Abstract: Artificial intelligence and chip technology are engaged in a deep, mutually reinforcing evolution, crystallized in two core directions: AI for Chip and Chip for AI. AI for Chip leverages AI to transform semiconductor design—enabling intelligent microarchitectural exploration, automated PPA-optimized physical implementation, and hardware-software co-design, significantly enhancing design efficiency and quality. Chip for AI focuses on architecting specialized hardware to accelerate AI workloads. While NVIDIA dominates through its GPU-CUDA ecosystem, extending open instruction sets like RISC-V with vector and tensor capabilities is emerging as a key path toward architectural innovation and ecosystem diversification. Looking ahead, a powerful virtuous cycle is taking shape: advanced AI tools enable more capable domain-specific chips, which in turn provide the essential computational foundation for next-generation AI advancements.