1. Technical difference: Deep learning technology is usually used for large-scale models, and deep neural networks are trained through large-scale data sets, thus achieving efficient solutions to complex problems. The large model has good generalization ability and can obtain good performance on a large number of data sets. In addition, the large model has good scalability and can improve the performance by increasing the depth and width of the network. Traditional AI technology is mainly based on rules and knowledge base to solve problems. Traditional AI technology usually uses a simple neural network structure and uses a large amount of data for training, so as to obtain better performance. Traditional AI technology is real-time and can quickly deal with problems in specific scenarios.
2. Differences in application scenarios: The big model has made remarkable achievements in natural language processing, computer vision, speech recognition and other fields. For example, in the field of natural language processing, the large model can realize the deep understanding and generation of natural language, thus realizing tasks such as text classification and machine translation. In the field of computer vision, large model can realize the deep understanding and generation of images, so as to realize the tasks of target detection and image generation. In the field of speech recognition, the large model can realize the deep understanding and generation of speech signals, thus realizing the tasks of speech recognition and speech synthesis. Traditional AI technology has achieved good application results in search engines, recommendation systems, intelligent customer service and other fields. For example, in the field of search engines, traditional AI technology can realize the deep understanding and generation of keywords, thus improving the search effect. In the field of recommendation system, traditional AI technology can deeply analyze and predict user behavior, thus improving the recommendation effect. In the field of intelligent customer service, traditional AI technology can deeply understand and generate user needs, thus improving customer service effect.
3. Differences in industrial impact: The big model has brought unprecedented opportunities for the development of science and technology industry. For example, in the field of natural language processing, the development of large-scale models has made an important breakthrough in the field of artificial intelligence in China and brought new development opportunities to China's science and technology industry. In addition, the large-scale model has achieved good application results in the fields of finance, medical care, education and so on, providing a new impetus for the industrial upgrading of China. Traditional AI technology has also achieved good application results in industrial control, smart home, driverless and other fields. For example, in the field of industrial control, traditional AI technology can achieve deep control of equipment and improve production efficiency. In the field of smart home, traditional AI technology can realize intelligent control of home equipment and improve living comfort. In the field of unmanned driving, traditional AI technology can achieve deep control of vehicles and improve driving safety.