This introductory educational module explores how neuroscience serves as a vital blueprint for advancing artificial intelligence beyond its current limitations. While modern systems excel at specific tasks through dense computation and massive energy consumption, the human brain demonstrates a superior model of energy-efficient, sparse processing and continuous, lifelong learning. The text identifies critical hidden assumptions in AI development, such as the rigid separation between training and deployment, which differ fundamentally from biological intelligence. It further argues that recent innovations like RAG and agentic AI are merely external scaffolding rather than the deep architectural integration seen in nature. Ultimately, the source encourages students to look toward biological principles to design robust, adaptive systems that can function effectively in the real world.