Mar 5 2021
Human beings are living inside an ocean of signals. These signals enable human beings to demonstrate intelligence. Similarly, machines are also surrounded by signals. Artificial intelligence (AI) or machine intelligence has become a hot topic for many decades due to the high expectation of the public on the emergence of smart machines and smart products.
However, the AI research community is still struggling to determine the foci of machine intelligence. For instance, the low-level focus of AI is to advocate computer-aided human intelligence. We believe that the more challenging focus should aim at creating machines that can achieve human-like self-intelligence by themselves.
The development of machine's self-intelligence faces two fundamental issues. The first one is to discover, or formulate, the physical principles behind the transformation of visual signals to cognitive states of knowing the meanings of these visual signals.
The second one is to discover, or formulate, the physical principles behind the transformation of audio signals to cognitive states of knowing the meanings of these audio signals.
New Foundation of Artificial Intelligence lays out the new foundation of AI with two objectives in mind. The first objective is to shed light on this new direction which is founded on the use of human languages together with an extension into a technical language (i.e. mathematics) and programming languages.
In this way, the answer to the question of knowledge representation becomes obvious to all researchers in the AI community.
The second objective is to provide the teaching materials which will guide students in AI to master the fundamentals of achieving computer-aided human intelligence, as well as to prepare students to venture into the achievements of machine's self-intelligence.
New Foundation of Artificial Intelligence retails for US$88 / £73 (hardcover) and is also available in electronic formats. To order or know more about the book, visit http://www.worldscientific.com/worldscibooks/10.1142/7264.
Source: https://www.worldscientific.com/