Baidu, Inc. Q2 FY2025 Earnings Call

Hello, and thank you for standing by for Baidu's Second Quarter 2025 Earnings Conference Call. Today's conference is being recorded. I 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 2025 Earnings Conference Call. Baidu's earnings release was distributed earlier today, and you can find a copy on our website as well as our 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 Securities 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 filings with the SEC and 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 unaudited non-GAAP financial measures. Our press release contains a reconciliation of the unaudited non-GAAP measures to the unaudited most directly comparable GAAP measures and is available on our IR website at ir.baidu.com. As a reminder, this conference is being recorded. In addition, 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 Core's total revenue was RMB 26.3 billion. Our AI cloud continued to gain momentum, growing 27% year-over-year to RMB 6.5 billion. Notably, Baidu Core's non-online marketing revenue exceeded RMB 10 billion for the first time. That's up 34% year-over-year. This performance helped offset the near-term headwinds in our online marketing business. This year marks Baidu's 20th anniversary as a public company. Over the past 2 decades, we remain grounded in our belief in technology and innovation. Today, technological advancement is unfolding at an unprecedented pace. We've embraced the mega trend with an open mind, experimenting boldly, adapting quickly, and engaging deeply with AI frontiers. Amid rapid evolution, we've identified and doubled down on a few directions we believe hold the greatest long-term value and are deepening our efforts with increasing clarity and confidence. Foundation model development remains a key focus area where we are actively exploring the frontier of foundation model research and pushing the boundaries of AI capabilities. With an application-driven approach, we see earnings intuition towards areas with real-world application value, such as the fundamental AI transformation of Baidu Search and our industry-leading digital human technology. Take digital human as a prime example, which represents one of the best applications of our ERNIE models. This quarter, powered by ERNIE, our digital human technology reached new levels of realism and capabilities, matching or even exceeding human performance in certain scenarios. A standout case was a live stream featuring the digital human of a top influencer in China, which generated tens of millions in GMV fully powered by ERNIE series models, closely mirroring the real person's communication style. Our multi-model capabilities delivered industry-leading visual realism with nuanced facial expressions, gestures, and body movements that responded naturally to conversation flow in real time, achieving next-level performance that sets new standards in digital human technology. Beyond this flagship case, digital humans are empowering our broader merchant base with performance that already surpasses human live streaming hosts in many scenarios. Going forward, we will continue accelerating foundation model integration, strategically focusing our efforts on areas with application value where we can maintain our most competitive capabilities. Beyond the model capabilities, our unique 4-layer end-to-end AI architecture has become a core competitive advantage and represents a key focus in our AI cloud business where our full-stack AI capabilities are driving healthy growth. As the infrastructure layer, we achieved a critical system engineering breakthrough this quarter by completing the large-scale stable deployment of prefiled detailed separation architecture. This breakthrough significantly improves inference on currency and resource utilization while substantially reducing inference costs. The achievement was made possible by the end-to-end optimization enabled by our unique 4-layer AI architecture. At the same time, each layer remains open, giving customers flexible choices between Baidu's proprietary and third-party options. As a result, we continue to improve the cost-effectiveness of our AI cloud products and solutions, reinforcing our position as China's top-tier cloud provider in the AI era. Meanwhile, our industry-leading MaaS platform, Qianfan, continues to evolve to better support enterprise clients in building models and facilitating AI application development. Qianfan features a comprehensive model library covering nearly all mainstream foundation models on the market. This quarter, we further expanded the library with a range of new models, including our newly offered ERNIE 4.5 series, additional third-party multi-model solutions, and other leading options enabling greater flexibility across enterprise use cases. Leveraging our breakthrough in cloud infrastructure, Qianfan delivers enhanced stability, higher concurrency, and lower inference costs when running models, meeting our superior price performance. On the toolchain front, Qianfan's toolchains are among the most comprehensive with industry-leading reinforcement learning and post-training tools for our model development. In Q2, Qianfan was further enhanced to support a wider range of AI tools and functions that can be accessed via the MCP or API, including Baidu's proprietary capabilities such as Baidu AI Search, Baidu Wiki, Baidu Maps, as well as selected third-party capabilities like payment services. These enhancements helped simplify AI application development and continue to solidify Qianfan's leadership as one of China's top MaaS platforms. Autonomous driving remains one of the most promising areas where we've invested heavily, representing a critical frontier in physical world AI. Following the successful validation of our urban model at the end of last year, Apollo Go is now scaling rapidly. In Q2, Apollo Go provided over 2.2 million fully driverless rides to the public, marking a 148% year-over-year increase, which is our strongest quarterly growth