An article explains the principles of artificial intelligence and industrial upgrading opportunities

Artificial intelligence seems to be superior. Actually, cutting-edge technology companies are hoping that this long-term research will bring new opportunities for their current business. Neural networks, machine learning, and deep learning will build the basis of artificial intelligence. This paper describes three major issues. The basics are how to operate and implement artificial intelligence.

Artificial intelligence has now become a common topic discussed by the tech industry. This technology has been applied to Gmail, self-driving cars and photo finishing. Mark Zuckerberg even plans to develop an artificial intelligence butler. But the problem is that the concept of artificial intelligence is a bit too sci-fi, and it is always reminiscent of supercomputers that manipulate spacecraft, not clever spam filters. As a result, people have begun to worry about when artificial intelligence will rebel and rule humanity.

Technology companies also encourage people to ignore the gap between artificial intelligence and sci-fi artificial intelligence to some extent, but when you try to understand what computers do, it's easy to understand the difference. This article is about the most common direction of application of artificial intelligence in consumer applications, the limitations of current technology, and why we do not need to worry about the rise of robots.

What exactly is neural network, machine learning and deep learning?

These three terms now have a fairly high frequency of occurrence. They can be viewed as three different levels: the neural network is at the bottom level, it is the computer structure that builds the artificial intelligence; the machine learning is the next level, it is a program that can run on the neural network and can train the computer in the data Finding specific answers; deep learning at the top level, which is a feature type of machine learning that has only become popular in the last 10 years, and its popularity is mainly due to cheap processing performance and Internet data.

The concept of neural networks dates back to the beginning of artificial intelligence in the 50s. In simple terms, it is a way to build a computer, making it look like a cartoon brain, which is networked by neural nodes. These nodes themselves are stupid and can only answer the most basic questions. Once combined, they can solve complex problems. What's more important is that with the right algorithms, they also have the ability to learn.