The Decade of Artificial Intelligence, How Does Deep Learning Change the World?

5 min readJan 21, 2022

In 1942, Asimov, the American science fiction giant, proposed the “three laws of robotics”, which proposed the relationship between man and machine. Artificial intelligence was formally born at the Dartmouth Conference in 1956. In the early stage, due to the limitation of computer development, artificial intelligence was in a slow development stage, which experienced hot and cold winter.

In the last decade, the development of artificial intelligence has been constantly accelerated, and various deep learning networks have emerged in endlessly. Deep learning has begun to achieve success in the fields of speech and image.

Deep learning is one of the fastest developing branches in the field of artificial intelligence in the past 10 years. In 2012, in the famous ImageNet image recognition competition, the group led by Jeffrey Hinton adopted the deep learning model AlexNet to win the title, and deep learning has attracted the attention of everyone.

Over the past decade, along with advances in computing power and big data, deep learning has tackled many of the problems we used to struggle with, especially computer vision and natural language processing.

In addition, deep learning technologies are increasingly coming into our lives and becoming ubiquitous. In the field of image recognition, In 2014, Facebook’s DeepFace project, based on deep learning technology, was able to recognize faces with an accuracy rate of more than 97%, almost the same as that of humans.

In 2016, AlphaGo beat Go world champion Li Zaishi, and in September of the same year, the Institute of Computing Technology of the Chinese Academy of Sciences released the “Cambrian 1A” deep neural network processor. All of this highlights the fact that deep learning is well on its way and growing in influence. In 2020, OpenAI’s GPT-3 took social networks by storm.

With the development of deep learning, speech, image and natural language processing are the three main research fields in which deep learning algorithms are most widely applied.




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