spacemaker
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Artificial intelligence (AI) promises to revolutionize our present world. Instead, it's all about computer algorithms doing complex, interpretive tasks efficiently and, dare we say it, intelligently. One area where the promise seems particularly bright is architecture. In many ways, AI is the perfect tool for this field. There's always an element of artistry when it comes to design for buildings and outdoor spaces, but there are a ton of calculations to consider too.
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Autodesk is buying Norwegian construction AI firm for $240M
Autodesk Inc. (Nasdaq: ADSK) said it has signed a definitive agreement to acquire Spacemaker for $240 million net of cash. The acquisition will provide the San Rafael-based design and manufacturing software maker with a powerful platform to drive modern, user-centric automation -- powered by artificial intelligence -- and accelerate outcome-based design capabilities for architects, according to the company. Based in Oslo, Norway, Spacemaker uses cloud-based AI and generative design to help architects, urban designers, and real estate developers make more informed early-stage design decisions faster and enables improved opportunities for sustainability from the start. By evaluating the best options from the outset, Spacemaker is said to help architects maximize their clients' long-term property investments. The transaction is subject to customary closing conditions and is expected to close during Autodesk's fourth quarter of fiscal 2021, ending Jan. 31, 2021.
Stanislas Chaillou, founder of CitiX, brings background in the use of generative adversarial networks in architecture to Spacemaker
Stanislas will join Spacemaker.ai as a Data Scientist and Architect. He received his undergraduate degree in Architecture at the Swiss Federal Institute of Technology of Lausanne, and his Master in Architecture from Harvard University. Focusing his practice around Architecture and Technology, his work mainly tackles the integration of Artificial Intelligence in the design process. More specifically, Stanislas' Master thesis investigated the possibilities offered by recent generative models, such as Generative Adversarial Neural Networks. Leveraging nested GAN models, Stanislas implemented a generative "stack", allowing designers and architect to draw seamlessly potential architectural design options.
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