百度 (BIDU) 2025 Q2 法說會逐字稿

Hello, and thank you for standing by for Baidu's second quarter 2025 earnings conference call. (Operator Instructions) Today's conference is being recorded. (Operator Instructions)

您好，感謝您參加百度2025年第二季財報電話會議。（操作員指示）今天的會議正在錄製。（操作員指示）

I now like to turn the meeting over to your host for today's conference, Juan Lin, Baidu's Director of Investor Relations. .

現在，我想將會議交給今天的會議主持人、百度投資者關係總監林娟。。

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.

大家好，歡迎參加百度2025年第二季財報電話會議。百度的獲利報告已於今天早些時候發布，您可以在我們的網站和新聞專線服務上找到一份副本。參加今天電話會議的有我們的共同創辦人兼執行長李彥宏、負責百度行動生態系統事業群 MEG 的執行副總裁羅榮、負責百度智慧雲端事業群 ACG 的執行副總裁沈抖，以及我們的財務長何海建。在我們準備好發言之後，我們將舉行問答環節。

Please note that the discussion today will contain forward-looking statements made under the Safe Harbor provisions of the US 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 SEC and Hong Kong Stock Exchange. Baidu does not undertake any obligation to update any forward-looking statements except as required under applicable law.

請注意，今天的討論將包含根據 1995 年美國信用證券訴訟改革法案的安全港條款做出的前瞻性陳述。前瞻性陳述受風險和不確定性的影響，可能導致實際結果與我們目前的預期有重大差異。有關這些風險和不確定性的詳細討論，請參閱我們最新的年度報告以及向美國證券交易委員會和香港證券交易所提交的其他文件。除適用法律要求外，百度不承擔更新任何前瞻性聲明的義務。

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.

我們的收益新聞稿和本次電話會議包括對某些未經審計的非公認會計準則財務指標的討論。我們的新聞稿包含未經審計的非公認會計準則 (Non-GAAP) 指標與未經審計的最直接可比較公認會計準則 (GAAP) 指標的調節表，可在我們的投資者關係網站 ir.baidu.com 上查閱。另請注意，本次會議正在錄製中。此外，本次電話會議的網路直播將在百度投資者關係網站上提供。

I will now turn the call over to our CEO, Robin.

現在我將電話轉給我們的執行長羅賓。

Hello, everyone. In Q2, Baidu Core's total revenue was RMB26.3 billion. Our AI cloud continued to gain momentum, growing 27% year over year to RMB6.5 billion. Notably, Baidu Core's non-online marketing revenue exceeded RMB10 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 marked Baidu's 20th anniversary as a public company. Over the past two 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 open mind, experimenting boldly adapting quickly and engaging deeply with AI frontiers.

大家好。第二季度，百度核心總營收為263億元。我們的AI雲持續保持強勁成長勢頭，較去年同期成長27%，達到人民幣65億元。值得一提的是，百度核心非網路行銷收入首次突破100億元。與去年同期相比成長了 34%。這項業績有助於抵銷我們在網路行銷業務近期面臨的阻力。今年是百度上市20週年。二十年來，我們始終堅信科技與創新。當今，科技進步正以前所未有的速度發展。我們以開放的心態擁抱大趨勢，大膽嘗試，快速適應，深入參與人工智慧前沿領域。

Amid rapid evolution, we've identified and doubled down on a few directions wherewe believe holds 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 ERNIE’s iteration towards areas with real world application value. such as the fundamental AI transformation of Baidu Search and our industry-leading digital human technology.

在快速發展的過程中，我們確定並加倍努力了一些我們認為具有最大長期價值的方向，並以越來越清晰的思路和信心深化我們的努力。基礎模型開發仍然是我們關注的重點領域，我們正在積極探索基礎模型研究的前沿，並突破人工智慧能力的界限。透過應用驅動的方法，我們看到 ERNIE 向具有現實世界應用價值的領域進行迭代，例如百度搜尋的根本性 AI 轉型以及我們業界領先的數位人技術。

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. Standout case was a live stream featuring the digital human of Luo yonghao, a top influencer in China. The 7-hour live stream generated tens of millions in GMV fully powered by ERNIE series models. ERNIE 4.5 Turbo generated the complete script, including dialogue, tone and action cues. closely mirroring the real person communication style.