in 2 years. Also, Apollo Go's global expansion has gained solid momentum, highlighted by two strategic partnerships with leading global ride-hailing platforms. In July, we announced a multi-year strategic partnership with Uber. Under this partnership, thousands of Apollo Go's fully autonomous vehicles will be deployed on the Uber platform across multiple international markets, with initial rollouts planned for Asia and the Middle East. This milestone was followed by our partnership with Lyft in August, which will also bring thousands of our fully autonomous vehicles to key European markets through the Lyft platform. Starting with Germany and the United Kingdom, and expanding across Europe over time. Our expansion into international markets is built on a strong foundation. In China, we have already achieved positive unit economics in markets where ride fares are much lower than those in major overseas markets. That's why these global partnerships are both logical and strategic, positioning us to capture greater value in higher fare markets while scaling efficiently. Leveraging our partners' local market presence, we can accelerate market entry across different continents and achieve faster deployment while maintaining a cost-efficient, asset-light business model. In markets we've already entered, we continue to make encouraging progress in Hong Kong, one of the world's most complex right-hand drive cities. We recently expanded our testing coverage to include Tongcheng and Southern District, advancing our open road testing into more complex urban scenarios across both commercial and residential areas. Also, we further strengthened our presence in the Middle East in Dubai and Abu Dhabi, where we started open road testing in designated areas in August. Notably, Apollo Go leads the world in the right-hand drive robotaxi market. This is a space where hardly any companies of our kind have entered, and we've made by far the most progress. The rapid progress we are making in Hong Kong really shows our global leadership. It's proof of how adept our technology is and how mature our operations have become across all kinds of environments. Our experience there provides us valuable insights for entering other right-hand drive markets, strengthening our confidence in scaling Apollo Go globally. With solid progress quarter by quarter, we are more confident than ever in Apollo Go's international potential. As China's largest autonomous ride-hailing service provider and a global leader in this space, Apollo Go continues to combine industry-leading technology, extensive operational experience, and extraordinary safety records to bring safe, comfortable, and affordable autonomous ride-hailing services to more markets worldwide than anyone else. In our mobile ecosystem, transforming our products with AI remains a strategic priority, especially for our legacy consumer-facing product, Baidu Search. Baidu is at the forefront of applying AI to transform search globally rather than simply inserting AI summaries into search results. We are fundamentally revolutionizing the search experience by completely replacing static structural hyperlinks with intelligent, structured, and multi-model first AI-generated responses. These responses start with relevant multi-model content right at the top, making complex information more accessible to a broader user base and therefore creating a more intuitive experience. In Q2, our AI transformation continued to accelerate, with AI-generated content reaching over 50% of mobile search result pages by the end of June, up from 35% in April. By July, 64% of mobile search result pages contained AI-generated content presented in a structured and multi-model first format, marking the broader rollout of our innovative AI search experience. This AI transformation reached over 90% of Baidu App's monthly active users in July, with over 60% of such search result pages starting with rich media elements such as images or videos. As we advance our AI transformation, the expanding content ecosystem across Baidu provides meaningful support. Leveraging ongoing progress in Gen AI and multi-model capabilities, Baidu's AI-generated content has grown significantly in both scale and quality, providing more high-quality content for search results. AI-generated multi-model content, in particular, has experienced rapid expansion. For example, daily AIGC video generation reached millions of units starting from May, and daily AIGC video distribution within Baidu App has grown rapidly. We're delighted to see sustained improvements in user metrics. In June, Baidu App's MAU reached 735 million, representing a 5% year-over-year growth. The daily average time spent per user in Q2 increased by 4% year-over-year. Building on Search's ability to satisfy user intent, we are expanding its boundaries from providing smart answers to completing tasks and connecting real-world services. For instance, our agents engage users in multiround conversations, connect them with relevant service providers when needed, and facilitate end-to-end task completion across multiple verticals. We believe this represents a meaningful expansion of what Search can achieve, enabling users to seamlessly move from information to action. Now let me review the key highlights of each business sector this quarter. AI cloud revenue reached RMB 6.5 billion in Q2, up 27% year-over-year, with non-GAAP operating profit achieving year-over-year growth. The growth was primarily driven by the growing demand for our highly cost-effective end-to-end AI products and solutions. Within the enterprise cloud, which contributes the vast majority of AI cloud revenue, subscription-based revenue grew at a solid pace, signaling a healthier and more sustainable revenue structure. On the infrastructure layer, we continuously enhanced our resource management capabilities, achieving increasingly higher infrastructure utilization. Through ongoing end-to-end optimization across our 4-layer AI architecture, combined with increasingly refined and