Hello and thank you for standing by for Baidu's second quarter 2026 earnings conference call. At this time, all participants are in a listen-only mode. After management's prepared remarks, there will be a question and answer session. Today's conference is being recorded. If you have any objections, you may disconnect at this time. If you wish to ask a question, You will need to press the star key followed by the number 1 on your telephone keypad. I would now like to turn the meeting over to your host for today's conference, Juan Lin, Baidu's Director of Investor Relations.

Hello, everyone, and welcome to Baidu's second quarter 2026 earnings conference call. Baidu's earnings duties were distributed earlier today, and you can find a copy on our website as well as on newswire services. On the call today, we have Robin Li, our co-founder and CEO, Julius Rong Luo, our EVP in charge of Baidu Mobile Ecosystem Group, MEG, Dou Shen, our EVP in charge of Baidu AI Cloud Group, ACG, and Henry Haijian He, our CFO. After our prepared remarks, we will hold a Q&A session. Please note that the discussion today will contain forward-looking statements made under the safe harbor provisions of the U.S. Credit Security Litigation Reform Act of 1995. Forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from our current expectations. For detailed discussions of these risks and uncertainties, please refer to our latest annual report and other findings with S&C and the Hong Kong Stock Exchange. Baidu does not undertake any obligation to update any forward-looking statements except as required under applicable law. Our earnings press release and this call include discussions of certain annotated non-GAAP financial measures. Our press release contains a reconciliation of the annotated non-GAAP measures to the annotated most directly comparable GAAP measures and is available on our IR website at ir.baidu.com. As a reminder, this conference is being recorded. A webcast of this conference call will be available on Baidu's IR website. I will now turn the call over to our CEO, Robin.

