Summarize
With the continuous progress and development of artificial intelligence technology, deep learning has become one of the core technologies for realizing artificial intelligence. Since the 1980s, neural networks and deep learning have experienced a long and tortuous development process, with many ups and downs, the proposal and application of classic models and algorithms, the solution of classic problems and the promotion of industry applications.
This article systematically reviews and summarizes lithuania mobile database the development of neural networks and deep learning, from the back-propagation algorithm to the release of GPT-4. This article introduces the origin and development of neural networks, and elaborates on the development trajectory of deep learning technology and their applications in computer vision, natural language processing, reinforcement learning and other fields. At the same time, this article also introduces the breakthrough progress of the latest technologies such as GPU and TPU, AlphaGo, and AlphaFold.
In this post, we will explore the origins and early research of artificial intelligence AI and machine learning. AI refers to enabling computers to perform tasks that usually require human intelligence, while machine learning is a subfield of AI that enables computers to learn from data. We will review the important events and research results from 1950 to 1980 and introduce some methods and theories that have had a lasting impact.