efficient GPU resource management capabilities, our large-scale key clusters have achieved over 90% utilization rates recently for key tasks. Our enhanced capabilities allow us to deliver better performance at lower cost and provide more competitive pricing for enterprise customers, establishing a virtuous circle, where our growing customer base and diversified workloads further improve resource utilization, reinforcing our sustainable revenue model. In Q2, our customer portfolio continued to improve as existing clients deepened collaboration and increased spending, while mid-tier enterprise clients demonstrated strong growth momentum. Additionally, this quarter marked several strategic partnerships with prominent companies across key verticals, including a leading lifestyle platform and top-tier gaming company in China. In the embodied AI industry, we have partnered with 20 companies cumulatively, including Shenzhen Institute of Artificial Intelligence and Robotics for Society. In autonomous driving, we established a partnership with Black Sesame Technologies on AI cloud infrastructure. This partnership reflects the strong recognition of Baidu AI cloud and affirms our competitive position in China's AI cloud market. Building on our full-stack AI capabilities, we are not only serving enterprise clients but also driving internal productivity and mass-market AI adoption at the application layer. Internally, we have widely adopted Comate, our AI coding assistant for developers. Comate's capabilities continue to improve, enabling a more efficient development workflow. In July, AI contributed to generating over 45% of our new code with developers providing oversight and approval. This has significantly boosted our engineering productivity and meaningfully enhanced our internal R&D efficiency. Externally, Miaoda extends these AI development capabilities to the broader community. Following Miaoda's official launch last quarter, we are now delivering 2 no-code capabilities that enable users to create applications, from mini-games to utility tools and websites, through simple natural language conversations with AI, requiring no programming expertise. As of July, users have created around 200,000 applications on Miaoda, all built completely without writing a single line of code. We are continuously enhancing no-code capabilities as we work toward our mission to democratize AI and empower anyone to innovate. Moving to intelligent driving, in Q2, Apollo Go provided over 2.2 million fully driverless rides to the public, which marks a 148% year-over-year increase. As of August, cumulative rides provided to the public have surpassed 14 million, underscoring the scale and maturity of our fully driverless operations. As of June, Apollo Go's global footprint spans 16 cities. To date, our fleets have accumulated over 200 million autonomous kilometers with an outstanding safety record, which is a testament to the capability and safety of our autonomous driving technology. Beyond global partnerships like Uber and Lyft, we are accelerating the rollout of asset-light business models domestically. This quarter, we established new partnerships with HelloRide and T3 Mobility, expanding our collaborative network with leading mobility service providers. Additionally, building on the partnership announced last quarter, Apollo Go's fully autonomous vehicle rental service officially went live on the Car Inc. app, offering users a new access point to our Apollo Go fleet. These partnerships enable us to rapidly scale our services while leveraging partners' operational expertise and existing customer bases, creating an efficient path to broader market penetration. Going forward, we are confident in further accelerating our global expansion and capturing significant value across multiple markets worldwide. For mobile ecosystems, we continue accelerating the AI transformation of search in Q2. In today's highly competitive mobile internet market, where new products and technologies are emerging and evolving faster than ever, user needs and behaviors are constantly shifting, making it essential for us to keep iterating at a rapid pace. While our AI transformation is progressing rapidly, it is still in the early stages with considerable room for optimization before reaching its full potential. We are not yet at the stage for large-scale monetization. Against this backdrop, we began prudent small-scale monetization testing in Q2 with user experience remaining our top priority. Early results have been satisfying. For example, some queries that were previously difficult to monetize are now showing potential. Agents maintained strong performance in driving better conversion efficiency, further validating our effectiveness. In Q2, revenue generated by our agents for advertisers grew 50% quarter-over-quarter, contributing 13% of Baidu Core's online marketing revenue, up from 9% in Q1. In parallel, digital humans gained traction as an innovative monetization avenue for our advertising business, particularly through AI-powered live streaming. We've seen steady growth in digital human adoption over recent quarters. Beyond serving live streaming hosts for merchants, they are being adopted at growing scales in healthcare, legal services, education, and automotive sectors. More advertisers recognize their value in boosting conversion performance through real-time user interaction and round-the-clock availability, leading to increased ad budget allocation towards digital humans. In Q2, revenue generated by digital humans increased by 55% quarter-over-quarter, contributing 3% of Baidu Core's online marketing revenue. To sum up, as we look ahead, Baidu will stay anchored in our long-term mission and move forward with greater focus and resolve as we continue to translate AI innovation into real-world value. Before we move to Q&A, I'd like to take a moment to welcome Henry, Mr. Haijian He, who recently joined us as Chief Financial Officer. With that, let me turn the call over to Henry to go through the financial results.

