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With first Claude and now Gemini playing Pokemon, I was thinking of doing my own game-playing experiment over the weekend. However, I quickly learned that it's very far from the VLA-style "pixels->plan" that I naively thought it was, and wanted to do myself. It's like 90%… https://t.co/5cVrbmYArc
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"text": "With first Claude and now Gemini playing Pokemon, I was thinking of doing my own game-playing experiment over the weekend.\n\nHowever, I quickly learned that it's very far from the VLA-style \"pixels->plan\" that I naively thought it was, and wanted to do myself.\n\nIt's like 90% harness, 10% model. Not raw pixels. A lot of info is extracted from the game's RAM, rendered on top of screenshots, given in the prompt. A lot of game-specific instructions and tools are given to the model. And, importantly, the harness is continuously \"improved\" as the game progresses (and the model gets stuck).\n\nIt's ironic, because about a year ago I had a chat with a person from GDM working on rl+games, we discussed what they work on and they asked me if I think Gemini, just given game screens, could it just play? I said of course not, unless someone put tons of replays from that game, with actions, in the training. But I bet nobody did, because why spend budget on that? The person confirmed the team ran the experiment and it can't, and were surprised I predicted that.\n\nSo I thought with (Claude/Gemini) Plays Pokemon, maybe we made huge progress. But not really, give them unannotated screenshots and light instructions, and they don't even get the first level.\n\nThe Pokemon streams are fun, but progress is made more by the scaffold builders than the models.\n\n@a1zhang and @OfirPress are building a benchmark with a lighter scaffold and more games in the open (VGbench).\n@Lanxiang_Hu, Qiyu Li, and Anze Xie are building LMGameArena with a unified/simple scaffold and a leaderboard.\n\nLinks and sources with a lot more details in next tweet.",
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"full_text": "@giffmana Generalisation is building the game and then playing the game\n\nIt's futile for AGI gamebenchmark if it doesn't build the game first (yes humans retrospectively understand gamebuild by playing it) \n\nSo far only claude3.7 can replicate pokemon gameboy games in code ≈ 70%",
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"text": "Agreed. LLMs are surprisingly bad in ASCII roguelikes or gym envs too. I say \"surprisingly\", because there's certainly that sort of data in the pretraining set, so while I can kinda understand pixels -> actions failing (there's just nothing in pretraining for that), I'd have expected better performance on Nethack and such. Hell, even SOTA models still struggle with tic-tac toe, or that simple taxi env in gymnasium (can't even get grid positions in a 5x5 grid right)\n\nSomething is clearly missing. Could just be as simple as a robust finetune (that demo of Llama-7b playing doom with ASCII graphics showed it's maybe enough). Working on it",
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"full_text": "@giffmana Agreed. LLMs are surprisingly bad in ASCII roguelikes or gym envs too. I say \"surprisingly\", because there's certainly that sort of data in the pretraining set, so while I can kinda understand pixels -> actions failing (there's just nothing in pretraining for that), I'd have…",
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"text": "It actually heavily depends on the game. Both models know Pokemon by heart already (training data) and they know exactly what they need to do next at every given observation. The main reason you still have the harness is efficiency, especially in navigation. I‘m very sure both models could play almost the entirety of the game fully black box at this point, but it would be unwatchable since 90% of it would just be trying to slowly get from point A to B (and also there will be some reaction-based interactions they would probably not be able to perform). (Source: we‘ve literally done the exact same demo and benchmark one year ago already, its on our website)",
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"full_text": "@giffmana It actually heavily depends on the game. Both models know Pokemon by heart already (training data) and they know exactly what they need to do next at every given observation. The main reason you still have the harness is efficiency, especially in navigation. I‘m very sure both…",
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