Today, Tencent Holdings Limited released its first-quarter financial report. The company reported revenue of RMB 196.46 billion for the quarter, representing a 9% year-over-year increase. Non-IFRS operating profit reached RMB 75.63 billion, also up 9% year-over-year. Excluding the impact of new AI products, Non-IFRS operating profit would have grown 17% year-over-year to RMB 84.4 billion. The period's free cash flow amounted to RMB 56.7 billion. Following the earnings release, company executives including Chairman and CEO Pony Ma, President Martin Lau, Chief Strategy Officer James Mitchell, and CFO John Lo held an earnings conference call to discuss the results and answer analyst questions. The following are key excerpts from the analyst Q&A session: Citi Analyst Alicia Yap: I have two questions. First, since the Hunyuan 3.0 model was introduced to users in the form of the Hy3 preview, and as management mentioned in the briefing, the Hunyuan large language model has been deeply integrated into many of Tencent's core internal products, including Yuanbao, ima, and WorkBuddy. Could management share what improvements in product performance or efficiency you have observed as the Hunyuan model is integrated into these workflows? Furthermore, looking ahead, as the Hunyuan 3.0 model is further integrated into the WeChat ecosystem, what are the planned product roadmaps from management? For example, will Mini Program enterprises also be able to leverage these AI agent workflows to enhance efficiency and drive future digital upgrades? My second question concerns advertising. As AI agents gradually replace traditional "click-based interaction tools" on web pages and within apps, how does management view potential changes in future advertising product pricing? What impact might this have on advertiser budget allocation? In management's view, which types of digital content and online activities will likely remain resilient and continue to attract significant user engagement in the future? Additionally, has management proactively considered and strategically positioned for new advertising formats to adapt to this potential shift in advertising expenditure trends? We would appreciate more insights and outlook from management on this front. Martin Lau: Regarding the Hunyuan 3.0 model, we provided a relatively comprehensive overview of its capabilities in the earlier briefing. As you can see, the Hunyuan 3.0 model demonstrates a higher level of intelligence. Although its parameter scale is relatively compact, its performance in reasoning capabilities is actually very strong. Simultaneously, compared to Hunyuan 2.0, the Hunyuan 3.0 model shows significant improvement in its capabilities as an AI agent. Based on these characteristics, as we integrate the Hunyuan 3.0 model into various products, we find the overall product performance quite encouraging. Product teams across the board have reported noticeable improvements in performance, which they can directly observe from the user side. Compared to Hunyuan 2.0, the total volume of token calls for the Hunyuan 3.0 model has increased by at least tenfold. This is a very clear signal that the design of the Hunyuan 3.0 model is highly successful. Furthermore, because the Hunyuan 3.0 model was co-developed with some of Tencent's core products, such as Yuanbao, CodeBuddy, and WorkBuddy, it is better aligned with the needs of these products, which has also garnered widespread recognition from the product teams. Regarding your question about how the Hunyuan 3.0 model will integrate into WeChat workflows, I believe this will be a gradual process. In fact, some WeChat features have already been integrated and iterated upon using the Hunyuan 3.0 model. In certain application scenarios, we also test different models concurrently to evaluate which one best suits current user needs. Therefore, as the Hunyuan 3.0 model continues to be optimized, we will naturally expand its integration with WeChat products. On the topic of Mini Programs. I believe the most direct advantage the Hunyuan 3.0 model offers to enterprises is this: if they are already using our products built on the capabilities of Hunyuan 3.0, such as AI programming tools, CodeBuddy, or WorkBuddy, they are already benefiting from the performance enhancements of the 3.0 model. In the future, as we begin large-scale integration of Mini Programs into the AI agent ecosystem, enabling agents to call upon Mini Programs as tools, this will also bring more traffic to Mini Program enterprises. Therefore, to summarize from two perspectives, I would say the first is the "internal aspect": enterprises can enhance their own production efficiency by using our AI agent products. The second is the "external aspect": in the future, their Mini Programs will be invoked and used by more users and more AI agents, thereby creating more growth opportunities. James Mitchell: Regarding your question about advertising, it's a very interesting one. I believe this potential shift might have a greater impact on e-commerce companies than on a company like ours. The reason I say this is that users actively choose to spend time watching short videos, listening to music, consuming content, or chatting with friends; however, generally, when users spend time on e-commerce platforms, it's often because they want to find the lowest price for a product, not necessarily because they truly enjoy the process itself. If AI agents play an increasingly significant role in price comparison in the future, users might indeed reduce their time spent on e-commerce websites and, correspondingly, be exposed to fewer ads—because AI agents can help users quickly browse through an unlimited list of products, and they are not influenced by advertisements in the way humans are, given that human attention is limited, and advertising precisely exploits this limited attention. Of course, having said that, historically, the industry has seen multiple iterations of "price comparison services," including search engines. Even with the existence of these services, large e-commerce companies have, on the whole, continued to succeed and grow. Therefore, I think it is still too early to draw a definitive conclusion on "how AI will affect e-commerce industry peers." At least for now, we do not consider this to be a core risk that Tencent will need to face in the future. (To be continued...)