This human-plus-machine combination is proving more potent than the machine-only hype/promise.
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Because computers lack common sense, they cannot interpret statements that assume a background of general knowledge, as the Winograd Schema challenges show.
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Some of the stuff that made a difference, they couldn’t put in a computer. Some people say, if you can’t measure it, it doesn’t count but sometimes the things that count can’t be measured.
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If you ask about anything that’s a puzzle, joke, riddle, or sarcasm that you can’t look up in Wikipedia, computers are helpless.
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If Shakespeare is right about imagination, Sophia will certainly break some hearts.
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Kurt Gödel (1906–1978) proved that there are truths in mathematical logic that lie outside mathematical logic, which means that the mind cannot be understood simply as a computer.
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Popular culture is looking for high-tech ETs to be its saviors and Silicon Valley aspires to become those ETs. What could possibly go wrong?
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Machine learning is not a new technique, but is simply a modern extension of a tool that we have had in our toolbox since the days of the Babylonians. It continues to serve us well to help us extrapolate our data to estimate the value of unknown results and to help find the signal in noisy data.
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The idea that machines are capable of replacing us is the topic of many books he has read but, he argues, the thing that really distinguishes us is the capacity for developing creative freedom.
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