vozka

This seems like a futile process to me. We all love TheDarkMod and tremendous work has been done on the engine, but I suspect that when developing a new project, especially commercial, almost everyone would rather go for a more modern engine because the reality is that stealth games are a relatively small niche and you need everything you can get to make people notice and buy your thing. TDM with its historical limits on polycounts (unless switching to lightmaps removed that?) and other features that we're used to and have no problem with but that are not exactly state of the art in my opinion just isn't "it", and it's only going to be less and less "it" over time, despite being a brilliant game on its own. And making the game fully libre just so it can be included in certain distributions' free repos, while stripping out almost everything that makes TDM what it is, the community content, doesn't make sense to me either. If anything that could hurt its reputation because people who tried that wouldn't experience the actual game. I only skimmed parts of the thread, have I missed a good reason to do this? Also, another big issue that I think wasn't spelled out explicitly enough: I too thought that it would be awesome to have TDM on Steam. After looking into it, being educated by others and doing some searching I found out that TDM very likely contains a nontrivial amount of old content that may be seemingly re-licensed as CC-BY-NC, but legally cannot be, as its original license does not allow it. I'm talking specifically about old textures.com content - it uses its own asset license that explicitly disallows being released as CC (because CC allows redistribution anywhere and textures.com license explicitly prohibits that). Yet some of those assets are a part of TDM, and it's likely that nobody knows for sure which ones and how many there are. Textures.com was at one point even recommended as a source to create assets on the wiki. So you may get permission from some old mission author who doesn't even remember that he did this, but his content can still be non-free and in fact infringing on its original license. Realistically nobody cares because there's no damage to textures.com being done (the textures are not being redistributed anywhere, they're "just" being incorrectly rebranded with a license that would allow it), but it makes the whole libre thing even more difficult.

I looked through the wiki and it doesn't seem that complicated. I don't want to spend the time to learn DarkRadiant enough to create testing rooms with different reverbs (I don't use it at all and when I tried it I spent too much time on basics like where to save which definition files and how to correctly use them etc.) so I'm not going to be super helpful here, but I looked through this thread dealing with that exact issue: And through this page: https://wiki.thedarkmod.com/index.php?title=Setting_Reverb_Data_of_Rooms_(EAX) It seems like the parameters in the version 2 of EAX Reverb are relatively sane, you only need a few of them and according to the linked thread (it includes a couple examples) it should be possible to just take existing presets and modify a couple parameteres that need to be modified. One important part of the wiki is the image of the table with existing parameters and their allowed ranges. It also contains contains a link to OpenAI EFX manual section that explains all the parameters in reasonably plain english: https://usermanual.wiki/Pdf/Effects20Extension20Guide.90272296/view#95 The way I understand it the parameters are used without the AL_EAXREVERB_ prefix and the most important one is the GAIN parameter, which controls how loud the reverb/echo is compared to the original sound, its default value is 0.32 and allowed range is 0.0 - 1.0, so setting it somewhere lower than 0.32 would be a good start. The second is DECAY_TIME, set in seconds, range 0.1 - 20.0: the larger the room, the longer the decay time, but at the same time the more filled with absorbent materials it is (carpets, beds, armchairs but also full bookcases), the shorter the decay and quieter the the gain. There are other parameters that would allow you to make the reverbs and echos more sophisticated, but these two should be enough to fix the big problems.

I'm regularly thrown off by how unnatural the reverb in TDM sounds (and mission authors tend to use too much of it) and by how nonsensical the panning system is up close - you stand in front of a lock you're picking and yet sometimes the picking sound is heard almost entirely from the right and then the door opening sound is heard entirely from the left. I can imagine a trivial geometrical explanation of why that is, but it just doesn't work well in these edge cases. I think there's a ton of potential to improve sound engines in games, for me personally this has a big influence on how immersed I am and how well I remember the game (Bioshock 1 was excellent, despite the fact that the reverb was also kind of crude in it, but it was used well and the sound design was great - I can still remember how it sounds). So I warmly welcome any improvements. But working with sound in various ways is both a big hobby and an occassional source of income for me, so I'm not exactly the average person (though arguably experiences like these are partially what led me to the hobby).

Just finished. What an excellent mission. Even the intro video was one of the best I've seen. If I had to nitpick, I'd say there's too much echo on the dialogue, but I'm only saying that because I feel this is a bit of a trend among TDM creators in general (usually in missions, not in intro videos). Beautiful graphics style and lighting, interesting areas that are fun to traverse. Sometimes I had a bit of an issue with the AI being mildly weird, but that's just something that happens in TDM. The difficulty was relatively mild - when purchasing the copy of the master key, that is. I didn't try ghosting it, just no kills and one or two knockouts, without significant issues. The loot limits were set up relatively benevolently as well, ended up with 1580 without having to backtrack anywhere, 6 out of 8 secrets. Took just short of 2 hours. Therefore I agree that it would work pretty well in a campaign.

