On June 7, 'New Stock Guru' Serenity published an article sharing his investment methodology, stating that his investment style essentially belongs to discretionary investing. The core focus is on discovering industry trends that the market has not yet reached a consensus on, combining real-world observations, industry research, and revenue forecasts for high-confidence projections. Serenity used Raspberry Pi (RPI) as an example, indicating that while most investors still view it as an educational and DIY hardware, he observed an increasing number of developers starting to use Raspberry Pi and Apple Mac Mini to deploy AI applications, validating this trend through online tutorials, and ultimately concluding that AI would become a new growth engine for companies. Subsequently, the company's financial report showed a 58% year-on-year revenue growth, significantly exceeding the market's previous growth expectation of 14%. Discussing the investment case of AXT (AXTI), Serenity stated that his judgment was based on research of the indium phosphide (InP) substrate supply chain and expectations of a photonics supercycle. At that time, the market generally believed that the related market size was limited, but he believed that AXT held about 40% of the InP supply chain share, possessing a critical bottleneck position, thus its long-term value was severely underestimated. Following this, Goldman Sachs and related industry chain companies successively released research and performance data that validated some of his views. Regarding X-FAB (XFAB), Serenity mentioned that it is currently still in the 'projection validation stage.' Although the market generally does not view it as a photonics company, he found in government documents, ASE data, and industry chain information that the company is becoming an important player, and Nvidia is evaluating its related capabilities. He will continue to observe in the coming months to see if more evidence validates this investment logic. Serenity stated that many current investment opportunities arise from a comprehensive inference of fragmented information, real trends, and industry changes, rather than just traditional valuation models. He believes that investing is essentially a process of combining long-accumulated industry knowledge, life experience, and market analysis. While high-confidence projections may sometimes be wrong, they are often a significant source of excess returns.