Hello, everyone. In Q2, Baidu General Business generated total revenue of RMB 25.2 billion, with Baidu Core AI-powered business continuing to represent half of the total, reinforcing AI's position at the core of our business. AI Cloud Infra delivered another quarter of strong growth with overall revenue increasing 50% year-over-year, once again outpacing the broader market. Within AI Cloud Infra, GPU cloud revenue nearly quadrupled year-over-year, growing 283% and accelerating significantly from an already strong 184% growth rate last quarter. With AI powered business now at the core of our revenue mix, we are focused on building a stronger foundation for its next phase of growth. Across our full AI stack, from chips and cloud infrastructure to models and applications, we are continuing to strengthen the capabilities that will support sustained innovation, power our future growth, and reinforce our long-term competitiveness. Let me now turn to the key business highlights of this quarter, starting with our proprietary AI chips, Kunlunxin. In Q2, Kunlunxin continued to demonstrate strong business momentum, with demand remaining robust and broadening across industries. A growing number of customers are adopting its chips for an expanding range of AI workloads, reflecting increasing market recognition of Kunlunxin's stability, efficiency, and versatility at scale. Kunlunxin continues to strengthen its software ecosystem, broadening compatibility with leading models and frameworks, and improving ease of deployment across enterprise environments. Building on its support for Ernie, and other leading foundation models in China. Kun Lunxin further extended its coverage in Q2 to include newer versions of major Chinese foundation models, such as Kimi EK3, GLM 5.2, Minimax M3 and Huiyuan 3. It also improved inference throughput and overall compute efficiency, strengthening its ability to support diverse and demanding AI workloads at scale. Over more than a decade, Kunlunxin has successfully developed and commercialized three generations of AI chips. Building on this track record, it continues to advance a clearly defined product roadmap, including the latest M100, optimized for large-scale inference, and the upcoming M300. This roadmap reflects Kunlunxin's deep understanding of evolving AI technology, workflows, and their compute requirements. positioning it to support the next wave of AI innovation. As we continue to advance our AI infrastructure capabilities, we believe sequencing will play an increasingly important role within our full-stack AI architecture and enhance our ability to deliver high-performance, reliable, and cost-efficient AI computing at scale. As demand for AI computing in China continues to grow, we believe our proprietary AI chips and full-stack capabilities will become increasingly valuable, supporting the future growth of our AI businesses and reinforcing our long-term competitiveness in AI. Building on our strengths at the infrastructure layer, AI Cloud Infra delivered another quarter of strong growth In Q2, AI Cloud Infra revenue increased by 50% year-over-year, continuing to outpace the broader industry. Several factors combined to drive this sustained growth momentum. First, AI Cloud Infra continued to benefit from strong demand for AI computing. Demand remained robust across both training and inference workloads, while computing supply remains constrained across the market. Second, our existing key clients, including leading companies in online gaming, e-commerce, and lifestyle content, continue to increase both their usage and spending with us. Meanwhile, our overall customer count grew rapidly, with new clients spanning companies of varying sizes. Third, demand remained broad-based across industry verticals, including internet, embodied AI, autonomous driving, smartphones, financial services, and more. Within this mix, internet and autonomous driving sustained strong growth while embodied AI revenue grew approximately six-fold year-over-year in Q2. Based on these trends, we believe AI cloud infra-revenue growth will remain strong in the second half, with the potential for further acceleration. Importantly, the growth in AI Cloud Infra was accompanied by rapid profit growth and expanding margins on a year-over-year basis, reflecting continued improvement in the overall health and quality of the business. Within AI Cloud Infra, GPU cloud revenue growth accelerated sharply to 283% year-over-year. Building on an already high base of 184% growth last quarter, this momentum reflects strong underlying demand for scalable AI compute in the public cloud. The mix of our business continues to shift toward higher quality revenue streams, with GPU Cloud accounting for a growing share of AI Cloud infra revenue. Given its more attractive margin profile, this shift is contributing to a healthier revenue mix and strengthening the long-term profitability of our cloud business. On MaaS, our Tianfan MaaS platform offers one of the most comprehensive model libraries, covering Baidu's Ernie family, as well as virtually all of China's leading models. A key priority for Tianfan is to make model inference at scale more reliable and cost-efficient for customers. Leveraging our deep expertise in AI infrastructure and engineering, we further enhanced model serving through continued inference optimization, delivering higher throughput and greater service stability while reducing latency and inference costs. In Q2, revenue from external customers' token usage on Qianfan grew more than ninefold year-over-year, primarily driven by rapid growth in daily average token consumption among these customers. Turning to foundation models, advancing learning and our overall model capabilities remains important to our next phase of AI-driven growth. Our commitment to foundation model innovation remains unwavering. As discussed in prior quarters, we reorganized our model teams into two groups with clearer mandates and greater focus across foundation models and applications. More recently, we welcomed a new generation of top AI talent to work on foundation models, further demonstrating our determination to compete and innovate at the forefront of AI. We believe these efforts will support the continued evolution of Ernie and strengthen the foundation for future innovation across both models and AI applications. Moving next to AI applications, where we continue to enhance product capabilities and expand real-world use cases. Let me begin with digital humans. As our digital human technology continues to advance, it is delivering stronger performance at lower cost and enabling an expanding range of use cases. From e-commerce live streaming and digital human videos to real-time interactive digital humans and our newly introduced video podcast, these advances are opening up far broader possibilities for how digital humans can be used across industries. Our digital human capabilities are gaining increasing recognition from clients. In Q2, we continue to win new clients, including leading companies across industries, while existing clients also meaningfully scaled their usage. Some of our clients started with a pilot and after seeing what our digital human technology could deliver, expanded their usage. A well-known Chinese internet company, for example, expanded its digital human live streaming deployment to approximately 2.5 times the previous level after just one quarter of use. Meanwhile, we continue to advance the global expansion of our digital human capabilities. Since launching our overseas digital human platform last quarter, we've seen encouraging momentum with its differentiated capabilities delivering compelling results for merchants and creators overseas. As demand continues to unfold across more industries and regions, we believe the long-term growth potential for digital humans remains substantial. Turning next to MiaoDa, our VIVE coding