Thank you, Robin, and hello, everyone. I'm delighted to join the Baidu team and looking forward to working with all of you. Now let me walk through the details of our second quarter financial results. Total revenues were RMB 22.7 billion, decreasing 4% year-over-year. Revenue from Baidu Core was RMB 26.3 billion, decreasing 2% year-over-year. Baidu Core's online marketing revenue was RMB 16.2 billion, decreasing 15% year-over-year. Baidu Core's non-online marketing revenue was RMB 10 billion, up 34% year-over-year, primarily driven by the boost of AI cloud business. Within Baidu Core's non-online marketing revenue, AI cloud revenue was RMB 6.5 billion, increased by 27% year-over-year. Revenue from iQIYI was RMB 6.6 billion, decreasing 11% year-over-year. Cost of revenue was RMB 18.4 billion, increasing 12% year-over-year, primarily due to an increase in costs related to AI cloud business and content costs. Operating expenses were RMB 11.1 billion, decreasing 4% year-over-year, primarily due to a decrease in personnel-related expenses, partially offset by an increase in channel spending expenses. Baidu Core's operating expenses were RMB 9.7 billion, decreasing 5% year-over-year. Baidu Core's SG&A expenses were RMB 5 billion, increasing 6% year-over-year. SG&A accounted for 19% of Baidu Core's revenue in the quarter compared to 18% in the same period of last year. Baidu Core R&D expenses were RMB 4.7 billion, decreasing 14% year-over-year. R&D accounted for 18% of Baidu Core's revenue in this quarter compared to 20% in the same period of last year. Operating income was RMB 3.3 billion. Baidu Core's operating income was RMB 3.3 billion, and Baidu Core's operating margin was 13%. Non-GAAP operating income was RMB 4.4 billion. Non-GAAP Baidu Core operating income was RMB 4.4 billion, and the non-GAAP Baidu Core operating margin was 17%. Total other income net was RMB 4.9 billion, increasing 531% year-over-year, primarily due to an increase in the fair value gain and a pickup of earnings from long-term investments, partially offset by an increase in the net foreign exchange loss arising from exchange rate fluctuations between RMB and the U.S. dollar. Income tax expenses were RMB 881 million compared to RMB 1.1 billion in the same period of last year. Net income attributable to Baidu was RMB 7.3 billion, and the diluted earnings per ADS was RMB 20.35. Net income attributed to Baidu Core was RMB 7.4 billion, with a net margin for Baidu Core of 28%. Non-GAAP net income attributed to Baidu was RMB 4.8 billion. Non-GAAP diluted earnings per ADS was RMB 13.58. Non-GAAP net income attributed to Baidu Core was RMB 4.8 billion, with a non-GAAP net margin for Baidu Core of 18%. As of June 30, 2025, cash, cash equivalents, restricted cash, and short-term investments were RMB 124.2 billion. Cash, cash equivalents, research cash, and short-term investments, excluding iQIYI, were RMB 119.9 billion. As of June 30, 2025, cash, cash equivalents, short-term investments, and the long-term time deposits and held-to-maturity investments for Baidu Core were RMB 229.7 billion. Free cash flow was negative RMB 4.7 billion, and free cash flow, excluding iQIYI, was negative RMB 4.6 billion, primarily due to the increase in investment in AI business. We define net cash position as total cash, cash equivalents, restricted cash, short-term investments, net long-term time deposits, held-to-maturity investments, and others, less total loans, convertible senior notes, and notes payable. As of June 30, 2025, the net cash position for Baidu was RMB 155.1 billion. Baidu Core had approximately 31,000 employees as of June 30, 2025. With that, operator, let's now open up the call for the questions. Thank you.

