• Future of computing? Analog vs. digital for very powerful AI algorithms.

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    Analog computers have been used mostly for solving differential equations. They are much faster doing this than digital computers, but are not as precise, so they are not always appropriate when great numerical precision actually matters very much.

    One very different and also really old and, in a highly evolved form, new again application of both analog and digital computers is in the implementation of neural network algorithms (AI). The first such network, the simplest one, initially run in a digital computer and later in an analog one, was the “Perceptron”, invented back in the late 1950s. It was hugely hyped saying it would do things well beyond what it really could do. And then the hype self-destroyed, starting the first “AI winter”, when work on AI was pretty much in suspended animation, if not actually dead.
    The first such “winter”, but not the last, because hype come back when people started to work on these algorithms again, and then the field crashed again because of it.

    Now days these algorithms are used for increasingly more important and interesting purposes and are being trained with the help of huge databases. For this, large digital server farms are used that consume great amounts of power, particularly during the training process.

    As shown in this video “We are building computers wrong”, new developments on analog hardware might provide a way to use much smaller computers just as powerful as those huge digital server farms and using much more modest amounts of electrical energy to get the same or better results.

    Of course, whether the development of effective and powerful AI algorithms is good or evil depends on which weights one prefers to give to the good things that might be possible, e.g. better help at home for old people and invalids, versus the awful ones, such as working people being displaced by robots from their jobs.

    Interested? Then have a look:

    https://www.veritasium.com/videos/2022/3/2/were-building-computers-wrong

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