What happens when we teach a computer how to learn? Technologist Jeremy Howard shares some surprising new developments in the fast-moving field of deep learning, a technique that can give computers the ability to learn Chinese, or to recognize objects in photos, or to help think through a medical diagnosis. (One deep learning tool, after watching hours of YouTube, taught itself the concept of “cats.”) Get caught up on a field that will change the way the computers around you behave … sooner than you probably think.
Ex Machina looks unlike any science fiction film you’ve seen lately. Its mostly subterranean location is opulent and claustrophobic—and then there’s Ava, the eerily beautiful robot. Check out an exclusive clip from the DVD’s special features, and our interview with the film’s production designer, Mark Digby.http://www.amazon.com/Ex-Machina-Cor... Ex Machina Ex Machina Ex Machina Amazon.com: $14.97 Buy now
"Brass Swarm is an experimental prototype developed through self-organisational algorithmic design processes and robotic fabrication. The project explores spatial self-organisation, emergent tectonics and the relationship between robotic and algorithmic behavior."
Alessio Erioli's insight:
Brass Swarm, Prototype, Shanghai, 2015
Design Director: Roland Snooks
Project Team: Cam Newnham, Ben Verzijl
Fabrication Team: Zhao Sheng, Cai Yuan Zhen, Tang Yan Chao, Chen yu Lan, Xu Lei, Yan Lei, Zhang Wu
Brass Swarm is an experimental prototype developed through self-organisational algorithmic design processes and robotic fabrication. The project explores spatial self-organisation, emergent tectonics and the relationship between robotic and algorithmic behavior.
Kokkugia has developed a multi-agent algorithmic strategy for spatial self-organisation, from which topological surfaces emerge. This manifold swarm strategy self-organises clouds of agents into coherent, continuous surfaces, and complex spatial division. These spatial agents simultaneously generate the intricate tectonics of the project. Each agent has a body that is capable of interacting and connecting to the bodies of the surrounding agents. The interaction of these agentBodies generates intricate ornamental and structural networks.
The prototype is robotically fabricated through the interaction of two Kuka Agilus robots, which bend the brass rods comprising the agentBodies. The robots have a precise set of physical and mechanical constraints that limit the possible angles and direction of the bends. This behavior of the robots has been encoded within the generative algorithm to ensure that the agentBodies negotiate between highly volatile generative design behaviors and more pragmatic concerns of fabrication. This process compresses fabrication and design imperatives into a single process, removing the need to post-rationalize complex geometry with regard to fabrication criteria.
These multi-agent algorithmic processes are part of the Behavioral Formation strategy developed by Kokkugia. This strategy encodes architectural design decisions within computational agents that interact, giving rise to a self-organised design intention and an emergent architecture.
This project was supported by: RMIT University Architectural Robotics Lab & WITH International Design & Development (Yang Feng, Li Zhi Bin, Ye Xin).
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C. Orexis Artist Caitlin McCormack has created intricately crocheted the skeletal remains of different animals that are pinned to black backgrounds or encased in glass specimen jars. Many of these skeletal sculptures are available for purchase. McCormack
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