Artificial intelligence development

artificial intelligence (AI), also known as machine intelligence, refers to the intelligence shown by machines built by humans. Generally, artificial intelligence refers to the technology of rendering human intelligence through ordinary computer programs.

First Wave (non-intelligent conversation bots)

In the 1950s and 1960s

In October 1950, Turing introduced the concept of artificial intelligence (AI), along with the Turing Test to test AI.

Within a few years of the Turing Test being proposed, people saw the "dawn" of computers passing the Turing test.

The first wave did not use any new technology, but some tricks to make computers look like real people, and computers themselves were not intelligent.

The Second Wave (Speech Recognition)

In the 1980s and 1990s

In the second wave, speech recognition is one of the most representative breakthroughs. The core reason for the breakthrough is to give up the thinking of the symbolic school and change to the statistical thinking to solve practical problems.

The biggest breakthrough of the second wave was to change the way of thinking, to abandon the symbolic school of thought, and to use statistical ideas to solve problems.

The Third Wave (Deep Learning + Big Data)

Early 21st century

The year 2006 was a watershed in the history of deep learning. Jeffrey Hinton published "A Fast Learning Algorithm for Deep Confidence Networks" in the same year, and other important deep learning academic articles were published in the same year, making several major breakthroughs at the basic theoretical level.

There are two main reasons why the third wave is coming:

1) The rapid development of the Internet industry since 2000 has resulted in massive data. And the cost of data storage is falling fast. It makes it possible to store and analyze massive data.

2) The continuous maturity of GPU provides the necessary computing power support, improves the availability of algorithms, and reduces the cost of computing power.

The third wave comes mainly because big data and computing power conditions are in place, so that deep learning can play a huge power, and AI's performance has surpassed that of humans, and can reach the stage of "usable" rather than just scientific research.