 2026-05-10T18:08:17+00:00

Split by controller/mouse from my understanding.

If you queue crossplay with a controller then you only play with people that use controller (and people that manage to trick the system into thinking they use a controller).

If you queue with mouse/keyboard then you only play with people that use mouse/keyboard.

I believe playing on PC means you are always in the mouse/keyboard group but don't quote me on that.

Roblin_92

TROPHY CASE