platform, with the launch of MiaoDa 3.0 last quarter, users can now generate standalone mobile apps for both Android and iOS using natural language. Applications that once required a professional development team, a lengthy development cycle and significant investment can now be completed far more easily through MiaoDa, even directly from a phone. We are seeing users engage with MiaoDa more deeply. An increasing number of users are moving beyond one-off experimentation and returning to MiaoDa to continue developing. It is reading on and refining their applications over time, reflecting stronger user stickiness. In June, Miaoda's monthly active users increased by 67% compared with March. Adoption is also expanding across industries ranging from technology and education to healthcare, manufacturing, financial services, and logistics, demonstrating Miaoda's applicability across diverse business scenarios and its broader commercialization potential. We are also applying AI to help enterprises solve complex operational problems. A good example is PhamoAgent, which can autonomously explore possible solutions to identify the best ones. Following the launch of PhamoAgent 2.0 last quarter, we have continued to improve its usability and expand the scenarios it can address. Phamo agent has attracted growing interest from leading enterprises and begun to gain early commercial traction this quarter. We are pleased to see Phamo agent moving beyond efficiency gains to help enterprises optimize their operations and deliver real, tangible business value. As its capabilities continue to advance, we believe its potential will continue to grow. Another key direction for our AI applications is general purpose agents. Earlier this year, we launched DouMate, our general purpose agent for everyday productivity with seamless access across PC and mobile. In Q2, we introduced an enterprise version and continued to expand Duminate's proprietary Baidu skills and specialized toolkits, broadening the range and sophistication of tasks it can support. Meanwhile, our flagship consumer-facing AI applications, Baidu Wenku and Baidu Dry, continue to embrace AI across the board, introducing new AI capabilities, sharpening existing ones. and this quarter rolling out an upgrade to GameFlow that brings AI more deeply into users' everyday workflows. In June, AI DAU penetration across Baidu Wenku and Baidu Drive increased by 27.4% year-over-year, reflecting broader adoption of their AI-powered features. Turning to AI search, we continue to improve both the quality of AI-generated answers and the overall user experience. Users are increasingly receiving answers that are more reliable, better structured, and more effectively presented. At the same time, hallucination rates remain low while our models became more effective at assessing content quality, helping reduce the incidence of low-quality answers. Together, these improvements draw better user experience and higher user satisfaction. We also further integrated AI search with Ernie Assistant, extending the search experience beyond one-time answers into more seamless and interactive conversations that can better address users' follow-up questions and broader needs. In June, Ernie Assistant's daily active users grew 83% year-over-year, while daily average conversation rounds more than tripled, reflecting growing user adoption and deeper engagement with this evolving search experience. Turning now to AI in the physical world, let me discuss ApolloGo, our autonomous ride-hailing service. This quarter, we continue to advance global expansion while further enhancing safety, operational performance, and the rider experience. Hong Kong marked an important milestone for ApolloGo this quarter. In June, we received Hong Kong's first permits for fully driverless testing and began testing on Airport Island in July. This made ApolloGo the first autonomous ride-hailing service provider globally to conduct fully driverless testing in a right-hand drive, left-hand traffic robotaxi market. Hong Kong is one of the world's most sophisticated urban mobility markets with a complex operating environment and rigorous standards for both technology and operations. Reaching this milestone in Hong Kong provides strong validation of the maturity and adaptability of our technology and operational capabilities. The experience we have gained in Hong Kong is already helping us advance more efficiently in London. In July, ApolloGo began open-road testing there in partnership with Uber and Lyft. Together, our progress in these two markets demonstrates our technology's ability to generalize across different operating environments, giving us greater confidence in expanding into more and more high-value right-hand drive, left-hand traffic robotaxi markets over time. We also made progress across several other international markets. In Dubai, we launched fully driverless commercial operations in July and now operate at the largest scale among fully driverless autonomous ride-hating services in the city with rides available through both the Apollo GO and Uber apps. In Switzerland, we began open-road testing in partnership with Hostbus. We also signed a memorandum of understanding with Kazakhstan's Turlov Private Holding Limited to jointly explore autonomous ride-having services in the country. Overall, ApolloGo delivered around 1 million fully driverless operational rides in Q2. As of June 2026, cumulative rides provided to the public by ApolloGo exceeded 23 million. Ride volume during the quarter was temporarily affected by operational adjustments in certain domestic cities due to regulatory considerations. Over this period, we conducted a systematic review to further strengthen the robustness of our autonomous driving systems and the rigor of our operational processes. As of August, operations in the affected cities had begun to resume on a stronger footing. Meanwhile, we continued to expand our operations across other domestic markets. We are confident that ride volume will regain momentum over the coming quarters as we steadily ramp up operations and pursue further expansion. In Q2, we continue to raise the bar on safety and the rider experience. As of the end of June, our fully driverless vehicles recorded an average of approximately one airbag deployment every 14.4 million kilometers, underscoring our industry-leading safety performance. We also enhanced pick-up and drop-off point recommendations to reduce walking distances and avoid unsuitable stopping locations, while further improving perception and motion planning capabilities to deliver smoother and more consistent rides. These improvements represent an even higher operating standard when we intend to build on as we continue to integrate ApolloGo more seamlessly into urban transportation systems, making it a more convenient and trusted part of everyday mobility. Looking ahead to the second half, our priorities for ApolloGo are clear. Further enhance our safety standards and operational capabilities advance our global expansion, scale our fleet and ride volumes, and bring more cities to unit economic spread even. We believe progress across these priorities will further strengthen ApolloGo's leadership in autonomous ride hailing and lay a stronger foundation for scaling its operations safely and sustainably over the long term. To summarize, the progress we made across our full AI stack this quarter reaffirms Baidu's transition into an AI-first company and further strengthened the foundation for our next phase of growth. We are also actively expanding our AI businesses into global markets and are encouraged by the progress we are already seeing, including in AI applications and robot taxing. With this stronger foundation, we believe we are well-positioned to capture a broader range of opportunities across markets over time. With that, let me turn the call over to Henry to go through the financial results.

