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“Genetic improvement involves writing an automated “programmer” who manipulates the source code of a piece of through trial and error with a view to making it work more efficiently. This might include swapping lines of code around, deleting lines and inserting new ones – very much like a human programmer. Each manipulation is then tested against some quality measure to determine if the new version of the code is an improvement over the old version. It is about taking large software systems and altering them slightly to achieve better results. Read more

Remember a few weeks back, when we learned that Google’s artificial neural network was having creepy daydreams, turning buildings into acid trips and landscapes into Magic Eye pictures? Well, prepare to never sleep again, because last week, Google made its “inceptionism” algorithm available to the public, and the nightmarish images are cropping up everywhere.

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“It has taken time for neural networks, initially conceived 50 years ago, to become accepted parts of information technology applications. After a flurry of interest in the 1990s, supported in part by the development of highly specialized integrated circuits designed to overcome their poor performance on conventional computers, neural networks were outperformed by other algorithms, such as support vector machines in image processing and Gaussian models in speech recognition.” Read more

“The first marketable, personal computers in the late 70s came about after almost 40 years of research and development, which created the technology at public expense. One of the peculiarities, if you’d like, of our system of innovation and development is that it’s radically anti-capitalist in many ways…People who paid taxes in the 50s and 60s may not have known it, but they were creating what was ultimately marketed by Apple. But they don’t get any of the profit. I think that’s a social pathology and the same carries over into space.” Read more