Search the Community

Thanks, Dragofer. Implementing such UI facelift is fairly easy to do with zero risk of breaking anything. Target files: game/Objectives/MissionData.cpp (source) guis/mainmenu_success.gui (pk4) strings/*.lang (pk4) - Optional? Unfortunately there is little I can do on my own (mod) since this part of the source code is structured in an awkwardly linear, uncontrolled and strict way. If there ever is an initiative to seriously discuss improvements and come up with suggestions and mock ups, count me in. Let's just make sure someone is available and willing to commit changes of MissionData.cpp. Cheers!

Thanks for the Vicuna link. I need to do more research on open source chatbot solutions. I have a couple of projects in the works that would benefit from a home grown language model, plus it would be good experience. Seeing what others have done with modest resources is good inspiration. Also I must admit I was wrong earlier in this thread about open source not being able to compete with big tech. It did not occur to me that big industrial model builders would be incentivized to gift their own models into the public domain in order to gain mind share with open source ecosystems that can out-innovate them on the application side. The upside for them is that they can effectively crowd source the R&D to turn their fancy tech demo into actually valuable products for the open market and for their own internal consumption. Google at least is taking that concept seriously. Lastly: The results of a couple of gpt-4s attempts are fascinating to me... I got some really interesting failure points, including a rare pattern hypnosis where it fell into a meaningless cycle of iterative modulus calculations. But I doubt you guys want to read 4 pages of that, so here's the beginning and the end. Note for anyone wondering what is going on, the root mistake is a heuristic error humans also make: assuming no one would ask a stupid question. Thus the pattern recognitions assumes we want the complex systematic solution for the closest hard problem... which is what it gives above. Moreover because the question is so minimal it actually half asses its answer here: ignoring the fact that it already knows next Easter falls on March 31, 2024 from reading online calendars! What's more, it has more than enough information in its memory to attempt the computus calculation (albeit unsuccessfully in every attempt I saw). Once again we see that context is king for LLMs. In fact we can even break it out of the faulty heuristic with a small change to the prompt:

Thanks for playing and the kind feedback re: the bugs: the brew tank is a new one - thanks for that. Will add it to the list for any future update. the bow: I think that's a TDM bug. I experienced it as well, but only the early days of developing the mission so I thought it had gone away, but I guess not: https://forums.thedarkmod.com/index.php?/topic/21345-210-crashes-may-be-bow-frontend-acceleration-related/ the keys on the guard: never did get to the bottom of that one as I could never reproduce it.

Thanks for giving detailed insight. I don't understand what the navigation of readme files has to do with translation. Or can readme files also be translated? I didn't look much into translation, because of the complexity and I personally don't have a need for it for my language.

OK, I stared at the code some more. It doesn't care about EOL. It just divides the text into blocks based on where the known keyword strings are. (It's a bit complicated. It uses a sorted associative set of starting locations (plus end-of-text), and manipulates an iterator over that set is such a way that the block order is not important. That's in ModInfo.cpp's LoadMetaData() function.) So in the example above, a block begins at the start of "Title:..." and stops right before the beginning of "Author". Because "Version:" is not a parsed keyword, it's just more content for the title block.

Thanks! Hint for the safe code here: https://forums.thedarkmod.com/index.php?/topic/21837-fan-mission-the-lieutenant-2-high-expectations-by-frost_salamander-20230424/&do=findComment&comment=485264 Actually, it's probably time I added these hints to the original post....

Also, a more general lesson to draw from these examples is that context is critical to Large Language Model (LLM) algorithms. LLMs are pattern completion algorithms. They function by searching for patterns in the letter-sequence of the text within its memory buffer. It then predicts the most likely sequence of letters to come next. (Or more accurately it randomly selects a block of letters called a token from the predicted probability distribution of possible tokens, but that distinction is mostly academic for the end user.) These models are then trained on effectively the complete written works of humankind to self-generate an obscenely sophisticated prediction model, incorporating literally billions of factors. Context matters because the LLM can only build on patterns already established in the prompts you give it. The less context is given in the prompt, the more the response will tend towards the most common sort of non-specific example in the data set. Conversely the more patterns you establish in a conversation the more the model will want to stick to those patterns, even if they are contradicted by the user's directions or basic logic. In the life is a journey example, once the model has been infected with the idea that "Life is a journey" has four syllables that very simple and powerful meme starts to stick in its "mind". The mistake is to then introduce linkages to syllable counting and even arithmetic without ever directly contradicting that original mistake, which becomes a premise for the entire conversation. In a world where "Life is a journey" has four syllables is an axiom, it is actually correct that 1+1+1+2=4, Incidentally that conversation also demonstrates what I like to call mirroring. Not only does ChatGPT pick up on the content of the prompts you give it, it will also notice and start mimicking text features humans aren’t normally even conscious of: like patterns of writing style, word choice, tone, and formatting. This can be very powerful once you become aware of it, but causes issues when starting off. If you want a specific sort of output, don’t model an opposing mode of conversation in your inputs. If you want the maximize the model's openness to admitting (and embracing) that its previous statements are wrong then you should model open mindedness in your own statements. If you want it to give intelligent responses then talk to it like someone who understands the subject. If you want it to be cooperative and polite, model diplomacy and manners. I actually think it is worthwhile regularly saying please and thank you to the bot. Give it encouragement and respect and it will reciprocate to keep the conversation productive. (Obviously there are also tasks where you might want the opposite, like if you were having the AI write dialogue for a grumpy character. Mirroring is powerful.)

