Author: Zen and the Art of Computer Programming
With the development of technologies such as the mobile Internet and the Internet of Things, various industries are chasing high-efficiency, high-quality products and services. Visual products and services have become the core competitiveness of major companies. Due to the limitation of equipment performance and cost, traditional artificial intelligence (AI) technology cannot meet the demand. Therefore, more and more companies choose to integrate the ability of visual computing into their products, which is called "model generation" technology. Compared with artificially generated pictures, model generation technology can produce more realistic, natural and artistic visual effects. For example, photos generated using self-driving cars have a sense of immersion, realistic scenes, rhythm and movement; operating room perspective movies rendered using virtual reality technology are very good.
However, many companies have difficulty in bringing model generation technology to the market because they do not have the ability, resources or experience, resulting in insufficient market share. In addition, due to the lack of a reliable and trusted model training and publishing mechanism, model generation technology is also facing huge cost pressure. This requires enterprises to have a wealth of professional skills when building, optimizing, and deploying models, including machine learning engineers, software development engineers, algorithm researchers, and data analysts. Although the development of model generation technology has made great progress, there are still some technical bottlenecks and shortcomings. The purpose of this article is to explain the application and development direction of model generation technology in intelligent image generation, and what knowledge, skills, and accomplishments relevant personnel in the AI field should possess, hoping to provide reference for enterprises.
2. Explanation of basic concepts and terms
2.1 Overview of Model Generation
Model generation techniques can be divided into two categories: static model generation and dynamic model generation.
static model generation
Static Model Generation refers to images rendered from geometric shapes and materials manually made by computer programmers. These images are judged and created by human engineers and are often highly polished but lacking in innovation. Generally speaking, static model generation is mainly used in art projects such as architecture, video games, advertising design, photography, and advertising.