以數位人作為主要例子，它代表了我們的 ERNIE 模型的最佳應用之一。本季度，在 ERNIE 的支持下，我們的數位人類技術達到了新的真實感和能力水平，在某些情況下可以匹敵甚至超越人類的表現。突出的案例是中國頂級影響力人物羅永浩的數位人類進行的直播。這場長達7小時的直播在ERNIE系列模式的助力下，創造了數千萬的GMV。ERNIE 4.5 Turbo 產生了完整的劇本，包括對話、語氣和動作提示，緊密反映了真實人物的溝通風格。

Our multimodal 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 of 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 iteration, strategically focusing our efforts on areas with application value where we can maintain our most competitive capabilities.

我們的多模式功能提供了業界領先的視覺真實感，細緻入微的面部表情、手勢和肢體動作可以即時自然地響應對話流，達到更高水平的性能，為數位人類技術樹立了新的標準。除了這個旗艦案例之外，數位人類還為我們更廣泛的商家群體提供支持，其性能在許多場景下已經超越了人類直播主播。未來，我們將持續加速基礎模型的迭代，策略性地聚焦在具有應用價值的領域，並保持最強的競爭力。

Beyond the model capabilities, our unique four-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 prefill decode separation architecture. This breakthrough significantly improves inference concurrency and resource utilization, while substantially reducing inference costs.

除了模型能力之外，我們獨特的四層端對端AI架構已成為核心競爭優勢，並代表了我們AI雲端業務的重點，我們的全端AI能力正在推動健康成長。作為基礎設施層，我們本季實現了關鍵的系統工程突破，完成了預填解碼分離架構的大規模穩定部署。這項突破顯著提高了推理並發性和資源利用率，同時大幅降低了推理成本。

The achievement was made possible by the end to end optimization enabled by our unique 4-layer AI architecture. spanning infrastructure framework models and applications, which allows us to coordinate improvements across all layers. At the same time, each layer remains open, giving customers flexible choices between Baidu's proprietary and third-party options. As a result, we continuously improving 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 continue to evolve to better support enterprise clients in building models and facilitating AI application development.

這項成就得益於我們獨特的 4 層 AI 架構實現的端到端優化，涵蓋基礎設施框架模型和應用程序，使我們能夠協調所有層的改進。同時，每一層都保持開放，讓客戶可以在百度專有和第三方選項之間靈活選擇。因此，我們不斷提高人工智慧雲端產品和解決方案的成本效益，鞏固我們作為人工智慧時代中國頂級雲端供應商的地位。同時，我們業界領先的MaaS平台千帆也在不斷發展，以更好地支援企業客戶建構模型和促進AI應用開發。

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 open sourced ERNIE 4.5 series, additional third-party multimodal models 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, maintaining our superior price performance.

千帆擁有完善的模型庫，幾乎涵蓋了市面上所有主流的基礎模型。本季度，我們進一步擴展了該庫，增加了一系列新模型，包括我們新開源的 ERNIE 4.5 系列、額外的第三方多模式模型和其他領先選項，從而為企業用例提供更大的靈活性。憑藉我們在雲端基礎架構方面的突破，千帆在運行模型時提供了更高的穩定性、更高的並發性和更低的推理成本，同時保持了我們卓越的性價比。

On the tool chain 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 caused via MCP or API including Baidu's proprietary capabilities such as Baidu Search, Baidu Wiki, Baidu Map 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.