How does it compare to Bing? Bing supposedly uses GPT4? It still struggles with seemingly simple tasks. It has obvious blind spots. It struggles to write a regular poem in English that doesn't have any rhymes. On the other hand it absolutely cannot write a poem that rhymes in Polish. It will happily write you a poem in Polish that doesn't rhyme. When asked which words in the poem rhyme it will list words that don't rhyme. It has problem with counting letters and syllables too: "Write a regular poem in English that has an equal number of syllables in each line." "Birds chirp and sing their sweet melodies" - how many syllables are there? Can you list them? Check again bro. It generally will do worse writing in languages other than English for obvious reasons - the training data. When asked to write Polish words that rhyme, it sometimes will make up a word. Sometimes a Polish word paired with an English word (but when asked it will tell you it's Polish), sometimes it will write words that don't rhyme at all. It clearly doesn't "see" words the way we are. Neither literally nor metaphorically. Not to mention it can't hear how they are pronounced which is important for rhyming. Some of the problem may come from the fact that language models are trained on tokens rather than letters or syllables. Couple of months ago people found that there were some really weird words that were invisible for Chat GPT or caused erratic behavior. It later turned out to be that there were a bunch of anomalous tokens, like Reddit user names that were cut from the training data. That caused errors when they were used in prompts. It was quickly patched. Edit: Just had a discussion with Bing: So how many are there? Check again bro. "One plus one plus one plus two equals four." Do you see anything wrong? How many "ones" are there in that sentence? Can you write it using digits? You still see nothing wrong? It seems like once it gets it wrong it has a hard time seeing the mistake it made.

I never realised Bill Gates was a member of these forums. Welcome to the community! I hope you enjoy The Dark Mod. Perhaps your Foundation could help pay for the server hosting or fund the development of some new features?

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.

Language models are a mirror, reflecting the collected works of humanity back at us. Some people look in that mirror, see their own reflection, and conclude "there is a artificial person behind this sheet of glass that looks and behaves exactly like me... our days as humans are numbered!". But it's not true. It's just a reflection. It can't create anything that humans couldn't (or haven't) created to begin with. I have no doubt that one day, artificial human-like intelligence will exist, but it will require a lot more than just a language model remixing stuff on the internet. If you're a cargo cult programmer copy-pasting junk code off Stack Overflow, or a hack blog writer churning out articles with titles like "20 dumb things Trump has said", AI is coming for your job — but that's because your job wasn't worth anything to begin with.

There's a lot of money on the side wanting to use AI (see Microsoft), and geopolitical concerns. Example: If EU or America tightly regulates AI, China could run with it and use it to dominate certain industries. Best case scenario: light/no/ineffective regulation Worst case scenario: regulation takes AI away from the people, but big corporations still get to use it. There's already talk of surveillance of cloud providers to watch for AI training, and restrictions on purchasing AI hardware. https://cyber.fsi.stanford.edu/io/news/forecasting-potential-misuses-language-models-disinformation-campaigns-and-how-reduce-risk https://arxiv.org/abs/2301.04246

@kano I think you are spot on with that assessment (unfortunately), at least for the next 10-15 years. As with pretty much everything tech I would love it if the commons could produce a viable non-proprietary competitor. Unfortunately the massive amount of work, data, and processing power it takes to train one of these bots simply necessitates major corporate or government backing. That may change as the field matures and people start figuring out what makes these bots work. Human infants are able to learn to speak with far, far, far, far, FAR less language exposure than it takes even the most primitive chat bots to approximate coherent fluency. That's because a human brain is not a single undifferentiated mass of neurons. Our brains come pre-divided into function oriented sub modules, pre-populated with effective neural configurations for their specific tasks. By contrast, an undifferentiated mass really is more or less how these bots start out. 99% of all that training they need is just getting them to the starting line of approximating any sort of receptive brain configuration. Once people start cracking the code though that whole process will become much more efficient. Assuming our current society survives, people will eventually be able to buy pre-configured bot-brain-parts to train and run on their home computers for a build-your-own AI companion experience. We are still in early days of this technology. Incidentally that's why I'm skeptical of any claims that the hallucinations these bots continue to exhibit are a feature to the people building them, rather than a bug. I'm sure we will see that eventually (truth by Google...), but for right now it is hard enough just to get these bots to stop spouting racial slurs. Teaching them to double think on top of that is too much work... for now.

