The domestic discussion of artificial intelligence is mostly fragmented and fragmented. It is difficult to understand the development of artificial intelligence and technical system from it, and it is difficult to have practical reference. In a report released by Deloitte DUP, the history, core technology and application of artificial intelligence are described in detail, especially the important cognitive technologies. This report will help us to understand the artificial intelligence and cognitive technology, and also help companies in various industries to consider the practical value of artificial intelligence applications.
I. Overview
In recent years, interest in artificial intelligence has surged. Since 2011, companies that have developed and commercialized products and technologies related to artificial intelligence have acquired more than $2 billion in venture capital, while technology giants are investing more. One billion dollars to acquire artificial intelligence startups. Related reports have been overwhelming, and huge investments, computer-induced unemployment, and other issues have begun to emerge. Computers are smarter than humans and may threaten human survival. Such assertions are cited by the media and cause widespread concern.
IBM is committed to spending $1 billion to commercialize their cognitive computing platform Watson.
Google’s investments in recent years have focused on artificial intelligence, such as the acquisition of eight robotics companies and a machine learning company.
Facebook hired Yann LeCun, the AI ​​academic leader, to create its own artificial intelligence lab, hoping to make a major breakthrough in the field.
Researchers at the University of Oxford have published a report that shows that about 47% of jobs in the United States are at risk due to the automation of machine-aware technology.
The New York Times' best-selling book, The Second Machine Age, argues that the era of dramatic changes in digital technology and artificial intelligence has arrived, but the consequent negative effects of unemployment.
Silicon Valley entrepreneur Elon Musk keeps an eye on artificial intelligence by investing constantly. He even believes that artificial intelligence is more dangerous than nuclear weapons.
Famous theoretical physicist Stephen Hawking believes that the successful creation of artificial intelligence means the end of human history, "unless we know how to avoid risks."
Even with so many hype, there is no lack of significant business practices in the field of artificial intelligence, which have or will have an impact on various industries and organizations. Business leaders need a thorough understanding of the meaning and trends of artificial intelligence.
Second, artificial intelligence and cognitive technology
The first step in uncovering artificial intelligence is to define terminology, outline history, and describe the underlying core technologies.
1. Definition of artificial intelligence
There are many concepts and definitions in the field of artificial intelligence, and some are not enough. As one of the founders of the field, Mr. Nils Nilsson wrote: "Artificial intelligence lacks a common definition." An authoritative artificial intelligence textbook that has been revised three times now gives eight definitions, but the book does not disclose it. Which definition does the author prefer? For us, a practical definition is that artificial intelligence is a theoretical study of how computer systems can perform tasks that only rely on human intelligence to accomplish. For example, visual perception, speech recognition, making decisions under uncertain conditions, learning, and language translation. Compared with how humans conduct thinking activities, they define artificial intelligence from the perspective of tasks that humans can accomplish. Rather than how humans think, in today's era, we can circumvent the neural mechanism to face the definition of wisdom and directly explore its actual situation. application. It is worth mentioning that as computers are upgraded and expanded to solve new mission challenges, the threshold for the definition of tasks that need to rely on human intelligence to solve them is getting higher and higher. Therefore, the definition of artificial intelligence evolves over time. This phenomenon is called “artificial intelligence effectâ€. In summary, “artificial intelligence is to achieve a collection of tasks that cannot be achieved without human intelligence.â€
2. History of artificial intelligence
Artificial intelligence is not a new term. In fact, this field began to be launched in the 1950s. The history of this exploration is called the “era of embarrassment and eagerness, frustration and disappointment†– a more appropriate evaluation recently.
In the 1950s, the bold goal of artificial intelligence to simulate human intelligence was clarified. From then on, the researchers carried out a series of research projects that continued through the 1960s and continued into the 1970s. These projects show that computers can complete a series of books. Tasks within the scope of human capabilities, such as proving theorem, solving calculus, responding to commands through planning, performing physical actions, and even simulating activities such as psychologists and composers.
However, overly simple algorithms, the lack of theory that is difficult to cope with uncertain environments (which is ubiquitous in life), and the limitations of computing power have seriously hampered the use of artificial intelligence to solve more difficult and diverse problems. With the disappointment of the lack of continued efforts, artificial intelligence gradually faded out of public view in the mid-1970s.
In the early 1980s, Japan launched a project to develop a computer structure that is leading the field in artificial intelligence. The West began to worry about losing to Japan in this area, and this anxiety prompted them to decide to start investing in artificial intelligence again. Commercial suppliers of artificial intelligence technology products have emerged in the 1980s, some of which are already on the market, such as Intellicorp, Symbolics, and Teknowledge.
In the late 1980s, almost half of the “Fortune 500†were developing or using the “Expert Systemâ€, a man-made model that simulates the problem solving ability of human experts to simulate human experts solving problems in the field. Intelligent Technology.
The over-expectation of the potential of the expert system completely obscures its limitations, including the apparent lack of common sense, the difficulty of capturing the tacit knowledge of experts, the complexity and cost of building and maintaining large systems, when this is the case As more people realize, artificial intelligence research is once again out of orbit.
In the 1990s, the technological achievements in the field of artificial intelligence were always at a low tide, and the results were slim. Rather, technologies such as neural networks and genetic algorithms have gained new attention because they avoid some of the limitations of expert systems and because new algorithms make them more efficient.
The design of neural networks is inspired by the structure of the brain. The mechanism of the genetic algorithm is to first iteratively generate an alternative solution, then eliminate the worst solution, and finally introduce a random variable to generate a new solution, thus "evolving" the best solution to the problem.
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