AI is not a brand new thing, he has been developing for decades! Below we introduce the most representative 3 development stages.
First wave (non-intelligent dialogue robot)
20 century 50 era to 60 era
1950 10 month, Turing proposed the concept of artificial intelligence (AI), and proposed the Turing test to test AI.
The Turing test suggested that in a few years, people saw the "twilight" of the computer through the Turing test.
1966 year, the psychotherapy robot ELIZA was born
People of that era rated him very high, and some patients even liked to chat with robots. But his implementation logic is very simple, is a limited dialogue library, when the patient speaks a certain keyword, the robot responds to a specific word.
The first wave did not use any new technology, but used some techniques to make the computer look like a real person. The computer itself is not smart.
Extended reading:
Second wave (speech recognition)
20 century 80 era to 90 era
In the second wave, speech recognition is one of the most representative breakthroughs. The core breakthrough was to abandon the idea of the symbol school and changed it to a statistical idea to solve practical problems.
in"人工智能In the book, Kai-Fu Lee introduced the process in detail, and he is also one of the important people involved.
The biggest breakthrough of the second wave was to change the way of thinking, to abandon the idea of the symbol school, and to use statistical ideas to solve the problem.
Extended reading:
History of Speech & Voice Recognition and Transcription Software
The third wave (deep learning + big data)
21 century
The 2006 year is a watershed in the history of deep learning. In this year, Jeffrey Sinton published "A Fast Learning Algorithm for Deep Belief Networks". Other important deep learning academic articles were also released this year, and several major breakthroughs were made at the basic theoretical level.
The reason why the third wave will come is that the 2 conditions are mature:
After the years of 2000, the rapid development of the Internet industry has produced massive data. At the same time, the cost of data storage has also dropped rapidly. It makes the storage and analysis of massive data possible.
GPU The continuous maturity provides the necessary computing power to improve the usability of the algorithm and reduce the cost of computing power.
Deep learning has developed a powerful ability after various conditions have matured. In speech recognition, image recognition,NLPThe field continues to set records. Make AI products truly available (for example, the error rate of speech recognition is only 6%, and the accuracy of face recognition is higher than that of humans.BERT The stage of exceeding the human...) in the performance of the 11 item.
The third wave struck, mainly because of the big data and computing power conditions, so that deep learning can exert great power, and the performance of AI has surpassed human beings and can reach the stage of “availability”, not just scientific research.
Extended reading:
What is deep learning?
Recommended books - "The Age of Big Data"
Why is GPU and deep learning more suitable?
Interpretation of Google's strongest NLP model BERT
The difference between the three waves
This content is taken from Li Kaifu’s人工智能In the book, all views are Li Kaifu's own, and this is just a retelling.
- The first two craze was dominated by academic research, and the third craze was dominated by real business needs.
- The first two craze is mostly at the market level, while the third craze is at the business model level.
- The first two crazes were mostly in the academic world to persuade the government and investors to invest money. The third wave of enthusiasm was that investors actively invested in academic projects and entrepreneurial projects in hotspots.
- The first two booms raised questions more, and the third boom solved problems more.