I'm NOT talking about "AI" but about "large language model" and that's the SAME thing people do (they DON'T think, they just apply learned patterns in their work) You misread my post, I'm saying people are "stupid" just like the LLMs "The human brain is capable of so many things machines couldn't even "think about" doing" And I'm saying people DON'T use brain capabilities when working, they use patterns.

It gave a link to Minecraft mod for some reason, but the answer is pretty good. I find Bing to be more truthful than at least the free version of ChatGPT. I had a conversation with Bing the other day and it wrote me a plugin for Blender, even though I don't know any Python. It took couple of hours, but it went better than my previous attempt using ChatGPT. 119 lines of code, nothing too complicated. Of course there are memory limitations to how long the generated code can be, but that's not going to be a big limitation for too long given the speed of progress we've been seeing. Large language models "only" predict words, but as some people pointed out, if you want to predict text accurately, at some point you have to start to "understand" what you talk about, whatever that means. I recently watched this interview with AI researcher Geoffrey Hinton and he shares this view. Physicist Sabine Hossenfelder also says something similar. On the other hand we know that those models don't think like we do. I've seen this interview with an interesting example. If you ask Bing: "A rose is a rose, a dax is a _" it gets confused. In my opinion that's a fairly intelligent response, even if the bot needed some help.

ChatGPT is a digital parrot** that takes our own words & designs mashes them up & hands the result back to us as something original, it isn't It tells lies, when called on it's lies, it doubles down creating spurious links to back up it's bullshit, the links it makes are fragments of other links bolted together because that looks like the links in the data it's been trained on It is not AI it's a large language model neural network, it has no understanding of what it says because it hasn't got the capacity to understand, it's output is a statistical best fit to it's training data It's output looks like natural language because that's what it's been trained on, some people think this means it's intelligent You ask it for "A couple of paragraphs about the band Pink Floyd", it will mash up some words about "the band Pink Floyd", some of it will be accurate, it won't tell you anything that hasn't already been published & it could cheerfully tell you that they went down with the Titanic because it's training data mentioned "The band played on" & that was in the question ChatGPT and all LLM's need to die in a fucking fire before some moron decides to use one to make decisions that affect real people **Apologies to parrots everywhere they have intelligence, unlike LLM's

Thanks for the replies, gonna try those spoiler Tags again now for my short review (oh well it inserted one above my text now and I can't seem to delete it on mobile - this text editor is strange)

Just finished this mission and wow I gotta say in great honor to Grayman and of course the rest of the team picking it up, this was something I've never seen before in any other TDM mission, especially visually wise. I am so happy that grayson gave green light for other experienced mappers to finish his last mission. And what came out of this is really something special. I'll put my review in spoiler tags since I'm now referring to critical mission details. Edit - How do I put spoiler text here on mobile?? [spoiler] test [/spoiler][SPOILER] test [/SPOILER] [spoiler[spoiler [sfah

You can try my alternative footstep sounds package which addressed the things you described together with a lot of other footstep sounds both for player and AI if you want to. https://forums.thedarkmod.com/index.php?/topic/17631-new-footstep-sounds/

Mods can this moved again? @Acolytesix- can you make sure you post in the beta thread instead of this one please (this one is public, the beta thread is only for logged-in forum members): https://forums.thedarkmod.com/index.php?/topic/21822-beta-testing-high-expectations/

sure - I would only ask that you follow the thread to make sure you don't report stuff that has already been mentioned: https://forums.thedarkmod.com/index.php?/topic/21822-beta-testing-high-expectations/

IMO there's some benefits to using "" around paths, one it permits you to put spaces in your paths (thou I don't recommend that at all), second it breaks your paths into easier strings, for the text parser to read/deal with, it also help us visually distinguish what's is what better. They aren't a rule you can ignore them but imo using them maybe decreases the probably of parsing errors. About lower case, I'm not sure but unless you are comparing strings, I don't think the parser itself cares about the case of character in a string. Thou because of portability to linux and other OS's idSoftware recommended, no spaces in folder names and no higher case letters in a path, the engine even has a warning message just for that. But like you see above, even I forget that sometimes, is why I have plenty of warnings about non portable paths in the console!

Market area and restaurant with the basic outside detail done. It was thankfully easy to create a colorized / toggleable version of the new lampion model: Only disadvantage is you don't see a light source inside which sucks a little, might end up using a flame like for candles later. The ones on strings swing which gives off a nice effect as the light moves around!

heh i was thinking the same though it might just have been a glitch when writing the names are pretty similar. But for correctness it is called the dark engine and the newer version that allows us to run these beauties on win10/11 is called newdark. newdark is kinda interresting as it just suddenly popped up on a french forum some time ago by an anonymous developer with the alias le corbeau who allegedly got his hands on the original source code and started updating it for modern OS. this was the original thread i believe -> https://www.ttlg.com/forums/showthread.php?t=140085 bikerdude was on that forum to when the patch hit i noticed hehe.

Okay, I had no idea, I have googled it up now and you are right, to my own surprise. Done, I´ve put some paragraphs which were previously not in spoiler tags into spoilers.