Yeah, I don't think it needs to be removed.

Damn, what a crazy mission. One issue with missions like this is that sharing screenshots that would accurately represent it would ruin the experience. So if anybody is reading this and considering whether to play it or not: this is very much not a standard city/mansion mission. Obviously I was blown away. My favorite moment was wondering "Are these just decorations or will I be able to jump onto them? Surely it's just a decoration." And it wasn't. I bet I wasn't alone in this. The story was a bit confusing in places (the details like family issues, not what was overall happening), but what's important is that the mission was not. It was huge and there was a lot to do, but it flowed well. What helped was that finding stuff in "act one" helped me understand the layout of things in "act two", that in turn helped me find which areas I likely missed in "act one", and I was then free to take my time and return to them. That's a concept that worked really well because the added context made revisiting the old areas interesting again, something that I don't believe any other mission has achieved to do for me. I did have to go through this thread to find some of the secrets, but that's because I generally don't replay missions and wanted to get the (mostly) full experience from my one playthrough. It did seem at one point that the mission could be completed when the player has seen maybe 50% of it, which was a bit strange, but I guess most people here would not do that anyway.

I've never actually seen the insides of an elevator but from what I know about electronics in similar settings from a few friends who did some work in the field, my guess is that it's an ARM system on a chip and it's quite possible that it runs Linux. And it's highly likely that it's separated from a chip that's taking care of the actual elevator movement, so you probably couldn't use the buttons for input. The reason for this being that ARM SoCs able to run linux are really not that expensive nowadays, whereas developing custom systems outputting graphics with a cheaper weaker chip has a large upfront cost. And if you're using a universal OS like Linux, you can keep the software side the same if the ARM chip you're using goes out of production and you need to switch to a new one. If these assumptions are true, running Doom on it would be easy provided there's some input method.

This is getting a bit ridiculous. Don't you think you should tone down the quality a bit? It's almost obscene.

I'm pretty sure this happened to me at least once as well, but not every time the crash happened, if this brilliantly specific information helps any. It was not in the mission mentioned above (The Lieutenant 2), it was in various different missions.

As far as I know ChatGPT does not do this at all. It only saves content within one conversation, and while the developers definitely use user conversations to improve the model (and tighten the censorship of forbidden topics), it is not saved and learned as is.

I didn't want to spam this thread even more since I wasn't the one who was asked, but since you already replied: img2img does not work well for this use case as it only takes the colors of the original image as a starting point. Therefore it would either stay black & white and sketch-like or deviate significantly from the sketch in every way. Sometimes it's possible to find a balance, but it's time consuming and it doesn't always work. This probably used Control Nets, specialized addon neural nets that are trained to guide the diffusion process using specialized images like normal maps, depth maps, results of edge detection and others. And there's also a control net trained on scribbles which is what I assume Arcturus used. It still needs a text prompt, the control net functions as an added element to the standard image generation process, but it allows to extract the shapes and concepts from the sketch without also using its colors.

Trying to bring this thread back to the original topic. Had ChatGPT 4 generate ideas for a game. I chose 7-day roguelike because it's supposed to be simple enough. I would like to participate in the 7-day roguelike contest. It's a game jam where you make a roguelike game in 7 days - some preparation before that is allowed, you can have some basic framework etc, but the main portion of work is supposed to be done within the 7 days. Therefore it favors games with simple systems but good and original ideas. Some of the games contain "outside the box" design that stretches the definition of a roguelike. Please give me an idea of a 7-day roguelike that I could create. Be specific: include the overall themes and topics, describe the game world, overarching abstract ideas (what is the goal of the player, how does the game world works, what makes it interesting...) and specifics about gameplay systems. Describe how it relates to traditional roguelike games or other existing games. This is really not bad and after some simplification I could actually see it work, though I don't know if the mechanic is interesting enough. I had it generate two more. One was not roguelike enough (it was basically something like Dungeon Keeper), the other was a roguelike-puzzle with a time loop: you had to get through a procedurally generated temple with monsters, traps and puzzles in a limited amount of turns, and after you spend those turns, you get returned to the beginning, the whole temple resets and you start again, trying to be more efficient than last time.

The issue with this argument is that the process of training the neural network is not in principle any different than a human consultant learning from publicly available code and then giving out advice for money. The only obvious difference being that GPT is dramatically more efficient, dramatically more expensive to train and cheaper to use. This difference may be enough to say that LLMs should be somehow regulated, but I don't see how it could be enough to say that one is OK and the other is completely unethical and disgusting. Isn't the issue with LLMs that they don't give credit to the material that they were trained on? How is then any reputation tarnished? Or do you mean tarnishing somebody else's reputation by generating libelous articles etc.? That may be a problem, but I don't see the relation to the fact that training data is public. As far as I know there is some legal precedent saying that training on public texts is legal in the US. It might change in the future because LLMs probably change the game a bit, but I don't believe there's any legal reason why they should receive any bills at this moment. They also published some things about training GPT-3 (the majority is Common Crawl). Personally I don't see an issue with including controversial content in the training dataset and while "jailbreaks" (ways to get it to talk about controversial topics) are currently a regular and inevitable thing with ChatGPT, outside of them it definitely has an overall "western liberal" bias, the opposite of the websites you mention.

