Suggesting that machines are rapidly gaining spatial and social sensibilities might sound futuristic, but actually the forces behind this transposition are two very old concepts in Silicon Valley years : artificial intelligence and spatial computing. Artificial intelligence now mostly consists of Machine Learning ; spatial computing is an umbrella term for everything used to collect information from the real world and then communicate it back to the environment around us.
The myth of computer simulations is of efficiency, and when it comes to daily tasks most people expect computer programs to be doing things like bookkeeping or the pixelpushing that photoshop used to be. But actually computer programs now are mostly working in the background, unnoticingly collecting data, adding it to data sets, learning from those sets and spreading to new areas of human life which can be, in turn, computed. He can learn all the languages and give each number a name. He would register the same dog in two different situations as two different creatures, seeing his own face in the mirror would always take him by surprise.
The first relates to the algorithms named deep neural networks.
Constantly tweaking and training deep neural networks, passing big amounts of data through their layers, each layer recognizing a pattern in the layer before it e. Ireneo Funes finally found salvation. So how did these recent breakthroughs in Machine Learning come to be?
Actually by a number of engineering achievements: cloud type server services able to host and process unimaginable amounts of data, connected to a diverse and exponentially growing horde of devices, through some very fast internet. The horde of devices part is the one to dwell on.pheycalsuppno.ml
Big practical guide to computer simulations /Alexander K. Hartmann. – National Library
In order to have huge amounts of data for your machines to feed on, it helps having cameras, microphones and other sensors sticking out of every hole. The iconic form of a computer involves a screen and a keyboard, though from its early days of conception it was clear that a computer can actually take any shape.
The ideal computer was already described in the 70s as being invisible. Any form of noticeable interface is just a distraction. We are, of course, not far from this desire — starting with the good old GPS, to newer forms of spatial tracking, and the omnipresent voice control moisture sensors in smart greenhouses, gyroscopes and compasses in moving computers — the types of sensors are trying to surpass the types of information.
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The dream of Smart Dust — computers so small they can float in the air and befriend microbes — seems almost as an overkill. Communicating information back to people with an invisible interface is a bit more tricky. The other ways to turn the computer boundaryless is to make people use virtual and augmented reality devices or to simply let objects communicate between themselves, while doing things on their own. Designed objects no longer need to be represented in distinct instances — 3d models are starting to be presented as a latent design space.
You can choose if you want your chair to be more of an arm chair or more of a stool Caitlin Mueller from MIT and others are working on making tools that help architects explore those endless spaces more intuitively. Ian Cheng , an artist with the appropriate background of cognitive science, names his works simulations.
Whether in virtual reality or on a screen, seeing his video games endlessly play themselves as a complex system of characters and sceneries is an experience nothing like watching a movie or a play. VR can also help achieve more practical results where other architectural mediums are failing.
Following the virtual tour the opinions changed dramatically from absolute disapproval to absolute approval the project was sacked — in the non-virtual reality you still have developers and politicians. The magic of contemporary computer simulations is bringing back the old practice of trying out architecture before building it.
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