Thank you, Robin. and hello everyone. We were pleased with the continued momentum of Baidu core AI-powered business this quarter. Revenue from Baidu core AI-powered business reached RMB 12.5 billion and continued to account for half of Baidu general business revenue. AI cloud infra revenue grew approximately 50% year over year, with GPU cloud revenue growing 283% year over year in Q2. This performance reinforces AI-powered business as a key driver of Baidu's long-term growth. In addition, we advanced an important capital market initiative to broaden access to capital markets and create long-term shareholder value. In July, our board approved a motion to pursue the voluntary conversion of our Hong Kong listening to dual primary status. Since then, we have submitted our application and received Hong Kong Stock Exchange's acknowledgment. We also plan to convene an extraordinary general meeting on August 26 to seek shareholder approval for certain related matters. We currently expect the conversion to become effective within this year, subject to the approval of the shareholders and the Hong Kong Stock Exchange. Once effective, we believe the dual primary listing will broaden our investor base, enhance the liquidity of our shares, and provide greater flexibility in accessing capital across both markets. As we move forward, AI remains central to Baidu's long-term growth and competitiveness. We will continue to invest with conviction and discipline in the capabilities and businesses where we see the strongest long-term opportunities. Now, let me walk through the details of our second quarter 2026 financial results. Total revenue of Baidu was RMB 31.3 billion, decreasing 2% quarter over quarter and 4% year over year. Revenue from Baidu General Business was RMB 25.2 billion, decreasing 3% quarter-over-quarter and 4% year-over-year. Revenue from iQiyi was RMB 6.3 billion, increasing 1% quarter-over-quarter and decreasing 5% year-over-year. Cost of revenues was RMB 19.1 billion, decreasing 3% quarter-over-quarter, primarily due to a decrease in costs related to AI cloud business. partially offset by an increase in traffic acquisition costs and increasing 4% year-over-year, primarily due to increases in costs related to AI cloud business. Operating expenses were RMB 9.2 billion, decreasing 1% quarter-over-quarter and decreasing 17% year-over-year. The year-over-year decrease was primarily due to decreases in expected credit losses, channel spending expenses, and R&D personnel related expenses. Operating income was RMB 3.0 billion and operating margin was 10%. Non-GAAP operating income was RMB 3.8 billion and non-GAAP operating margin was 12%. Total other income net was RMB 184 million compared to RMB 626 million last quarter and RMB 4.9 billion for the same period last year. The year-over-year decrease was primarily due to a decrease in fair value gain from long-term investments and an increase in net foreign exchange loss arising from exchange rate fluctuation between renminbi and the US dollar Income tax expense was RMB 1.0 billion compared to RMB 528 million last quarter and RMB 881 million for the same period last year Net income attributable to Baidu was RMB 2.3 billion Net margin for Baidu was 7%, and diluted earnings per ADS was RMB 5.74. Non-GAAP net income attributable to Baidu was RMB 2.6 billion. Non-GAAP net margin for Baidu was 8%, and non-GAAP diluted earnings per ADS was RMB 7.22. We define total cash and investments as cash, cash equivalents, restricted cash, short-term investments, net long-term time deposits, and how-to material investments. and adjusted long-term investments. As of June 30, 2026, total cash and investments were RMB 283.1 billion. Operating cash flow was RMB 3.4 billion. Baidu General Business had approximately 27,000 employees as of June 30, 2026. With that operator, let's now open the call to questions.

