In recent years, large language model (LLM) technology has developed rapidly, and visual language model, as an important branch, has received widespread attention. Especially in China, universities such as Tsinghua University and Zhejiang University actively promote the research and development of open source visual models, injecting new vitality into the development of the domestic artificial intelligence field. This article will focus on several high-profile open source vision models and analyze their potential in the field of vision processing.
Universities such as Tsinghua University and Zhejiang University have promoted open source alternatives to GPT-4V, and a series of open source visual models with excellent performance have emerged in China. Among them, LLaVA, CogAgent and BakLLaVA have attracted much attention. LLaVA has demonstrated capabilities close to GPT-4 levels in visual chatting and reasoning question answering, while CogAgent is an open source visual language model improved on CogVLM. In addition, BakLLaVA is a Mistral7B basic model enhanced using the LLaVA1.5 architecture, which has better performance and commercial capabilities. These open source vision models have great potential in the field of vision processing.
The emergence of open source visual models such as LLaVA, CogAgent and BakLLaVA marks China's significant progress in the field of artificial intelligence, providing powerful tools and resources for academia and industry, and also indicates that visual language models will have a broader future application prospects, promote the sustainable development of artificial intelligence technology, and bring changes to all walks of life. The open source of these models also lowers the technical threshold and promotes broader innovation and cooperation.