在工具鏈方面，千帆的工具鍊是最全面的工具鏈之一，擁有業界領先的密集學習和後期訓練工具，可用於我們的模型開發。在第二季度，千帆得到了進一步增強，支援透過 MCP 或 API 實現的更廣泛的 AI 工具和功能，包括百度搜尋、百度維基、百度地圖等百度專有功能以及支付服務等選定的第三方功能。這些增強功能有助於簡化 AI 應用程式開發，並繼續鞏固千帆作為中國頂級 MaaS 平台之一的領導地位。

Autonomous driving remains one of the most promising areas we’ve long invested, which represents a critical frontier in physical world AI. Following the successful validation of our business model at the end of last year, Apollo Go is now scaling rapidly. In Q2, Apollo Go provided over 2.2 million fully driverless drives to the public. That's up 148% year over year, marking our strongest quarterly growth in two years. Also, Apollo Go global expansion has gained solid momentum, highlighted by two strategic partnerships with leading global ride-hailing platform.

自動駕駛仍然是我們長期投資的最有前景的領域之一，它代表了物理世界人工智慧的關鍵前沿。繼去年年底我們的商業模式成功驗證後，Apollo Go 目前正在迅速擴張。第二季度，Apollo Go 向公眾提供了超過 220 萬次全無人駕駛汽車。這比去年同期成長了 148%，創下了兩年來最強勁的季度成長記錄。此外，Apollo Go 全球擴張勢頭強勁，與全球領先的叫車平台建立了兩項策略合作夥伴關係。

In July, we announced a multiyear strategic partnership with Uber. Under this partnership, thousands of Apollo Gos 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 United Kingdom and selling across Europe over time.

7 月，我們宣布與 Uber 建立多年策略夥伴關係。根據此次合作，數千輛 Apollo Gos 全自動駕駛汽車將在 Uber 平台上部署，覆蓋多個國際市場，最初計劃在亞洲和中東地區推出。繼這一里程碑之後，我們在 8 月與 Lyft 建立了合作夥伴關係，並透過 Lyft 平台將數千輛全自動駕駛汽車推向歐洲主要市場。首先從德國和英國開始，然後逐漸在歐洲各地銷售。

Our expansion into international markets is built on a strong foundation. In China, we have already achieved positive unit economics in markets where wide fares are much lower than those in major overseas markets. That's why this 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.

我們向國際市場的擴張建立在堅實的基礎上。在中國，我們已經在票價遠低於主要海外市場的市場中實現了正的單位經濟效益。這就是為什麼這種全球合作夥伴關係既合乎邏輯又具有戰略意義，使我們能夠在有效擴大規模的同時在更高票價的市場中獲得更大的價值。利用我們合作夥伴的當地市場影響力，我們可以加速進入不同大洲的市場並實現更快的部署，同時保持成本效益高、輕資產的商業模式。

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 city. We recently expanded our testing coverage to include Tungchong and Southern District, advancing our open road testing into more complex urban scenarios across both commercial and residential areas.

在我們已經進入的市場中，我們繼續取得令人鼓舞的進展。香港是世界上最複雜的右側行駛城市之一。我們最近擴大了測試範圍，將東湧和南區也納入其中，將我們的開放道路測試推進到商業區和住宅區更複雜的城市場景。

Also, we further strengthened our presence in the Middle East in Dubai and Abu Dhabi, we started open road testing in designated areas in August. Notably, Apollo Go leads the world in 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 adaptable our technology is and how mature our operations have become across all kinds of environment.

此外，我們進一步加強了在杜拜和阿布達比等中東地區的業務，並於 8 月開始在指定區域進行公開道路測試。值得注意的是，Apollo Go 在右側駕駛自動駕駛計程車市場處於全球領先地位。這是一個幾乎沒有我們同類公司進入的領域，但我們迄今為止取得了最大的進展。香港的快速進步確實彰顯了我們的全球領導地位。這證明了我們的技術適應能力強，以及我們的營運在各種環境下已經非常成熟。

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 combines 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.