Your first question comes from Alicia Yap, Citigroup.

And also welcome Henry as the new CFO. I have a question on your AI model. With the rapid model iteration, how do you view the current landscape? How do you position ERNIE strategically in the market and its alignment with Baidu's broader business strategy? And we also have heard that you are planning to launch ERNIE 5.0, could management share plans for ERNIE in the second half of this year and also the key focus area for this next version?

Alicia, this is Robin. Let me first give you our take on the current landscape. The pace of model iteration is faster than ever. We see multiple new models launched almost every week, and each new generation is stronger than the last. In recent months, we've seen models grow more capable, reaching the stage where their deeper logic and greater creativity now enable them to propose entirely new solutions we've never seen before. I believe this innovative ability is getting stronger. Meanwhile, the foundation model landscape is becoming more diverse and clearly not a one-size-fits-all situation, especially in China. Similar to EVs, you always have a lot of choices; different models excel at different tasks. Some are stronger in reasoning, some in coding, and some in multimodality. We will continue to see a market where multiple models coexist at very reasonable prices, and value creation will happen at the application level more than at the model level. Against this backdrop, ERNIE's positioning is clear. We take an application-driven approach to innovation. In fact, we've taken this approach since the first launch of ERNIE more than 2 years ago. Rather than spreading efforts across every possible direction, we stay focused on the strategically important areas that are valuable to us. We think we can deliver meaningful impact and sustain our leadership. For example, as we advance our AI search transformation, we direct our model capabilities towards generating and selecting multi-model search results. Our users love it, and so do our cloud customers who are paying for our Search API for the purpose of RAG in their Gen AI applications. Our hyper-realistic digital human technology also matches and even exceeds real human performance in the live streaming e-commerce scenario, which makes our model just better at convincing people to buy. Cloud customers are paying for these capabilities too. As we move into the second half and beyond, we will continue this acceleration. We're currently working on the next flagship version of ERNIE with significant improvements across key capabilities and expect to launch it as we are ready. In the meantime, we will continue to roll out iterations and updates on an ongoing basis for our existing models. We also keep monitoring industry developments to ensure our technology roadmap captures the most promising market opportunities. Thank you.

Your next question comes from Alex Yao from JPMorgan.

And Henry, all the best to your new role. So here's my question: how is the AI-powered search upgrade progressing in Q2 and Q3? Could management share updated metrics on how user behavior is shifting with the new experience, how should we think about the end game of AI search in terms of product format, user reach, and lastly, commercial potential?

