ENGAGE ON HIVE: AI WINTER

First AI Winter (1974 – 1980)

Following the research and advancement during the birth of AI, one would have expected the discovery to continually grow. However, the researcher had to deal with some limitations, which were limited memory space, and slow processor speed. These limitations led to the drop in funds from the government and sponsors. However, when the Japanese completed the "fifth generation" computer project, the US and Britain commenced funding of the research in a bid to gain world leadership of computer technology. Additionally, this phase of the first winter ended with the development of the "Expert Systems", which focused on gaining information from so many experts.

Expert Systems (1980 – 1990) became popular after the microprocessors of the 1970s. It was a method of Artificial Intelligence that uses the combined knowledge of experts to develop a program. This system could solve problems within a specified field of knowledge, making use of the "rules" of logic, and using this system, programs were easily built and adjusted. Also, this system became useful in various fields, such as sales, marketing, and medicine. As of the year 1985, several companies around the globe integrated Expert Systems, and this opened up a new field.

Second AI Winter (1987 – 1993)

It was another slowdown in the research of AI, and the Expert Systems were seen as slow and clumsy. Furthermore, with the evolution of desktop computers, Experts Systems were becoming too difficult to maintain in comparison with desktop computers. The former was difficult to update and learn, these difficulties were not encountered in the desktop computers. Additionally, DAPRA (Defense Advanced Research Projects Agency) redirected the funds, concluding that AI had no future.

New Boom (2010)

There was a movement away from the expert systems that involved coding rules for expert systems but allowing machines to discover them independently by correlation and classification, due to the big data available.

2 things have massively contributed to the boom:

The huge data volumes are available

The invention of the high efficiency of card processors and computer graphics to speed up the calculation of learning algorithms.

This is the age of the "big data", where we can store huge data that human brains cannot process. The application of AI has begun to bloom in several industries such as marketing, banking, education, and entertainment. Big data has improved much above algorithms, and computing systems can now learn through brute force.