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  • The real miracle of AI is that it could work with these prompts at all

    "now char coming but movement everything wrong ... prince is not in floor"

    I'm a games developer and I have no idea what OP is asking for here.

  • I see a lot of these attempts at getting a model to replicate a classic game. I'm sure this is a use case with some interest, not everyone wants to spin up an emulator, but it strikes me as odd. Rather than English being the new high level language for programming, the LLMs is handed a finished game as a specification and asked to copy it.

    That gets you past the problem of the lack of specificity in English, but requires you to already have the thing you want to get made. At least tokens are cheap.

  • Off tangent but the latest prince of Persia game is really fun
  • This isn't really comparing the models; he's using successive models to improve his rebuild of Prince of Persia. Either way though, it will be interesting to see which games, if any, resist implementation via LLM. I recently started a Starcraft 2 like real time strategy game with Fable managing many Opus agents and it got to a playable 3d game with 3 races, 40+ units, and 40+ buildings in 3 days.
  • The prompts provided are atrocious. It's amazing that the LLMs actually built something useful.

    > My first prompt was simple: "in this original code there 6502 assembly code for prince of persia, use the save level files and try to do it in c# console."

    Do what in the what now in the console?

  • Instead of fixing a broken version, maybe each model should have started from scratch
  • I am going to try to build the original Prince of Persia using Swift as it is the best language for building a macOS game. Being a classic 2D cinematic platformer, Apple's native frameworks provide exactly what I need without the overhead of a massive cross-platform engine, and I love simplicity

    So here goes my weekend, flag this and get a life

  • A German magazine (c't) ran a Asteroids programming contest in 2008 - create a client with access to the emulator output of the game that provides keyboard inputs to control the game.

    The highest scoring submission that won the contest had a high score of around 137k. Last week, I had GPT-6 Astra, Sol and Luna implement and hill-climb on this task, as I wanted to see how big the difference in smartness is. Luna implemented something, but never exceeded ca. 20k points, with a large variance. Sol got something in the area of the humans implementation.

    Astra, which finished fastest, had a highscore of around 1.7Mm when the game seemed to fairly reliably crash. On the way, it disassembled parts of the ROM to extract information about the game.

    I didn't do a ton work to document and measure the specifics, but it was very impressive.

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