From the advanced development of computational intelligence, perceptual intelligence and cognitive intelligence, AIGC has opened the door to cognitive intelligence for human society. It refers to the technology of generating artificial intelligence based on countermeasure network and large-scale pre-training model, and generating relevant content with appropriate generalization ability through learning and identifying existing data. AIGC has been widely used in media, education, entertainment, marketing, scientific research and other fields to provide users with high-quality, efficient and highly personalized content services.
The significance of AIGC to human society and artificial intelligence is a milestone. In the short term, AIGC has changed the basic productivity tools, in the medium term, it will change the social production relations, and in the long term, it will promote the qualitative breakthrough of the whole social productivity. In such productivity tools, production relations and productivity changes, the data value of production factors is greatly enlarged.
Development and prospect of AIGC
AIGC is a cutting-edge innovative artificial intelligence technology, which is constantly developing and progressing. With the improvement and optimization of artificial intelligence model and the enrichment and perfection of data resources, AIGC will be able to produce higher quality, more diversified and more personalized content to meet the various needs and scenarios of users.
AIGC will also be combined with other artificial intelligence technologies to achieve more powerful and intelligent content services. For example, AIGC can be integrated with natural language processing (NLP), computer vision (CV), speech recognition (ASR), speech synthesis (TTS) and other technologies to realize the generation of cross-media content such as text to image, image to text, text to speech, and speech to text.
AIGC can also be combined with machine learning (ML), deep learning (DL), reinforcement learning (RL) and confrontation generation network (GAN) to realize more autonomous and flexible content generation.