Following a tenfold surge in optical module stocks, the AI supply chain is poised for new opportunities. Companies like Yuanjie Technology have seen significant market attention, with its stock price briefly surpassing Kweichow Moutai. This highlights the shift of AI computing hardware from a technological theme to a market valuation driver. The next phase of AI development is expected to focus on overcoming bottlenecks in power and cooling infrastructure. AI data centers are evolving into energy businesses, with power access and liquid cooling becoming critical. The International Energy Agency projects global data center electricity consumption to nearly double by 2030, driven by AI demands. Additionally, the financialization of computing power assets, such as GPU-backed financing, is emerging as a significant trend, with companies like CoreWeave leading the way. As AI transitions from training to inference, cost optimization will become crucial. The market will shift focus from GPUs to specialized chips and infrastructure that enhance efficiency and reduce costs. This evolution will redefine the AI supply chain, emphasizing the importance of integrating AI into enterprise workflows and the potential for AI-native companies to transform organizational structures.