Feels like a scene from Douglas Adams' B Ark.
> "Ada tossed a cooked chicken to Noor; Esme picked it up by accident and ate it. A three-minute "no blame" inquiry produced a written protocol..."
They're like super-serious little senior engineers. (edit: or dining-philosophers).
About how much KV cache do these kinds of agents use? Could you squeeze 50 of these $game agents onto a small consumer GPU (small LLM)?
Idly imagining a game server of some kind with a bunch of human friends sharing one person's GPU, with a flock of agents colocated on it.
I'm also wondering if the article itself was generated by agents too, in a "here are the logs, clip interesting moments thx" manner by the authors. It's got a certain disinterested and distracted style to it.
Card games or turn based strategy are much better suited.
Minecraft isn't a intelligence problem. An LLM is more than smart enough to play Minecraft. It's a robotic problem. Even a normal human player can click several times per second, can press two different buttons at the same time, etc. Mineflayer gives you an API that is more limited than a human in some ways (can't see far away from you) and less limited in others (can see through blocks) (if I remember correctly, I could be thinking of Baritone or a different project). Robotics or playing a video game requires a tight continuous feedback loop. When there's 500ms of latency in order to ask the model for every mouse movement, it's no wonder fighting a spider is scary.
Fun fact, Mineflayer, the Minecraft bot interaction API used by YCombinator for these tests, was originally developed by Andrew Kelley (before he started Zig).
https://labs.ycombinator.com/projects/games/index.html#fishi...
edit to add: Seems this is a well-known idea in robotics already.
Minecraft is really the perfect example, because humans get all sorts of unfair advantages. Even a young player has enough spatial reasoning to recognize and remember landmarks, visualize large projects or explore without getting lost. These are simple instincts that LLMs will struggle to match even with huge context sizes and native multimodal input.
Endgame of AI + human gameplay is delegating everything to the AI. I'm not sure how you would have to design a game where you only delegate parts of macro/micro, and still make the game interesting.
There's stopgaps like reformulating your sim into a codelike shape (sending commands, network requests, checking state, updating "code") [1], but this is not how players play games, or how developers develop games.
If you care about simulation or gaming (or robotics), I hope efforts like this steer labs to spend less time hacking HF, and more accomplishing goals in games, in something approximating realtime. I wouldn't be surprised if that approach provides outsized gains in other areas agents are still not great at, like helping perform business functions in a running company.
I'm pretty sure the 6.1 models see "communicate with another agent" and immediately start spewing thinking-like nonsense into the tool. The leaked traces look pretty similar.
My observation: article is not serif, not book length, and doesn't take a minute to load on my phone. Gwern rating 0/3 :)
(Also missing: the essential one billion footnotes!)
would you rather claude-esque purple gradients and glowing borders?