It would be interesting if NPCs could react believably to free form input from the player, but that seems unlikely to be reliable. I'm not sure how you'd map the text to in game actions. Like, you could have the LLM respond with "ok I'll let you have my horse if you leave in the morning, and solve the zombie problem" but it's not trivial to make the game world respond to that. Not even counting it breaking out into "sorry as an LLM I can't ..."

You have optimism. It could be used for good like you describe, but most likely will be used by EA to cut artists out, slash costs, make as much profit as possible and suffocate the company until the private equity owners move on to the next company.

No, [that's exactly what this is about](https://insider-gaming.com/new-ea-owners-hoping-ai-will-cut-costs-and-boost-profits-its-claimed/).

Procedural generation with appropriate constraints and a connected game that stores and recalls what's been created can do this far better than a repurposed LLM. It's hard work on the front end but you have a much better idea of what the output will be vs. hoping the LLM "understands" and remembers the context as it goes.

I've seen prototypes of RPGs where you could freeform talk to NPCs and I pretty quickly lost enthusiasm for the idea after seeing it in action. It didn't feel like a DnD game where you're maneuvering a social conflict with the DM or other players, it felt more like jumping up on a table where an NPC couldn't get to you and stabbing them in the face.

Those poor players lol

What a fucking surprise.

They’re trying to cut costs to pay for the loans they took to make the acquisition


Sorry but procedural generation will never give you the same result as a well tuned small LLM can. Also there's no "hoping", LLM context preservation and dynamic memory can be easily fine-tuned even on micro models.

Yes it is trivial. LLM can already do tool calling, emotion metadata output and so on. It would take minimal effort for a well tuned model to also output things like facial expressions, body language, hand and body movements and so on.

I agree that the results will be different, and certainly a very narrowly trained LLM for conversation could have some potentials if it has proper guardrails. Which would work better is debatable and depends on the application. I've played around with plenty of fine tuned models, and they will get off track contextually with enough data. LLMs and procedural generation have a lot in common, but the latter is far easier to manage predictable outputs because of how the probability is used to create them.

Which is a different article about a (somewhat) unrelated topic. Using AI for development is already out there, and you can't put that genie back in the bottle. As an engineer I'm already using it in my daily work for tons of things - I've built separate agents to do a number of things: - read work tickets, collate resources, create a work plan, do the initial footwork (creating branches, moving tickets to the right states, creating Notion document with work plan and resources) - read relevant changes in UI design documents and plan + execute changes (still needs some manual review but e.g. with Android Jetpack Compose, it makes 90-95% of the needed work and requires minimal touch-up) - do structural work - boilerplates, etc. - write unit and integration tests, and already working out a UI test automation agent - do code reviews on changes, document them, and write appropriate commit messages - do PR reviews - I still review them myself but an extra eye is always helpful guess what, AI didn't replace me, it just allowed me to focus on actually thinking up solutions instead of doing hours of boilerplate stuff. AI isn't the enemy in software development. Companies who think they can replace engineers with AI. Middle managers will sooner be on that date, as they were mostly useless anyway.

The Saudis? ‍️

they should concentrate on disney ones.

You are going to get downvoted, but you're right. AI doesn't need to be used for every part of the entire development process for it to be "made with the help of AI". There are certain parts of the workflow that I'm sure is already being done regularly with AI, for example commenting code.

How do they reduce costs with AI if not by eliminating jobs?

What are these ass games you are talking about? Im willing to look past them being buggy.

I don't think it would be easy to map free form text to game behavior. Not just like "make the NPC smile" but complex behavior like "this NPC will now go to this location and take this action". That seems like it would be very error prone at best.

How do you think most game scripting engines work? Nowadays game engines don't rely on strictly speaking hardcoded behaviour, but rather are themselves just a scripting environment to execute a specific format of code. Skyrim is still the perfect example because it gives you the ability to literally do anything in the world, via a scripting language. Instructing NPCs to behave in a specific way is also done through these scripts. And LLMs - especially coding fine-tuned ones which could be tied into the execution chain - can easily translate things like `` to specific instructions so the NPC walks up and down at a specific distance or in a circle or whatever you want it to do. You're seriously over-estimating the work it takes on even crappy, but modern engines to get certain things to happen. Especially when it comes to things that are already dynamically scripted. Like NPCs.