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AI Dungeon is a text adventure game that uses artificial intelligence to generate random storylines in response to player-submitted stimuli. [1] [2] [3] [4]In the game, players are prompted to choose a setting for their adventure (e.g. fantasy, mystery, apocalyptic, cyberpunk, zombies), [5] [6] followed by other options relevant to the setting (such as character class for fantasy settings).
Dream Machine is a text-to-video model created by Luma Labs and launched in June 2024. It generates video output based on user prompts or still images. Dream Machine has been noted for its ability to realistically capture motion, while some critics have remarked upon the lack of transparency about its training data.
Generative AI features have been integrated into a variety of existing commercially available products such as Microsoft Office (Microsoft Copilot), [85] Google Photos, [86] and the Adobe Suite (Adobe Firefly). [87] Many generative AI models are also available as open-source software, including Stable Diffusion and the LLaMA [88] language model.
The game follows the rise of a self-improving AI tasked with maximizing paperclip production, [6] a directive it takes to the logical extreme. An activity log records the player’s accomplishments while giving glimpses into the AI's occasionally unsettling thoughts. [7] [failed verification] All game interaction is done through pressing buttons.
In 100 shogi games against Elmo (World Computer Shogi Championship 27 summer 2017 tournament version with YaneuraOu 4.73 search), AlphaZero won 90 times, lost 8 times and drew twice. [11] As in the chess games, each program got one minute per move, and Elmo was given 64 threads and a hash size of 1 GB. [2]
A prompt for a text-to-text language model can be a query, a command, or a longer statement including context, instructions, and conversation history. Prompt engineering may involve phrasing a query, specifying a style, choice of words and grammar, [ 3 ] providing relevant context, or describing a character for the AI to mimic.
Twine emphasizes the visual structure of hypertext, and does not require knowledge of a programming language as many other game development tools do. [5] It is regarded as a tool which can be used by anyone interested in interactive fiction and experimental games. [5] [6]
MuZero (MZ) is a combination of the high-performance planning of the AlphaZero (AZ) algorithm with approaches to model-free reinforcement learning. The combination allows for more efficient training in classical planning regimes, such as Go, while also handling domains with much more complex inputs at each stage, such as visual video games.