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  1. About. Architext is the world’s first semantic generation platform for Architecture. Using nothing more than plain language, users are albe to generate a rich variety of residential floorplans. This enables anyone to produce a nearly infinite set of creative designs, regardless of skill level or background.

  2. en.wikipedia.org › wiki › ArchitectArchitect - Wikipedia

    An architect is a person who plans, designs, and oversees the construction of buildings. [1] . To practice architecture means to provide services in connection with the design of buildings and the space within the site surrounding the buildings that have human occupancy or use as their principal purpose. [2] .

  3. Excite originally started as Architext in June 1993 in Cupertino, California, created by Graham Spencer, Joe Kraus, Mark VanHaren, Ryan McIntyre, Ben Lutch and Martin Reinfried, who were all students at Stanford University. The goal was to create software to manage the vast information on the World Wide Web.

  4. Architextuality is the designation of a text as a part of a genre or genres. Metatextuality is the explicit or implicit critical commentary of one text on another text.

  5. This allows architext to enable and end-to-end design workflow that is able to ideate, explore, evaluate and generate diverse collections of well-performing designs for different project constraints and goals. All with the use of language. Produce architectural designs directly from natural language. Machine learning for AEC design.

  6. en.wikipedia.org › wiki › ArchitectureArchitecture - Wikipedia

    It is both the process and the product of sketching, conceiving, [4] planning, designing, and constructing buildings or other structures. [5] The term comes from Latin architectura; from Ancient Greek ἀρχιτέκτων (arkhitéktōn) 'architect'; from ἀρχι- (arkhi-) 'chief', and τέκτων (téktōn) 'creator'.

  7. Architext, a novel semantic generation assistive tool. Architext enables design generation with only natural language prompts, given to large-scale Language Models, as input. We conduct a thorough quantitative evaluation of Architexts downstream task performance, focusing on semantic accuracy