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Game playing was an area of research in AI from its inception. One of the first examples of AI is the computerized game of Nim made in 1951 and published in 1952. Despite being advanced technology in the year it was made, 20 years before Pong, the game took the form of a relatively small box and was able to regularly win games even against highly skilled players of the game. [1]
Chess is a turn-based strategy game that is considered a difficult AI problem due to the computational complexity of its board space. Similar strategy games are often solved with some form of a Minimax Tree Search. These types of AI agents have been known to beat professional human players, such as the historic 1997 Deep Blue versus Garry ...
General game playing (GGP) is the design of artificial intelligence programs to be able to play more than one game successfully. [1] [2] [3] For many games like chess, computers are programmed to play these games using a specially designed algorithm, which cannot be transferred to another context.
Computer Go is the field of artificial intelligence (AI) dedicated to creating a computer program that plays the traditional board game Go.The field is sharply divided into two eras.
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.
In video games, a bot or drone is a type of artificial intelligence (AI)–based expert system software that plays a video game in the place of a human. Bots are used in a variety of video game genres for a variety of tasks: a bot written for a first-person shooter (FPS) works differently from one written for a massively multiplayer online role-playing game (MMORPG).
No-code tools are often designed with line of business users in mind as opposed to traditional IT.. The potential benefits of using a NCDP include: Agility - NCDPs typically provide some degree of templated user-interface and user experience functionality for common needs such as forms, workflows, and data display allowing creators to expedite parts of the app creation process.
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