Alex, thank you so much for your question. This is Julius. I think in Q2, we continue to accelerate transformation. As Robin has just mentioned, Baidu leads globally in using AI to transform search, and we are perhaps the most aggressive in revolutionizing search. We're probably the only company that has completely replaced the traditional links with intelligent AI answers that start with the multi-model content. This creates a more efficient, intuitive user experience and, unlike the current AI answers that remain mostly still text-based, our focus remains on delivering a better user experience. Beyond the MAUs and the time spent improvements, users exposed to AI Search now show higher UV and retention, indicating our next-generation search experience is driving stronger user satisfaction. As for the end game of AI Search, I think that is still an open question, but our path is quite clear. We are fundamentally restructuring search. First, instead of just indexing or linking to information, we are delivering intelligent AI-generated answers that begin with relevant multi-model content. Multi-model content now appears more at the very top of AI answers, with an increasing portion being AI-generated, high-quality AIGC content. As this expands on our platform, it directly enriches the search results and broadens what we can offer to users. Meanwhile, the AI is also empowering people across our ecosystem—from users to content creators, advertisers, and service providers—to produce more backed content. This includes enabling those who are not traditional content creators to participate in making our whole ecosystem more vibrant. For example, in July, we launched our MuseStreamer, our proprietary video generation model to facilitate AIGC video creation at scale. The latest version of MuseStreamer with significant updates will be launched tomorrow afternoon, so stay tuned as we are moving fast. In the second place, we are also evolving from providing information to completing tasks and connecting users with real-world services. For example, through the MCPs, we have connected search to external capabilities like our British Museum and Metropolitan Museum MCPs that can provide live explanations right in search. For more complicated needs, our agents help understand the user's intent and connect them with service providers when offline services are required. What we have done today is only the beginning, and search will continue advancing in capabilities and reach over time. Thirdly, we are also working towards the shift from general results to personalized pages, with AI Search understanding the individual context, memories, and preferences to generate tailor-made responses that deliver more intelligent, relevant answers while better matching users with the tools and services they need. Looking ahead, we will continue to accelerate AI transformation, which, in the short term, will weigh on our revenue. But over time, we believe the AI search will unlock exciting commercial possibilities, and the upside is substantial. Thank you for your question, Alex.

Next question comes from Gary Yu, Morgan Stanley.

I have a question regarding the AI cloud revenue. Can management provide a breakdown of the current revenue mix and margin profile? What's the split between subscription-based and project-based revenue? And how do you see them evolving in the coming quarters? And also, what's the margin profile looking like in the near term and over the long term?

Thank you, Gary. This is Dou. In Q2, AI cloud revenue grew 27% year-over-year to RMB 6.5 billion. For the first half of 2025, AI cloud revenue increased 34% year-over-year, accelerating from the low teens growth we saw in the first half of 2024. Enterprise Cloud has consistently outgrown our overall AI cloud business, and it remains the main growth driver. Within the Enterprise Cloud, subscription-based revenue accounts for more than half of the total and continued growing steadily in Q2. The growth was driven by strong momentum in subscription-based AI infrastructure, which grew over 50% year-over-year. We are seeing good traction with both top-tier and mid-tier customers. Our mid-tier customers in particular delivered notable revenue growth as they continue expanding with us, reflecting our broadening customer base. The other part of the enterprise cloud is project-based revenue, which is typically linked to customer deployments and will inevitably fluctuate from quarter to quarter based on contract timing and project schedules. We are currently conducting a careful review of our project portfolio and aim to gradually reduce the proportion of project-based revenue for greater revenue stability. Turning to Personal Cloud, which is a smaller part of our overall AI cloud business. Over the recent quarters, we've integrated Baidu Drive with Wenku and launched multiple new AI features. Recently, we opened up select AI features for free to encourage wider adoption. While this may involve some near-term trade-offs, we believe it helps deepen user engagement and positions us to benefit from broader AI adoption. On profitability, we achieved year-over-year growth in non-GAAP operating profit and maintained a healthy margin driven by a healthier revenue mix trending towards higher value offerings. While margins can move around from quarter to quarter due to dynamic market environments, we see clear potential for future improvement over the long run as we scale and optimize our mix. Thank you, Gary.

Our next question comes from Lincoln Kong from Goldman Sachs.