I agree with what you're saying. My biggest problem with this ethics debate is that there seems to be a lot of insincerity and moving the goalposts by people whose argument is simply "I don't like this" hidden behind various rationalizations. Like people claiming that Stable Diffusion is a collage machine or something comparable to photobashing. Or admitting that it's not the case but claiming that it can still reproduce images that were in its training dataset (therefore violating copyright), ignoring that the one study that showed this effect was done on an old unreleased version of Stable Diffusion which suffered from overtraining because certain images were present in 100+ copies in its dataset, and even in this special situation it took about 1.7 million attempts to create one duplicity, never reproducing it on any of the versions released for public use. I also dislike how they're attacking Stable Diffusion the most - the one tool that's actually free for everyone to use and that effectively democratizes the technology. Luddites at least did not protest against the machines themselves, but against not having the ownership of the machines and the right to use it for their own gain. They're just picking an easy target. I don't believe there's any current legal reason to restrict training on public data. But there are undoubtedly going to be legal battles because some people believe that the process of training a neural network is sufficiently different from an artist learning to imitate an existing style that it warrants new legal frameworks to be created. I can see their point to some degree. While the learning process in principle is kind of similar to how a real person learns, the efficiency at which it works is so different that will undoubtedly create significant changes in society, and significant changes in society might warrant new legislature even it seems unfair. The issue is I don't see a way to do such legislature that could be realistically implemented. Accepting reality, moving forward and trying to deal with the individual consequences seems like the least bad solution at this moment.

Seems like most threads about this topic on the internet get filled by similar themes. ChatGPT is not AI. ChatGPT lied to me. ChatGPT/Stable Diffusion is just taking pieces of other people's work and mashing them together. ChatGPT/Stable Diffusion is trained against our consent and that's unethical. The last point is kind of valid but too deep for me to want to go into (personally I don't care if somebody uses my text/photos/renders for training), the rest seem like a real waste of time. AI has always been a label for a whole field that spans from simple decision trees through natural language processing and machine learning to an actual hypothetical artificial general intelligence. It doesn't really matter that GPT at its core is just a huge probability based text generator when many of its interesting qualities that people are talking about are emergent and largely unexpected. The interesting things start when you spend some time learning how to use it effectively and finding out what it's good at instead of trying to use it like a google or wikipedia substitute or even trying to "gotcha!" it by having it make up facts. It is bad at that job because neither it nor you can recognize whether it's recalling things or hallucinating nonsense (without spending some effort). I have found that it is remarkably good at: Coding. Especially GPT-4 is magnificent. It can only handle relatively simple and short code snippets, not whole programs, but for example when starting to work with a library I've never used before it can generate something comparable to tutorial example code, except finetuned for my exact use case. It can also work a little bit like pair programming. Saves a lot time. Text/information processing. I needed to write an article that dives relatively deep into a domain that I knew almost nothing about. After spending a few days reading books and articles and other sources and building a note base, instead of rewriting and restructuring the note base into text I generated the article paragraph by paragraph by pasting the notes bit by bit into ChatGPT. Had to do a lot of manual tweaking, but it saved me about 25% of time over the whole article, and that was GPT-3.5. GPT-4 can do much better: my friend had a page or two full of notes on a psychiatric diagnosis and found a long article about the same topic that he didn't have time to read. So he just pasted both into ChatGPT and asked whether the article contains information that's not present in his notes. ChatGPT answered basically "There's not much new information present, but you may focus on these topics if you want, that's where the article goes a bit deeper than your notes." Naturally he went to actually read the whole article and check the validity of the result, and it was 100% true. General advice on things that you have to fact check anyway. When I was writing the article mentioned above, I told it to give me an outline. Turns out I forgot to mention one pretty interesting point that ChatGPT thought of, and the rest were basically things that I was already planning to write about. Want to start a startup but know nothing about marketing or other related topics? ChatGPT will probably give you very reasonable advice about where to start and what to learn about, and since you have to really think about that advice in the context of your startup anyway, you don't lose any time by fact checking. Bing AI is just Bing search + GPT-4 set up in a specific way. It's better at getting facts because it searches for those facts on the internet instead of attempting to recall them. It's pretty bad at getting truly complicated search queries because it's limited by using a normal search in the background, but it can do really well at specific single searches. For example I was looking for a supplement that's supposed to help with chronic fatigue syndrome and I only knew that it contained a mixture of amino acids, it was based on some published study and it was made in Australia. Finding it on google through those things was surprisingly difficult, I'm sure I could do it eventually, but it would certainly take me longer than 10 minutes. Bing AI search had it immediately.