Ladies and gentlemen, We will now begin the question and answer session. If you wish to ask a question, please press star 1 on your telephone and vote for the question to be announced. If you wish to cancel your request, please press star 2. If you are on a speakerphone, please pick up the handset to ask your question. The first question today comes from Alex Yao with J.P. Morgan. Please go ahead.

Thank you, management, for taking the question. So with the multi-trillion parameter models emerging rapidly and pushing the frontier on benchmark performance, how does Baidu think about earnings competitive positioning from here? Following the recent addition of a senior foundation model talent, what are the key technical and product priorities for earnings? And what should investors expect from its next

This is Robin. First, from an industry perspective, foundation models are still evolving rapidly. Roughly every few months, a different model takes the lead in some capability. This shows the field remains highly dynamic and the competitive landscape is far from settled. In a market like this, we believe long-term competitiveness ultimately comes down to sustained technology investment, application-driven approach, and patience. Baidu has always been a company that believes in technology and is willing to commit to it for the long term. Our experience has repeatedly shown that meaningful technological innovation takes patience and persistence. Today, many of Baidu's important AI assets, including Kunlunxin and ApolloGo, are the result of more than a decade of sustained investment. They've become a key source of our differentiated competitiveness. And their performance and commercial value are gaining increasing broad recognition. So we are very proud of that. Ernie has likewise always been an important part of Baidu's AI strategy and full stack AI capabilities. We were among the first companies in China to invest in foundation models. There were trials and errors along the way, but our commitment to make earnings competitive remains unwavering. Going forward, we will continue to invest resources needed to drive earnings' ongoing development. As part of this effort, We have further optimized our organization and recently brought in top AI talent. We are confident in accelerating AI integration and bring early back into the top tier of foundation models. Looking ahead, we will continue to take an application-driven approach. Foundation models span a very broad range of capabilities and no single model can lead in every dimension at all times. We will therefore focus on capabilities that matter most to Baidu's applications and make earning strongest in this area. Planning, AI search, digital human, Miao Da, Fa Mo, and general purpose agents like Bluemate. These applications are vital parts of Ernie's continuous improvement. I take AI search as an example. When we improve Ernie's ability to understand user intent and assess content quality, we apply those improvements directly to search and feed. This lets us quickly see the results, identify what still needs work, and feedback the relevant data into model training, which makes our model better at user intent understanding and content quality assessment. And we see this loop as an important path for earnings development, one that translates technological progress more directly into better product experiences and real user and commercial value and then ultimately benefiting a broader range of users and businesses. Thank you.

The next question comes from Alicia Yeh with Citigroup. Please go ahead.

Thank you. Good evening, management. Thanks for taking my questions. My question is on cloud. So Baidu AI Cloud Infra revenue has maintained strong growth. Could management discuss the key growth drivers and also your outlook for the revenue growth over the next two quarters? and also how should we think about the long-term margin potential as the business scale. Thank you.

