“We might deal in derivative IP, but it’s our derivative IP!”
Derivative over generative any day if you ask me.
Derivative IP is so fucking different from gen AI. It’s stupid IP laws that force what could have been a commercial fangame to instead be legally distinct.
I think it could work to give dynamic and varied answers to secondary characters given good prompts and other guardrails to preserve the immersion. As long as the core elements of the games are not AI generated slope, and developers are honest about where it was used.
As an amateur game dev, I believe AI will crash out for the public before it becomes truly useful for programming. I’ve heard colleagues try to use AI , but it often just creates more work. When the AI doesn’t know the answer, which is often. it makes something up, leading to errors, crashes, or hidden issues like memory leaks. I’d rather write the code correctly from the start and understand how it works, than spend hours hunting down problems in AI-generated code, only to never find the issue. Full disclosure I use Chatgpt to edit my dialogue as my English is not great.
I am using them as a side tool for development. I think LLMs are already very performent for web knowledge search (e.g. replacing a search on stackoverflow), suggestions, explanations and error detection. Although is it worth the resources consumption? Not sure, but I can’t afford not staying on top of the tooling available for my job. However, I agree, in my experience, the edit/agent modes are not efficient for coding, for now.
Generating secondary dialogues for a video game is quite a lower quality requirement than software engineering. So I think it could work there. It requires sounding natural, not being exact, LLMs are good at this.
web knowledge search
yeah for low stakes how-tos I’ve been asking more and more using one of the free LLMs. For higher stakes I ask for their sources if they can give it and go from them on my own.
It’s been really nice to be able to type a plain question (in any language) into Google and receive a concise answer before scrolling down to confirm with more trustworthy sources. In particular it’s been very good for solving annoyances with UI options by directing me to exactly what I’m looking for. A traditional search will often conflate my search with synonyms (even when using quotations, which is some bullshit), and even ignore what language my search was in.
e: Also you should be careful when clicking on any links provided by an LLM because they can accidentally send you phishing links.
SEO destroyed google’s usefulness. AI is a cope for that but AI kills the incentives for very thing it depends on for it’s usefulness, user generated content.
My anecdote for AI and coding is that it’s a good replacement for google searching, especially when you are learning a new language.
You need to understand the fundamentals first, but asking the AI how to do a task in C when you’ve only coded in JS is very helpful. It’s still wrong, but it’s not like Stack Overflow is more accurate.
We don’t believe in AI, says the developer of AI Art Impostor
With how badly that game was received, maybe they understood the point. Maybe
Pocketpair Publishing boss John Buckley
Any relation to loss guy?
Isn’t that Garfield’s owner
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Nonsense. Procedural generation is a rule-based deterministic system while generative AI is probabilistic and data driven. It’s fundamentally different.
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It’s less of a functional different and more of a moral one.
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I think it can - procedural generation consist of procedures, that is elements designed by humans, which are just connected into a bigger structure. Every single template, rule and atomic object (e.g. a single room in a generated house) is hand-designed, and as such no matter what comes out the elements and connections were considered by a real human. On the other hand, generative AI is almost always some sort of machine learning, that is an approximation of what a good structure of something should be, but it is only a very poor, randomised approximation. You have absolutely no guarantees nor constraints on what might pop out of the model - that is my main concern with genAI, though the whole outputted thing looks reasonable, upon closer inspection it has a lot of inconsistenties.
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You don’t need any preexisting training data for procedural generation
Where are all these prompt based image generators that identify themselves as procedural generation?