My question is about Search. Can management share more color on the reason for AI search monetization testing? Following your earlier comments on AI search opening up new monetization opportunities, could you elaborate on that? How are all pricing formats and business models evolving? What will the margin look like?

Thank you, Lincoln, for your curious question. I mentioned the monetization opportunities earlier, and let me elaborate here. From a product perspective, while our AI transformation already covers a large portion of the search results, we are still in the early stages with substantial room for improvement. We aim to further increase the penetration of multimodal content in such results and continue building and enriching our AI native ecosystem through MCP agents and on the foundation, enabling deeper, broader, or higher-quality connections to real-world services. As the AI transformation progresses and user experiences improve, monetization opportunities will naturally follow. The AI Search also brings native applications that feel intuitive and integrate, enhancing rather than interrupting the user experience. So, the vast majority of keywords that were previously difficult to monetize can now be monetized under AI Search, which should significantly expand our advertisement inventory over time. While initially, we will be very conservative with monetization to ensure we get the user experience right, the long-term upside is much higher. During our AI transformation, we are moving from simply generating sales leads to enabling real-world service delivery. This shift is made possible by new AI native commercial products such as agents or digital humans. These innovative products allow us to better capture and serve user needs through interactive conversations while connecting users with service providers in verticals like healthcare, travel, and education, where our agents and digital humans have already proven monetization capabilities. In Q2, we have already begun the early testing of the AI Search monetization. While it’s still in the early days, we have seen very encouraging signals, and we believe this trend will continue over time. That said, we always put user experiences first. So, we chose a very deliberate approach to AI Search monetization, and large-scale monetization has not started yet. At the same time, we have been aggressively accelerating our AI search transformation, including changing those queries with the highest monetization capabilities. In the near term, we do expect the revenue and margin will remain under significant pressure, but in the long term, we believe this positions us well for stronger growth.

Our next question comes from the line of Miranda Zhuang with Bank of America Securities.

My question is about cloud and GPU. How should we assess the sustainability of the AI-driven cloud demand, especially against the backdrop of a soft economy and intensifying market competition? With the easing of the H20 chip restriction, has management seen any meaningful improvement in supply? How do you think about the chip constraint? Will it remain a limiting factor for growth going forward?

Miranda, I would take those questions. Actually, we are seeing strong and growing demand for AI-driven cloud services as China's cloud market continues its shift towards AI-centric computing. The adoption of Gen AI and foundation models is accelerating, and AI has become a strategic focus for more and more companies. From what we've observed, demand is picking up across a wide range of sectors, not only from early adopters like internet companies, but also from a broader side of industries like utilities, financial services, and the public sector, where interest in AI-driven cloud solutions is rising quickly. Meanwhile, technological advances are filling strong new demand from emerging sectors such as embodied AI. We are effectively capturing new opportunities and working with leading players in this field, including 20 of China's promising embodied AI start-ups, four of which are China's top humanoid robot companies. The reason we can capture opportunities so quickly is our unique competitive positioning. What differentiates us is our ability to deliver highly cost-effective end-to-end AI cloud products and solutions, thanks to our full-stack AI capabilities. Taking our AI infrastructure as an example, we keep improving utilization and efficiency through our industry-leading resource management capabilities. By dynamically allocating computing resources, we can better match workloads with suitable resources and manage demand fluctuations, delivering better performance at lower cost. As a result, we can provide cost-efficient, reliable, and scalable cloud services that make it easy for companies to adopt AI with minimal effort and scale it into real business impact. On your question about chips, our focus remains on building a flexible AI architecture that maximizes GPU utilization and supports a variety of chips, including domestic chips. This enables us to better serve customers as the supply environment evolves. Looking ahead, we believe that a self-sufficient supply chain, together with increasingly major homegrown software stacks, will form a solid foundation for sustainable innovation in China's AI ecosystem. And clearly, Baidu is well positioned to lead the transition. Thank you.

Next question comes from Wei Xiong, UBS.

Given the near-term headwinds on ad revenue and continued investment in AI, I wonder what are the plans for cost optimization and efficiency improvement that can help protect margins? How should we think about the margin trend in 2026 and beyond?

