>The game runs on Windows, the audio processing and brain runs on my M4 MacBook. It could all run on Windows (provided there is dedicated ~12gb or more gpu ram for it)
I do wonder if this is an avenue for console gaming that might be practical in a few years; AI-centric hardware that might be too beefy or expensive for regular users, but can extend new or existing games. Kinda like the expansion paks of old.
unfortunate that the "ALE" design wasn't opensourced (couldn't find a link in their post) but I would be interested in learning more about the design, in particular what sort of data pipeline was necessary from skyrim to give this sort of action flexibility?
I will be open sourcing it soon :) my code is a bit dirty (the whole system is 3 pieces. The game adapter / a websocket bridge between game and brain / the brain itself) and it runs on 2 different (local) machines currently.
Ale is what makes this work locally, I felt a little conscious about it as I am not sure if it is a novel approach or somebody comes out and claims I rediscovered BERT or something (though ale runs at 1/10 the cost of BERT).
Hello, author here. I was intentionally a little vague about this because this is kind of the thing that makes the whole approach work.
An LLM predicts the next token. If you're trying to predict the next token in a mathematics competition, or while playing a deep strategy game, being a much larger and more capable model helps enormously. To predict that next token correctly, the model effectively needs to model a bunch of possible future states - even if that is a second order (unintended) effect, it is what is seems to be happening.
This is basically the Ilya (and Dario) argument that prediction, understanding, and compression are the same thing (deep rabbit hole) from a few years ago.
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In my opinion; this is a beautiful idea, but videogames do not need most of that. Videogames (and games in general) shine when character behavior is predictable, and when NPCs are a little dumb (just a little).
We already have very good small roleplaying models — Qwen 3.5 4B/9B/30B-A3B. Nowhere near frontier models at general reasoning. But they can act and write in a very engaging way. Good at roleplaying but very weak at reasoning. They just need a little nudge at reasoning...
And that's the key. The player has already expressed their intent: attack that guy, go look over there, cover me, find the key that shines and is golden, etc. A constrained world, with a constrained set of actions. Instead of asking the model to reason over an enormous space of possible futures, we're mostly asking it to map: player intent + current world state → a small sequence of plausible actions.
As for the "dump context to an LLM". It's basically. "You are roleplaying as X - you experienced Y - you like/dislike (dispositions) Z, you remember Alpha, your journal says Delta. Player orders you to do Gamma. - "What do you respond and do?"
It kind of works (as you can see in the videos I posted). I am not going against the grain, big models are better, but do we need those models for everything?
I must say absolutely hilarious video. The "persona" of the dog is great. As someone who is generally pretty "keep your AI out of my art" this looks very fun to play. I can imagine this being cleverly integrated as a primary feature of a game (this must already be in the works). Ideally as a small model able to run locally alongside the game.
The moment where the dog is going on about "something foul in the air" as the player is attacked by a wolf ("F--- dude you could have warned me!") was great comedy.
It's expensive, early attempts didn't impress, and many gamers are hostile to the tech because it threatens the livelihood of game creators and impacts gaming hardware prices.
>The game runs on Windows, the audio processing and brain runs on my M4 MacBook. It could all run on Windows (provided there is dedicated ~12gb or more gpu ram for it)
I do wonder if this is an avenue for console gaming that might be practical in a few years; AI-centric hardware that might be too beefy or expensive for regular users, but can extend new or existing games. Kinda like the expansion paks of old.
unfortunate that the "ALE" design wasn't opensourced (couldn't find a link in their post) but I would be interested in learning more about the design, in particular what sort of data pipeline was necessary from skyrim to give this sort of action flexibility?
I will be open sourcing it soon :) my code is a bit dirty (the whole system is 3 pieces. The game adapter / a websocket bridge between game and brain / the brain itself) and it runs on 2 different (local) machines currently.
Ale is what makes this work locally, I felt a little conscious about it as I am not sure if it is a novel approach or somebody comes out and claims I rediscovered BERT or something (though ale runs at 1/10 the cost of BERT).
I like the approach here. It’s cleverer than just “dump context to LLM”. I couldn’t quite figure out if it genuinely runs purely locally though.
If nothing else - this is how NPCs should work in games moving forward!
Hello, author here. I was intentionally a little vague about this because this is kind of the thing that makes the whole approach work.
An LLM predicts the next token. If you're trying to predict the next token in a mathematics competition, or while playing a deep strategy game, being a much larger and more capable model helps enormously. To predict that next token correctly, the model effectively needs to model a bunch of possible future states - even if that is a second order (unintended) effect, it is what is seems to be happening.
This is basically the Ilya (and Dario) argument that prediction, understanding, and compression are the same thing (deep rabbit hole) from a few years ago.
----
In my opinion; this is a beautiful idea, but videogames do not need most of that. Videogames (and games in general) shine when character behavior is predictable, and when NPCs are a little dumb (just a little).
We already have very good small roleplaying models — Qwen 3.5 4B/9B/30B-A3B. Nowhere near frontier models at general reasoning. But they can act and write in a very engaging way. Good at roleplaying but very weak at reasoning. They just need a little nudge at reasoning...
And that's the key. The player has already expressed their intent: attack that guy, go look over there, cover me, find the key that shines and is golden, etc. A constrained world, with a constrained set of actions. Instead of asking the model to reason over an enormous space of possible futures, we're mostly asking it to map: player intent + current world state → a small sequence of plausible actions.
As for the "dump context to an LLM". It's basically. "You are roleplaying as X - you experienced Y - you like/dislike (dispositions) Z, you remember Alpha, your journal says Delta. Player orders you to do Gamma. - "What do you respond and do?"
It kind of works (as you can see in the videos I posted). I am not going against the grain, big models are better, but do we need those models for everything?
Love the concept of void mode. A companion that follows you across games, that's cool.
I must say absolutely hilarious video. The "persona" of the dog is great. As someone who is generally pretty "keep your AI out of my art" this looks very fun to play. I can imagine this being cleverly integrated as a primary feature of a game (this must already be in the works). Ideally as a small model able to run locally alongside the game.
The moment where the dog is going on about "something foul in the air" as the player is attacked by a wolf ("F--- dude you could have warned me!") was great comedy.
New mediums always absolutely knock the humanity organism for a bit
Video game seem like the perfect fit for llm use and I don't understand why it hasn't happened already.
It's expensive, early attempts didn't impress, and many gamers are hostile to the tech because it threatens the livelihood of game creators and impacts gaming hardware prices.