At Mind Matters News, we have criticized his approach on numerous grounds. One problem that keeps getting left out is, who assumes moral responsibility and legal liability for self-driving vehicles?
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Humans intrinsically understand causation and, therefore know which pieces of data likely have some correlation. Therefore, when we select data for computers to analyze, we are drastically reducing the size of the problem for computers.
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Many “how” explanations can seem pretty off-topic. Imagine a situation where a book club is discussing the works of Stephen King where one commenter keeps on bringing up the fact that all of King's writing was done on a Mac.
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In the model of generalization set out in the paper, imperfect models can get better scores but they are discounted according to the amount of error they have.
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Rakover presents an initial sketch of a methodology that allows a better conceptualization of the method by which mental states get moved in and out of consciousness. The edition also features a review of Scott D. G. Ventureyra’s On the Origin of Consciousness.
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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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Rather than lacking insight into AI issues, this band of theologians is especially sagacious in applying theology to them.
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Software engineers call imaginary products “vaporware.” And if the tag fits, it wouldn’t be the first time that Tesla has marketed an illusion.
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While the learning curve is not an exact science, the interesting part, in my view, is that such a non-physical mechanism can be measured at all.
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A virtual rail is essentially a road that is built expressly for driverless cars.
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My primary reason for doubting that AI can match human intelligence is that the difference between mind and machine is a difference of kind, not of quantity. Understanding the distinction will help us exploit the abilities of each to their maximum potential.
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Is this the future of currency? Seems like the Dark Ages to me. Bitcoin is a clever idea, but it is perhaps too clever for its own good.
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Google is one of the most widely misunderstood success stories of our time. Many of us equate Google with “Big Data,” that is, amassing huge quantities of data and then finding useful statistical patterns. But is that how it succeeded? In Life after Google: The Fall of Big Data and the Rise of the Blockchain Economy, George Gilder criticizes Google primarily on two fronts: First, it is a “walled garden,” a great platform, but inherently isolated and closed. That is a point worth exploring, but not the focus here. The second point, the one I want to touch on, is that Big Data’s day has come and gone. Because Google is a Big Data company, its brightest days are behind it. Read More ›