我們在那裡的經驗為我們進入其他右側駕駛市場提供了寶貴的見解，增強了我們在全球推廣 Apollo Go 的信心。隨著每個季度的穩步進展，我們對 Apollo Go 的國際潛力比以往任何時候都更有信心。身為中國最大的自動駕駛叫車服務供應商和該領域的全球領導者，Apollo Go 結合了業界領先的技術、豐富的營運經驗和卓越的安全記錄，為全球更多市場帶來安全、舒適、實惠的自動駕駛叫車服務。

In our mobile ecosystem, transforming our products with AI remains a strategic priority, especially 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 actual hyperlink with intelligent, structured and multimodal first AI-generated responses. These responses start with relevant multimodal content right at the top. making complex information more accessible to a broader user base and therefore, creating a more intuitive experience.

在我們的行動生態系統中，利用人工智慧改造我們的產品仍然是一項策略重點，尤其是我們傳統的面向消費者的產品百度搜尋。百度在應用人工智慧改變全球搜尋領域處於領先地位，我們不是簡單地將人工智慧摘要插入搜尋結果，而是透過用智慧、結構化和多模式的人工智慧生成的首個響應完全取代靜態的實際超鏈接，從根本上徹底改變了搜尋體驗。這些回應從頂部的相關多模式內容開始，使更廣泛的用戶群更容易獲得複雜的訊息，從而創造更直觀的體驗。

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 multimodal-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.

在第二季度，我們的人工智慧轉型持續加速，截至 6 月底，人工智慧產生的內容佔據行動搜尋結果頁面的 50% 以上，高於 4 月的 35%。截至 7 月份，64% 的行動搜尋結果頁麵包含以結構化和多模式優先格式呈現的 AI 生成內容，標誌著我們創新的 AI 搜尋體驗的更廣泛推廣。此次人工智慧轉型在 7 月涵蓋了百度 App 超過 90% 的月活躍用戶，其中超過 60% 的搜尋結果頁面以圖片或影片等富媒體元素為切入點。

As we advance our AI transformation, the expanding content ecosystem across Baidu provides meaningful support. Leveraging ongoing progress in Gen AI and multimodal capabilities, Baidu's AI-generated content has grown significantly in both scale and quality providing more high-quality content for search result. AI-generated multimodal content, in particular, has been a seen 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 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.

隨著我們推動人工智慧轉型，百度不斷擴大的內容生態系統提供了有意義的支援。隨著人工智慧和多模式能力的不斷進步，百度人工智慧生成的內容在規模和品質上都得到了顯著提升，為搜尋結果提供了更多高品質的內容。尤其是人工智慧產生的多模式內容，已經出現了快速擴張。例如，自5月以來，AIGC影片日生成量已達數百萬條，百度App內AIGC影片日分發量快速成長。我們很高興看到用戶指標持續改善。6月份，百度App月活躍用戶數達7.35億，年增5%。第二季每位用戶每日平均使用時間較去年同期成長4%。

Building on search 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 engaged 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.

基於搜尋能力滿足使用者意圖，我們正在擴展其邊界，從提供智慧答案到完成任務和連接現實世界的服務。例如，我們的代理商與使用者進行多輪對話，在需要時將他們與相關服務提供者聯繫起來，並促進跨多個垂直領域的端到端任務完成。我們相信這代表了搜尋功能的一次有意義的擴展，使用戶能夠無縫地從資訊轉向行動。

Now let me review the key highlights of each business sector this quarter. AI cloud revenue reached RMB6.5 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.

現在我來回顧本季各業務板塊的重點亮點。第二季AI雲營收達65億元，年增27%，非美國通用會計準則營業利潤實現年增。成長主要得益於對我們極具成本效益的端到端人工智慧產品和解決方案日益增長的需求。在貢獻了絕大部分AI雲端收入的企業雲中，基於訂閱的收入以穩健的速度成長，顯示收入結構更健康、更永續。

On the infrastructure layer, we continuously enhanced our resource management capabilities, achieving higher and 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.

