Liangqu Long - Beginning Deep Learning with TensorFlow: Work with Keras, MNIST Data Sets, and Advanced Neural Networks

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What we want is a machine that can learn from experience.

Alan Turing

Information technology is the third industrial revolution in human history. The popularity of computers, the Internet, and smart home technology has greatly facilitated peoples daily lives. Through programming, humans can hand over the interaction logic designed in advance to the machine to execute repeatedly and quickly, thereby freeing humans from simple and tedious repetitive labor. However, for tasks that require a high level of intelligence, such as face recognition, chat robots, and autonomous driving, it is difficult to design clear logic rules. Therefore, traditional programming methods are powerless to those kinds of tasks, whereas artificial intelligence (AI), as the key technology to solve this kind of problem, is very promising.

With the rise of deep learning algorithms, AI has achieved or even surpassed humanlike intelligence on some tasks. For example, the AlphaGo program has defeated Ke Jie, one of the strongest human Go players, and OpenAI Five has beaten the champion team OG on the Dota 2 game. In the meantime, practical technologies such as face recognition, intelligent speech, and machine translation have entered peoples daily lives. Now our lives are actually surrounded by AI. Although the current level of intelligence that can be reached is still a long way from artificial general intelligence (AGI) , we still firmly believe that the era of AI has arrived.

Next, we will introduce the concepts of AI, machine learning, and deep learning, as well as the connections and differences between them.

AI is a technology that allows machines to acquire intelligent and inferential mechanisms like humans. This concept first appeared at the Dartmouth Conference in 1956. This is a very challenging task. At present, human beings cannot yet have a comprehensive and scientific understanding of the working mechanism of the human brain. It is undoubtedly more difficult to make intelligent machines that can reach the level of the human brain. With that being said, machines that archive similar to or even surpass human intelligence in some way have been proven to be feasible.

How to realize AI is a very broad question. The development of AI has mainly gone through three stages , and each stage represents the exploration footprint of the human trying to realize AI from different angles. In the early stage, people tried to develop intelligent systems by summarizing and generalizing some logical rules and implementing them in the form of computer programs. But such explicit rules are often too simple and are difficult to be used to express complex and abstract concepts and rules. This stage is called the inference period .