Hi, Alicia. This is Dou. AI Core Infra, Renew, grew 50% year-over-year in Q2. This remains a robust growth rate and above the industry average, I believe. So over a longer horizon, our AI cloud infrastructure has sustained rapid growth for several consecutive years, consistently outpacing the industry. The center of this quarter was the GPU cloud, whose revenue grew 283% year-over-year, marking its fourth straight quarter of triple-digit growth and accelerating further from 100 84% in Q1. Looking ahead, we see several drivers supporting a continued growth. Currently, demand for AI computing in China remains very strong, and as AI becomes more deeply embedded in real-world applications and business workloads, particularly as inference continues to scale rapidly, We expect demand to grow up further. Meanwhile, our customer base is also expanding rapidly, with new customers of different sizes adopting our AI Cloud Infra, while existing key customers keep increasing both usage and spending. Demand is also broadening across industries and use cases, including Internet, gaming, embodied AI, autonomous driving, smartphones, financial services, and others. Actually, most importantly, we have built and continued to strengthen differentiated full-stack AI architecture, spending tips, cloud infrastructure, models, and applications with competitive offerings at every layer. At the application layer, in particular, We moved early to build a portfolio of agents and AI applications with products such as FAMO, Dumit, Miota, and Yijian, gaining traction and strengthening our ability to capture an increasingly diverse range of AI opportunities. Based on current demand trends, our customer pipelines and these differentiated advantages, So we feel confident that AI Cloud Infra can maintain strong growth in the second half with potential for further acceleration. On the profitability side you just mentioned, we are pleased with the continued improvement alongside rapid revenue growth. In Q2, AI Cloud Infra profit and margins both increased year-over-year Going forward, we think several factors should support further margin extension. First, GPU cloud is growing significantly faster than AI Cloud Infra in general, and it continues to represent a large share of the mix. It also carries a more attractive margin profile than traditional CPU cloud. with further room for margin improvement as it scales, supported by a continued optimization of its product and the customer mix, better resource utilization, and greater operating efficiency. So as GPU cloud's contribution increases, the mix shift should continue to lift overall margins. Second, on mass. Revenue from external customers' token calls on Qianfan is growing very fast. WellMathView represents a relatively small share of our AI Cloud Infer revenue today, so the early momentum we are seeing is very encouraging. As usage skills and unit inference costs keep coming down, we believe over the longer term, mass-related businesses will be able to unlock more profit potential and become an increasingly meaningful contributor to margins. Finally, our full-stack AI capabilities and self-developed chips also provide end-to-end cost advantages that should support margin expansion. Taken together, we think there's still a lot of room for AI cloud infrared margins to improve over the long term. Thank you.

The next question comes from Miranda Zhuang with Bank of America Securities. Please go ahead.

Thank you, management, for taking my question. My question is about margin. So with AI-powered business now accounting for half of the revenues and also CapEx continuing to ramp, So how to think about Baidu's operating margin trajectory and how will management balance the continued AI investments with profitability? Thank you.

Thank you, Miranda. This is Henry. This quarter, AI-powered business continued to account for half of the Baidu general business revenue. Further on this morning, AI's positioning at the center of our business Within AI power business, AI cloud infrastructure sustained rapid revenue growth, with profit also growing quickly, and the margins improving year over year. Within AI cloud infra, our GPO cloud business, which typically carries a better margin profile, continue to increase as a percentage of revenue. As this next shift continues, together with a strong market demand, and the cost advantage we get from our self-developed chips and full-stack AI capabilities. We believe there is still meaningful room for AI cloud infrastructure margins to expand over the long term. As the business scales, we also expect better resource utilization and a greater operational leverage to provide further support for the margin expansion. We also see attractive long-term profitability potential in our AI applications. Many of these applications are sticky and substitution-based by nature, with the potential to deliver increasingly attractive margins over time at this scale. As adoption, growth, and monetization progresses, we expect them to become a more meaningful contributor to overall profitability. Meanwhile, I think we are still in an AI investment cycle, and our commitment to that investment is unwavering. We invest with conviction, but just as importantly, we spend wisely and stay closely focused on the ROI. Our investments are driven by a clear demand from both customers and our internal business, allowing much of where we invest to be put to work quickly and become begin contributing to revenue relatively soon. Meanwhile, we are continuously strengthening our supply chain management capabilities, which we believe will increasingly help us improve capital efficiency as we scale. Together, these strengths give us a good visibility into returns and a confidence in our ability to improve investment efficiency over time. That said, different AI investments play out on different timelines. and we will take longer to fully deliver their value. Some of them will take longer. We are now in a critical phase of investment and we intend to keep investing decisively in the area that matters most to our long-term competitive position while maintaining the same discipline around IOIC, operating efficiency and cash flow. As our AI business scale further and the monetization matures, We believe these investments will increasingly translate into some and more sustainable profit growth. Thank you.

The next question comes from Lincoln Kong with GS. Please go ahead.

Thank you, management, for taking my question.