在基礎設施層面，我們不斷增強資源管理能力，基礎設施利用率越來越高。透過持續對四層AI架構進行端對端優化，結合日益精細高效的GPU資源管理能力，近期大規模關鍵集群關鍵任務利用率已達到90%以上。

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. existing clients deepen the 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.

我們增強的功能使我們能夠以更低的成本提供更好的性能，並為企業客戶提供更具競爭力的價格，從而形成良性循環，不斷增長的客戶群和多樣化的工作負載進一步提高了資源利用率，強化了我們可持續的收入模式。第二季度，我們的客戶組合持續改善，現有客戶深化合作並增加支出，中型企業客戶表現出強勁的成長動能。此外，本季還與多個關鍵垂直領域的知名公司建立了戰略合作夥伴關係，其中包括中國領先的生活方式平台和頂級遊戲公司。

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 affirm our competitive positioning 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 widely adopted Comate our AI coding assistant for developers. Comate’s capabilities continue to improve, enabling more agentic and efficient development workflow.

在實體人工智慧產業，我們累計與深圳市人工智慧與機器人研究院等20家企業建立合作關係。在自動駕駛領域，我們與黑芝麻科技在AI雲端基礎設施方面建立了合作夥伴關係。此次合作體現了業界對百度AI雲的高度認可，並肯定了我們在中國AI雲市場的競爭地位。基於我們的全端 AI 能力，我們不僅服務企業客戶，還在應用層推動內部生產力和大眾市場 AI 的採用。在內部，我們廣泛採用了開發人員的 AI 編碼助理 Comate。Comate 的功能不斷改進，實現了更具代理性和更有效率的開發工作流程。

In July, AI contributed to generating over 45% of our new code with our developers providing oversight and approval. This has significantly boosted our engineering productivity and meaningfully enhanced our internal R&D efficiency. Externally, Miaoda extends this AI development capabilities to the broader community. Following Miaoda's official launch last quarter, we are now delivering true no-code capabilities that enable users to create applications from mini games to utility tools and websites through simple natural language conversations with AI, no programming expertise required.

7 月份，在我們的開發人員的監督和批准下，人工智慧幫助我們產生了超過 45% 的新程式碼。這大大提高了我們的工程生產力，並顯著提高了我們的內部研發效率。對外，妙達將這種AI開發能力延伸到了更廣泛的社區。繼上個季度妙答正式上線後，我們現在提供真正的無代碼功能，使用戶能夠通過與人工智能進行簡單的自然語言對話來創建從小遊戲到實用工具和網站的應用程序，無需任何編程專業知識。

As of July, users have created around 200,000 applications on Miaoda are 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.

截至 7 月，用戶已在秒達上創建了約 200,000 個應用程序，這些應用程式完全無需編寫任何代碼即可構建。我們致力於實現人工智慧民主化和賦予任何人創新能力的使命，不斷增強無程式碼功能。

Moving to intelligent driving. In Q2, Apollo Go provided over 2.2 million fully driverless to the public, up 148% year over year. As of August, cumulative rights 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 fleet have accumulated over 200 million autonomous kilometers with an outstanding safety record, which is a testament to the ability and safety of our autonomous driving technology.

邁向智能駕駛。第二季度，Apollo Go向大眾提供了超過220萬輛完全無人駕駛汽車，較去年同期成長148%。截至8月份，累計提供給大眾的權利已超過1,400萬，凸顯了我們全無人駕駛營運的規模和成熟度。截至 6 月，Apollo Go 的業務範圍已覆蓋全球 16 個城市。迄今為止，我們的車隊已累積自動駕駛超過2億公里，並擁有出色的安全記錄，證明了我們自動駕駛技術的能力和安全性。

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.

