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"Relationship between AI, machine learning, and deep learning-how to reproduce human "intelligence""


The differences and relationships between "artificial intelligence (AI)," "machine learning," and "deep learning" can be understood smoothly by examining the history of AI.

"Human "intelligence" can be artificially reproduced by machines." --In 1956, the term "artificial intelligence (AI)" was born from the ideal of such researchers.

Since then, research has continued for more than half a century.

　During this period, it starts from solving mazes, puzzles, games such as chess and shogi (searching and reasoning), registers human knowledge as a dictionary or rules in a computer, and

tries to derive answers like experts ( Rule base and expert system) have been carried out.

　However, since humans make dictionaries and rules, it is not possible to register all the phenomena in the world.

In addition, there was a problem that it would not be possible to process it given the contradictory rules that are common in the world.

As a result, we were able to achieve results in a narrow and limited field, but it was far from "human "intelligence"" that could be widely applied in various

fields, and we did not achieve great results.

　After that, "machine learning", a method of analyzing the data in a specific field to find out the regularity and rules for classification, distinction, judgment and prediction, will appear.

　Although the concept of machine learning has been around for a long time, the performance of computers is insufficient, and it has not reached its full potential, and it has

improved its capabilities as computer performance has improved and methods have evolved.

Also, the spread of the Internet has made it possible to collect a large amount of learning data at low cost, which has also accelerated this research.

Humans have to specify what kind of characteristics AI should be able to focus on when performing classification, distinction, and judgment, that is, "selection and combination of characteristics (feature amount)"

Machine learning is a method that finds out the distribution, pattern, and regularity of this feature quantity by analyzing a large amount of learning data, and uses the result

　However, the feature amount had to be designed and registered by humans, and its skill greatly affected the result.

　After that, research on the function of the brain when humans recognize images proceeded, and "deep learning", a method of machine learning that applies the results, will appear.

　This technology can be created by analyzing the data for selecting and combining feature quantities.

Therefore, the performance can be improved as the amount of data increases, without depending on human ability.

　It can be said that this has given rise to the possibility of arbitrarily classifying the world's forests.

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