Artificial Intelligence is regaining its wide popularity in recent years. On one hand, the success of Artificial Intelligence is guaranteed by the availability of big data which is the result of the formation of large systems that are interconnected by various networks. On the other hand, the importance of Artificial Intelligence is due to the urgent demand for autonomy (on top of automation) by robots and machines of tomorrow, which will be able to efficiently perform difficult tasks, and even to free human beings from doing dangerous jobs. With the rise of Artificial Intelligence inside the public minds, people are putting a very high level of interests on knowing the scientific principles behind the mental capabilities of machine’s self-skills as well as machine’s self-intelligence. In this long seminar, I will first go through the history of Artificial Intelligence, in which AI 1.0 was primarily focused on machine thinking while AI 2.0 was intensively focused on machine learning. Then, I will share with the audience some extremely important findings about: 1) why AI 1.0 and AI 2.0 are not the foundation of AI, and 2) why AI 3.0, which is a framework toward achieving machine’s self-intelligence, should be the authentic foundation of AI. Finally, the details of AI 3.0 will be presented to the audience.
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Xie M., 2024, Top-down Design of Human-like Teachable Mind, Special Issue in Celebrating IJHR’s 20th-Year Anniversary, International Journal of Humanoid Robotics.
