According to reports from Intelligent Emergence, YunJinWei, a developer of embodied intelligent agent operating systems, recently announced the completion of several million yuan in angel round financing, led by iFLYTEK. This round of financing will be used for the research and development of core technology products and the construction of a market ecosystem.
Founded in June 2021, YunJinWei focuses on the research and development of embodied intelligent agent operating systems. The company was established by Dr. Wang Wenyiyi, former general manager of the hardware division at Yitu Technology, and co-founder Dr. Zhou Chang, who previously led the development of large visual models at Alibaba's Damo Academy for the City Brain project. The team has received support from the Ningbo Yaojiang Talent Program and the Yongjiang Talent Project, along with government funding grants amounting to tens of millions.
Image Source Note: Image generated by AI, image authorized by service provider Midjourney
The company's self-developed YunJin OS and supporting products keep the cost of edge computing devices under 10,000 yuan, providing enterprises with low-threshold AI solutions. They have already achieved commercialization in sectors such as energy, water management, and transportation, serving nearly 100 enterprise clients with total sales reaching tens of millions of yuan, including large companies like China Electronics, Guiyang Rail Transit, and SAIC Group.
YunJinWei's core advantage lies in its self-developed VT-Transformer distributed collaborative computing framework, which has an open-source pure C language version that can replace NVIDIA's CUDA architecture and supports domestic AI chips. Through technological innovation, YunJinWei has reduced the deployment cost of million-level large models to the hundred-thousand level, and the hundred-thousand-level visual computing solutions to the thousand-yuan level.
"Our goal is to make AI affordable for every enterprise," said Wang Wenyiyi. He stated that the future of AI large model training will shift from the digital world of the internet to the physical world, transitioning from centralized network computing to distributed edge computing and cloud-edge collaboration. YunJinWei will continue to focus on lowering the barriers to AI applications and promoting the inclusive development of technology.