Thank you. This is Henry. First of all, on AI investment, we remain committed to investing in AI and have made substantial investments throughout this year, particularly in the AI transformation of Search. As Julius mentioned earlier, our core legacy product, search, is undergoing a radical transformation. Over the past several quarters, we have ramped up investments to accelerate this transformation, which we believe is critical to drive long-term value. However, since the AI search monetization is still in very early stages and has yet to scale, our revenue and margins are under considerable pressure in the near term, with Q3 expected to be especially challenging. To help push through the near-term impact, we will actively drive internal efficiency gains. This includes strengthening resource coordination efforts across different business groups and improving overall resource utilization efficiency. On the other hand, while we remain committed to long-term AI investment, we'll be prudent in managing the pace to avoid future deterioration of fluctuations in margins. Looking further ahead, we see potential for margin improvement as our core advertising business recovers and stabilizes, and our non-advertising business expands their revenue share and improves their own profitability. We believe our strategic direction and disciplined execution should support a gradual recovery in profitability over time. On the outlook front, I think by the end of this year, we expect to have greater visibility into next year, at which point we'll provide a clear outlook beyond the current quarters for the long term. In parallel, we are carefully assessing different approaches to present and unlock hidden and unstated value in our assets. By doing so, we aim to strengthen our portfolio, create significant long-term value for shareholders, and support sustainable growth over the long term of our business. Thank you.

The next question comes from Thomas Chong, Jefferies.

My question is about the global autonomous driving landscape. We see it becoming increasingly competitive. How does Apollo Go assess its long-term differentiation against peers? How do the recent Uber and Lyft partnerships fit into your global expansion strategy? What is the roadmap for achieving sustainable profitability?

Yes. I think autonomous driving is one of the most exciting frontiers where AI is transforming the physical world. Success in this field requires cutting-edge technology, massive sustained investment, and disciplined execution over many years to achieve commercial operations at scale. As one of the earliest entrants, we have built an unparalleled foundation across all these areas and become an undisputed global leader in this field. With our business model validated, our current focus is on running real-world operations at scale. We have established global leadership in both left-hand and right-hand drive robotaxi markets. In the left-hand drive market, we were the first to achieve UE breakeven, and all our current operations in Mainland China are fully driverless. Globally, we are among the very few capable of scaled fully driverless and commercial operations in a single complex, large population area. In the right-hand drive market, we lead the industry globally. In Hong Kong, we've rapidly expanded our operational testing and advanced into increasingly complex urban scenarios following regulatory approval. Our technology stack and operational expertise are highly transferable across geographies, allowing us to adapt efficiently to new markets and regulatory environments. We have built a major advantage with RT6, the world's first and only production vehicle designed specifically for level 4 autonomous driving from day one. Unlike some retrofitted cars, RT6 is purpose-built from the ground up, focusing on safety system integration and cost efficiency. It has the lowest unit cost globally for Level 4 and is already running in our commercial operations at scale, giving us a big edge for broader rollouts. With this strength, we are confident about expanding to more cities worldwide, especially those with higher ride fares. The picture we have is that we have the lowest cost level 4 vehicle and the most efficient operation. We first achieved UE breakeven in Wuhan, where taxi fares are over 30% cheaper than those in Tier 1 cities in China and far below many overseas markets. Yet we still managed to prove our business model there. Such operational excellence and cost efficiency is unmatched globally. For us, expanding overseas means going from low fare markets to high fare markets, often with fares several times higher. Our huge cost advantage can deliver much stronger unit economics in most major cities worldwide. To accelerate our global expansion, we are also taking a proactive approach to global partnerships. As we mentioned in our prepared remarks, we announced a partnership with Uber in July and followed by Lyft in August. Our partnerships with these world's leading mobility platforms will help us enter and scale more quickly into global markets like the Middle East, Asia, and Europe. Looking ahead, we anticipate accelerating growth in ride volumes with our global operational fleet size multiplying. With that momentum, we are confident that Apollo Go will continue to lead the market and stay at the forefront of autonomous driving worldwide. Thank you.

That does conclude our conference for today. Thank you for participating. You may now disconnect.