[Dry goods] How to understand artificial intelligence

Initially, when people predicted that Alpha Go and Li Shishi would win, I would say that Alpha Go would win. Because Li Shishi is faced with more than just an algorithmic program, in addition to the complex algorithms consisting of a chess network, a valuation network, a fast-moving subroutine, and a Monte Carlo search, the battlefield of man-machine warfare is equipped with 40 Online network platform, more than 1200 CPUs, more than 170 GPUs, big data, cloud computing, instant processing of the current game and 30 million games accumulated in history, and even a dedicated cable for the event, all of which are A group of world-class deep learning experts. In this sense, Alpha Go is a giant coupling of human-computer interaction. It is an extended cognitive system that handles special tasks in real time. The core of this system is people. The front desk performs only the program running terminal of this system, and the talent is the intellectual resource behind it.

Unintentional machines are the limitations of current artificial intelligence

One direct effect of Alpha Go's victory over Li Shishi is that many people believe that the victory of Alpha Go means that artificial intelligence has broken through certain limits and reached a high level of intelligence. As a result, all the wisdom that humans cherish will eventually be replaced by machines. The future of humanity is really worrying.

But in fact, despite the baptism of a child, the artificial intelligence has not yet got rid of the fate of the "unintentional machine". Today's artificial intelligence can be said to have neither intelligence nor mind. This is because the current computer uses a binary coded Turing machine calculation, which is a recursive algorithm. Eighty years ago, the great logician Gödel had pointed out that the Turing machine's computing power is inherently limited compared with humans. However, people are more keen on quoting Turing's words in "Machine and Intelligence" in 1950. "We can't blame a machine for not being able to participate in a beauty contest, just as we can't just blame him for not flying alone." The machine can also think"; it ignores the basic points of the 1936 Turing classic "On Computable Numbers", which clearly distinguishes what is computable, what is uncalculated, and where the boundaries of the calculation are. As long as it is an uncalculated problem, people can't find the algorithm anyway. And the uncalculated world is much more numerous than the world that can be counted.

International computational theory and visual theorist Marr has attributed the computability to three major steps. First, abstract the specific real problem into a problem that can be clearly defined. Second, it depends on whether it is a problem of computable classes. Third, find the algorithm in a computable range. For artificial intelligence, there is naturally another important step, to perform an algorithm on the machine to complete the calculation. At present, artificial intelligence can exceed human computing power in many local areas that need to do a lot of calculations, but its limitations are most acutely reflected in the inability to deal with the following three types of problems: meaning understanding; consciousness and consciousness experience; autonomy and awareness.

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