Solving the problem of information classification, AI stride forward

Humans naturally have the ability to classify information. However, this skill proved hard to be achieved by computers. In the face of a lot of data, computers often do not know where to start, unless you give it a specified structure, hierarchy, or linear order.
But now, MIT's new research will bring an explosive breakthrough in the AI field. The model developed by MIT's PhD recipient Charles Kemp can help computers identify various types of data like humans. This model can automatically identify which structure is most suitable for organizing the large amount of data currently facing.

Unlike previous models, it does not specify a specific data structure for each operation. Instead, we use our own algorithms to analyze the data and then select the structure most suitable for this operation. This provides an excellent solution for large-scale operations.
However, the greater impact of this model is that artificial intelligence may no longer have to deal with yes or no problems. Artificial intelligence will be able to analyze a large amount of data in the environment and respond to it.
Of course, this model is not perfect yet, and it can only catch up with the analytical capabilities of children. However, we believe that with the increasing application and improvement of this model, AI will surely bring us more surprises in the future.