除了與 Uber 和 Lyft 等全球合作夥伴合作外，我們還在國內加速推出輕資產商業模式。本季度，我們與 Helloride 和 T3 Mobility 建立了新的合作夥伴關係，擴大了與領先行動服務供應商的合作網絡。此外，基於上個季度宣布的合作關係，Apollo Go 的全自動汽車租賃服務已在 Car Inc 應用程式上正式上線，為用戶提供訪問我們 Apollo Go 車隊的新入口。這些合作關係使我們能夠快速擴展我們的服務，同時利用合作夥伴的營運專業知識和現有客戶群，為更廣泛的市場滲透創造有效的途徑。

Going forward, we are confident to further accelerate our global expansion and capture significant value across multiple markets worldwide. For our mobile ecosystem, we continue accelerating 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. And 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.

展望未來，我們有信心進一步加速全球擴張，並在全球多個市場中獲得巨大價值。對於我們的行動生態系統，我們在第二季度繼續加速搜尋的人工智慧轉型。在當今競爭激烈的行動互聯網市場中，新產品、新技術層出不窮、發展速度飛快，用戶的需求和行為也在不斷變化，我們必須保持快速迭代。雖然我們的人工智慧轉型正在快速進展，但它仍處於早期階段，在充分發揮其潛力之前還有很大的優化空間。而且我們還沒有到達大規模貨幣化的階段。在此背景下，我們在第二季度開始進行謹慎的小規模貨幣化測試，用戶體驗仍然是我們的首要任務。

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 grow 50% quarter over quarter, contributing 13% of Baidu Core's online marketing revenue. That's up from 9% in Q1. In parallel, digital human gained traction as an innovative monetization avenue for our advertising wins, particularly through AI-powered live streaming.

早期的結果令人滿意，例如，一些以前難以貨幣化的查詢現在顯示出潛力。代理商持續保持強勁表現，推動轉換效率提升，進一步驗證了我們的有效性。第二季度，代理商為廣告主創造的營收季增50%，貢獻了百度核心網路行銷收入的13%。這一數字高於第一季的 9%。同時，數位人類作為我們廣告勝利的創新貨幣化途徑而獲得了關注，特別是透過人工智慧驅動的直播。

We've seen steady growth in digital human adoption over recent quarters. Beyond serving live streaming hosts for merchants, they were being adopted at growing scale in health care legal services, education and automotive sector. 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 human increased by 55% quarter over quarter, contributing 3% of Baidu Core's online marketing revenue.

近幾個季度，我們看到數位人類的採用穩定成長。除了為商家提供直播服務外，它們還在醫療法律服務、教育和汽車領域中得到越來越廣泛的應用。越來越多的廣告商認識到透過即時用戶互動和全天候服務來提升轉換率的價值，從而增加了對數位人類的廣告預算分配。第二季度，數位人創造的營收季增55%，貢獻了百度核心網路行銷收入的3%。

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.

總而言之，展望未來，百度將牢記我們的長期使命，以更大的專注和決心繼續前進，繼續將人工智慧創新轉化為現實價值。

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.

在我們進入問答環節之前，我想花點時間歡迎亨利·何海建先生，他最近加入我們擔任財務長。

With that, let me turn the call over to Henry to go through the financial results.

說完這些，讓我把電話轉給亨利來報告財務結果。

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 (RMB32.7 billion) [corrected by the company after the call], decreasing 4% year over year. Revenue from Baidu Core was RMB26.3 billion, decreasing 2% year over year. Baidu Core's online marketing revenue was RMB16.2 billion, decreasing 15% year over year. Baidu Core's non-online marketing revenue was RMB10 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 RMB6.5 billion, increased by 27% year over year.

