In the middle of the 20th century, computer science researchers began to explore what it would take to produce a responsive graphical interface to mediate the interactions between people and computers. By the mid-1980s, the results of this research took on the form of the graphics processing unit, or GPU. Do Graphics Processing Units Have Politics? traces this story back to its roots at the University of Utah, and then continues on to the early 2010s, when a different group of computing researchers stumbled across the startling efficacy of GPUs for what had been for decades a mostly unpopular and only moderately successful set of methods for developing 'artificial intelligence' programs: artificial neural networks. The collision between GPUs and neural networks electrified the computer science world, leading to the AI renaissance in which we currently find ourselves in the early 2020s. But the mesh between GPUs and neural networks requires a third ingredient: training data, and lots of it. Who
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