How machine learning systems sometimes surprise us

This simple spreadsheet of machine learning foibles could not appear like a lot nevertheless it’s an interesting exploration of how machines “suppose.” The record, compiled by researcher Victoria Krakovna, describes numerous conditions through which robots adopted the spirit and the letter of the legislation on the similar time.

For instance, within the video under a machine studying algorithm discovered that it may rack up factors not by collaborating in a ship race however by flipping round in a circle to get factors. In one other simulation “the place survival required vitality however giving start had no vitality value, one species developed a sedentary life-style that consisted largely of mating as a way to produce new kids which may very well be eaten (or used as mates to supply extra edible kids).” This led to what Krakovna referred to as “indolent cannibals.”

It’s apparent that these machines aren’t “pondering” in any actual sense however when given parameters and a the power to evolve a solution, it’s additionally apparent that these robots will provide you with some enjoyable concepts. In different check, a robotic discovered to maneuver a block by smacking the desk with its arm and nonetheless one other “genetic algorithm [was] purported to configure a circuit into an oscillator, however as a substitute [made] a radio to choose up alerts from neighboring computer systems.” One other cancer-detecting system discovered that photos of malignant tumors often contained rulers and so gave loads of false positives.

Every of those examples reveals the unintended penalties of trusting machines to be taught. They are going to be taught however they may even confound us. Machine studying is simply that – studying that’s comprehensible solely by machines.

One ultimate instance: in a recreation of Tetris through which a robotic was required to “not lose” this system pauses “the sport indefinitely to keep away from shedding.” Now it simply must throw a tantrum and we’d have a intelligent three-year-old on our fingers.


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