謝謝你，羅賓，大家好。很高興加入百度團隊，期待與大家一起工作。現在讓我來詳細介紹一下我們第二季的財務表現。總收入為（327億元）[公司在電話會議後進行了更正]，比去年同期下降4%。「百度核心」營收為263億元，年減2%。百度核心網路行銷收入為人民幣162億元，較去年同期下降15%。百度核心非網路行銷收入為人民幣100億元，較去年成長34%，主要得益於AI雲業務的推動。百度核心非線上行銷收入中，AI雲端收入為人民幣65億元，較去年同期成長27%。

Revenue from iQIYI was RMB6.6 billion, decreasing 11% year over year. Cost of revenue was RMB18.4 billion, increasing 12% year over year, primarily due to an increase in costs related to AI cloud business and content costs. Operating expenses were RMB11.1 billion, decreasing 4% year over year, primarily due to a decrease in personnel-related expenses, partially offset by the increase in channel spending expenses. Baidu Core's operating expenses was RMB9.7 billion, decreasing 5% year over year. Baidu Core's, SG&A expenses were RMB5 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.

愛奇藝營收為66億元人民幣，較去年同期下降11%。營業成本為人民幣184億元，年增12%，主要由於AI雲業務相關成本及內容成本增加。營業費用為人民幣111億元，年減4%，主要由於人員相關費用的減少，但被通路支出費用的增加部分抵銷。百度核心營運費用為97億元，年減5%。百度核心的銷售、一般及行政費用為人民幣50億元，較去年同期成長6%。本季度，銷售、一般及行政費用佔百度核心收入的 19%，去年同期為 18%。

Baidu Core R&D expenses were RMB4.7 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 RMB3.3 billion. Baidu Core's operating income was RMB3.3 billion, and Baidu Core's operating margin was 13% non-GAAP operating income was RMB4.4 billion. Non-GAAP Baidu Core operating income was RMB4.4 billion, and the non-GAAP Baidu Core operating margin was 17%.

百度核心研發費用為47億元，年減14%。本季，研發支出佔百度核心營收的18%，去年同期為20%。營業收入為33億元。「百度核心」營業收入為33億元人民幣，百度核心營業利潤率為13%，非美國通用會計準則營業收入為44億元。非美國通用會計準則「百度核心」營業收入為人民幣44億元，非美國通用會計準則「百度核心」營業利益率為17%。

Total other income net was RMB4.9 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 increase in the net foreign exchange loss arising from exchange rate fluctuation between RMB and the US dollar. Income tax expenses was RMB881 million compared to RMB1.1 billion in the same period of last year. Net income attributable to Baidu was RMB7.3 billion, and the diluted earnings per ADS was RMB20.35. Net income attributed to Baidu Core was RMB7.4 billion, and the net margin for Baidu Core was 28%.

其他淨收入總額為人民幣49億元，年增531%，主要由於公允價值變動收益增加及長期投資收益增加，但被人民幣兌美元匯率波動產生的淨匯兌損失增加部分抵銷。所得稅費用為人民幣8.81億元，去年同期為人民幣11億元。歸屬於百度的淨利為人民幣73億元，每股美國存託憑證攤薄收益為人民幣20.35元。歸屬於「百度核心」的淨利為人民幣74億元，淨利率為28%。

Non-GAAP net income attributed to Baidu was RMB4.8 billion. Non-GAAP diluted earnings per ADS was RMB13.58. Non-GAAP net income attributed to Baidu Core was RMB4.8 billion, and non-GAAP net margin for Baidu Core was 18%. As of June 30, 2025, cash, cash equivalents restricted cash and short-term investments were RMB124.2 billion. And the cash, cash equivalents, research cash and short-term investments, excluding iQIYI were RMB119.9 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 RMB229.7 billion.

非美國通用會計準則下，百度淨利為人民幣48億元。每股美國存託憑證攤薄收益為人民幣13.58元。非美國通用會計準則下，「百度核心」淨利為人民幣48億元，「百度核心」淨利率為18%。截至2025年6月30日，現金、現金等價物、受限現金及短期投資為人民幣1,242億元。不含愛奇藝的現金、現金等價物、研究現金及短期投資為人民幣1199億元。截至2025年6月30日，百度核心持有的現金、現金等價物、短期投資及長期定期存款及持有至到期投資為人民幣2,297億元。

Free cash flow was negative RMB4.7 billion, and free cash flow, excluding iQIYI was negative RMB4.6 billion, primarily due to the increase of 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.