Could you update us on the progress of Kunlunxin's proposed listing and the key milestone ahead? I'm wondering what will drive its future growth, and how does management view its long-term commercial potential and strategic role within Baidu AI ecosystem?

Thank you.

Okay, I'll take it. This is Dou. The listing process for Kunting is still ongoing and we will update the market as soon as we have more to share. From a business perspective, we remain very confident in Kunting's long-term growth and commercial potential for a few reasons. First, across the industry, demand for AI compute continues to grow across both training and inference. As model capabilities keep improving and more applications move into real-world use, especially as agents advance and expand into a wider range of use cases. So we are seeing inference pick up pace in particular. So I believe this trend will continue creating a long-term structural growth opportunity for the AI chip industry. Secondly, the domestic market carries significant growth potential, while with supply likely to remain constrained for some time. Against this backdrop, customers are increasingly seeking high-performance, reliable, and cost-efficient domestic VR chips. This creates substantial opportunities for chip providers with strong technical and the ability to deliver at scale. Following more than a decade of investment, Kunsheng has built solid capabilities in chip performance, hardware-software integration, compatibility with mainstream models and frameworks, and large-scale deployment, earning growing recognition from customers. Those are the things that put Kunmingxin in a good position in this market and captured the commercial opportunities arising from China's growing AI computer news. Thirdly, within Baidu's AI ecosystem, Kunmingxin is an important part of the infrastructure layer in our foodstack AI architecture, expanding to cloud infrastructure, Models and Applications. The close coordination across these layers enables end-to-end optimization in allowing us to deliver greater performance, reliability, and cost efficiency. So this supports the long-term deployment of AI Cloud Infra and our other AI businesses while further strengthening the Competitiveness of Baidu's full-stack AI capabilities Looking ahead, we expect Kunlunxin to keep playing a meaningful role in our AI infrastructure capturing a broader range of commercial opportunities and serving a wider range of market needs Thank you

The next question comes from Wei Xiong with UBS. Please go ahead.

Sure, thank you. Good evening, management. Thank you for taking my question. Could you walk us through the timeline for the Hong Kong primary listing conversion and potential stock connect inclusion? Also, what's the strategic rationale and how could it affect Baidu's investor base share equity and valuation over time? Thank you.

Thank you. This is Henry.

Let me start with the timeline. Our board has approved the conversion to a dual primary listing back in July. We also filed our application with the Hong Kong Stock Exchange and received its acknowledgment. The next step is our extraordinary general meeting scheduled on August 26. During that meeting, we will seek shareholder approval for 30 matters required in preparation for conversion. And from there, we expect the conversion to take effect within this year, subject to approval of the Hong Kong Stock Exchange and other applicable conditions. On southbound Stock Connect, we are also actively preparing for potential inclusion following the conversion and hope our shares can be included at the earliest opportunity. And of course, This will remain subject to the applicable eligibility requirements and review of procedures and the decisions for the relevant exchange. As for the rationale, dual primary listing is really about broadening our investor base, enhancing the liquidity of our shares, and giving us greater flexibility in accessing both the Hong Kong and the U.S. capital markets. It also allows more investors, particularly in Asia, to better understand and participate in Baidu's value as an AI-first company. Looking further out, if we achieve Stock Connect inclusion down the road, we would expect that to meaningfully expand participation from mainland China investors specifically, which should support an even more diversified shareholder base over time. We will be happy to keep you updated as we make further progress.

The next question comes from Thomas Chong with Jefferies. Please go ahead.

Hi, good evening. Thanks management for taking my questions.

Could management update us about AI search progress across product capabilities, user experience, and monetization? We have seen online marketing revenue remain under pressure in Q2. What were the main factors, and how does management expect the business to trend in the second half? Thank you.

