The immediate catalyst, it seems, is an intensifying focus on capex, or capital expenditures. Microsoft revealed that its spending surged 66% to $37.5 billion in the latest quarter, even as growth in its Azure cloud business cooled slightly. Even more concerning to analysts, however, was a new disclosure that approximately 45% of the company’s $625 billion in remaining performance obligations (RPO)—a key measure of future cloud contracts—is tied directly to OpenAI, the company revealed after reporting earnings Wednesday afternoon. (Microsoft is both a major investor in and a provider of cloud-computing services to OpenAI.)
Which kind of illustrates the fundamental flaw right? Videogame companies have spent decades creating replayable DnD esc experiences that are far more memory efficient and cost effective. They already kind of do it the best way. AI can assist, and things like the machine learning behind the behaviors of the NPCs in Arc Raiders for example is very cool, but as you said, you need a custom program… which is what a video game is, so I guess my point is I don’t see the appeal in re-inventing it through sort of automated reverse engineering.
LLMs could theoretically give a game a lot more flexibility, by responding dynamically to player actions and creating custom dialogue, etc. but, as you say, it would work best as a module within an existing framework.
I bet some of the big game dev companies are already experimenting with this, and in a few years (maybe a decade considering how long it takes to develop a AAA title these days) we will see RPGs with NPCs you can actually chat with, which remain in-character, and respond to what you do. Of course that would probably mean API calls to the publisher’s server where the custom models are run, with all of the downsides that entails.