This paper proposes a solution to the problem of physics and optics education in underdeveloped areas by utilizing small language models (SLMs). It points out the problem of deepening inequality in STEM education in underdeveloped areas due to poor infrastructure, insufficient educational resources, and unstable internet access, and argues that SLMs, which can operate offline, can be a scalable solution to solve these problems by acting as virtual teachers and supporting native language education and interactive learning. It emphasizes that intensive investment in AI technology can bridge the digital divide and promote the development of STEM education and scientific capacity in underprivileged communities.