Hi, Thomas. This is Julius. Let me hear your question. I think over the past few quarters, our focus on the AI search transformations has been improving the quality of our AI answers through enhancing the user experiences a lot. Accuracy and authority has always been our core strengths, and we have reinforced them as the AI transformation moves forward. And now our AI search can better understand what users are looking for. The answers are more reliable, better structured, and presenting in richer formats. And meanwhile, hallucination rates remain low. Our models now are getting better at telling good content from bad. So we are facing more high-quality answers and fewer weak ones. Users have responded quite well on these changes, and we are seeing steady improvements in user satisfaction, the willingness to search, and retention. In this quarter, we further integrated the AI search with the earning assistant, turning one of the search answers into more coherent, interactive, multi-run conversations that better address the follow-up questions. and broader user needs. And we're also continuing to strengthen the tool use, multi-step planning, and the complex task executions to help users to get more done. Recently, the Earning Assistance Task Agent popped two influential sub-party agent benchmarks. The PinchBench v2, which is a global benchmark focused on the real-world complex tax complexion, and the SuperCruise xCloud evaluation of the leading domestic agent products. I think these results can help to reinforce the earning assistance leading capabilities in the tool use, multi-step planning, and task executions. That said, the competition in this industry remains very intense, and as new product forms like HR boards continue to get instructions, the ways users discover and Consume Information, Key Involving and Competition for Use of Time and Attention has intensified further. Meanwhile, we have continued to push forward with the AI search transformations while deliberately holding back on monetizing the AI search, both of which we have weighted on our advertising businesses in the near term. Given these dynamics are likely to persist, We expect our advertising business to remain under pressure in the second half. On monetization, our priority right now is still to getting the products and the user experience right. As model capabilities, the user experiences, and the task complexions continue to improve, we believe that more monetization opportunities, which fit naturally into the AI experiences, will emerge in future. Thank you, Thomas.

The next question comes from Ellie Jiang with Macquarie. Please go ahead.

Great. Thank you so much, management, for the opportunity. I have a question on Robotaxi, please. So with China's recent introduction of the new Robotaxi policies, how does management view the evolving regulatory environment? How should we think about ApolloGo's relative focus and also the pace of expansion across domestic overseas market? and it would be great if management can talk about the progress that ApolloGo has made in the overseas commercialization side. Thank you.

Hi, this is Robin. Let me answer this question. The global robot taxi industry is evolving very quickly. In the past, the industry's focus was on whether robot taxis could deliver a safe are all comfortable riding experience. Today, that focus has expanded to whether robot taxis can operate reliably at scale and fit into the broader transportation system. In line with this trend, major markets around the world are also iterating on and refining their regulatory frameworks for robot taxis. In China, for example, the country's first mandatory national standard on safety requirements for Level 3 and Level 4 automated driving systems was recently issued. And ApolloGo contributed its extensive technical and operating experience to the L4 requirements under this standard. Safety has always been our top priority. and we maintain an industry-leading safety record globally. We will continue to uphold high standards on safety and operations. More broadly, clearer, more systematic regulatory frameworks will help raise operational standards across the industry, build public trust, and lay a stronger foundation for the long-term orderly growth of Robotexis. Against this backdrop, we remain positive on ApolloGo's global expansion. We do not view domestic and international markets as an either-or choice. We are highly open and adaptive. We assess each city based on its regulatory framework. Mobility Demand, Right Pricing, Road Conditions, and Commercial Viability, and setting our pace of entry and expansion accordingly. Backed by proven technology and operating experience, we are ready to move quickly and scale efficiently in any city where regulations and market conditions Our goal is to go deep and build a solid presence in every city we enter, regardless of country boundaries. This is reflected in our progress across different cities. In Dubai, ApolloGo has entered fully driverless commercial operations and is scaling up and we now operate at the largest scale among robot taxi services providers over there. In London, we are advancing testing and development with partners including Uber and Lyft. In Hong Kong, we became the first robot taxi service globally to conduct fully driverless testing in our right-hand drive, left-hand traffic market. In Shenzhen, the number of rides are picking up very quickly, making it one of our largest markets. As our fleet expands and our operating model matures, we expect vehicle and operating costs to keep coming down. While scale brings additional efficiency gains, in the past, ApolloGo achieved unit economics break-even in a market with relatively low taxi fares. In the future, in overseas markets with higher ride prices, our low-cost vehicles and proven operating models have the potential to deliver even stronger unit economics. The international market outside of US and China is also larger than the domestic China market. So the addressable opportunity is quite substantial. Looking ahead, supported by our advantages in technology, cost, and operations, we are confident in bringing more cities to unit economic break-even. Thank you.

Ladies and gentlemen, that does conclude our conference for today. Thank you for participating and you may all disconnect.