自由現金流為負47億元，剔除愛奇藝的自由現金流為負46億元，主要由於AI業務投入增加。我們將淨現金狀況定義為現金、現金等價物、受限現金、短期投資淨額、持有至到期投資及其他的長期定期存款總額減去貸款總額、可轉換優先票據和應付票據。

As of June 30, 2025, net cash position for Baidu was RMB155.1 billion. Baidu Core had approximately 31,000 employees as of June 30, 2025.

截至2025年6月30日，百度淨現金狀況為人民幣1,551億元。截至 2025 年 6 月 30 日，百度核心約有 31,000 名員工。

With that, operator, let's now open up the call for the questions. Thank you.

接線員，現在讓我們開始提問環節。謝謝。

(Operator Instructions)

（操作員指示）

Alicia Yap, Citigroup.

花旗集團的 Alicia Yap。

Thanks for taking my question And also welcome Henry as the new CFO. I have a question on your AI model. with the rev model iteration, how do you view the current landscape? How do you position ERNIE strategically in the market and alignment with Baidu 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 this year and also the key focus area for this next version.

感謝您回答我的問題，也歡迎亨利擔任新任財務長。我對您的AI模型有一個疑問。隨著rev模型的迭代，您如何看待當前的格局？您如何在市場上對 ERNIE 進行策略性定位並與百度更廣泛的業務策略保持一致？我們也聽說您計劃推出 ERNIE 5.0，管理層能否分享今年下半年 ERNIE 的計劃以及下一個版本的重點關注領域。

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 they're deeper logic and greater creativity now enable them to proposed entirely new solutions to never saying before.

艾莉西亞，這是羅賓。首先讓我介紹一下當前情勢。模型迭代的速度比以往更快。我們幾乎每週都會看到多款新車型上市，而且每一代都比上一代更強大。最近幾個月，我們看到模型變得越來越強大，達到了更深層的邏輯和更強的創造力的階段，使它們能夠提出以前從未說過的全新解決方案。

And I believe this is this kind of innovative ability is getting stronger. Meanwhile, the foundation model landscape is becoming more numbers and clearly not a one-size-fit-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 are in coding and some in multimodality.

而且我相信這種創新能力正在變得越來越強。同時，基本車型種類越來越多，顯然不再是千篇一律的，尤其是在中國，與電動車類似，你總是有很多選擇，不同的車型擅長不同的任務。有些擅長推理，有些擅長編碼，有些擅長多模態。

So we will continue to see a market where multiple models coexist at very reasonable prices. And the value creation will happen at the application level more than at the model level. Against this backdrop, ERNIE positioning is clear. We take an application-driven approach to innovation. In fact, we've taken this approach since the launch of ERNIE -- first launch of ERNIE more than two years ago. Rather than spreading efforts across every possible direction, we stay focused on the strategically important areas that's valuable to us. We think we can deliver meaningful impact and sustain our leadership.

因此，我們將繼續看到多種型號以非常合理的價格共存的市場。價值創造將更多地發生在應用層面，而不是模型層面。在此背景下，ERNIE的定位十分明確。我們採用應用驅動的方法進行創新。事實上，自從 ERNIE 推出以來我們就一直採取這種方法——兩年多前首次推出 ERNIE。我們不會將精力分散到各個可能的方向上，而是專注於對我們有價值的具有戰略意義的領域。我們認為我們可以產生有意義的影響並保持我們的領導地位。

For example, as we advance AI search transformation, we direct our model capabilities towards generating and selecting multimodal search results. And our users love it. Our cloud customers also love it. They're paying for our search API for the purpose of RAG in their Gen AI applications. Another example is our hyper realistic digital human technology, which now matches and even exceeds real human performance in the live streaming e-commerce scenario. Our model is just better at convincing people to buy.

例如，隨著我們推動人工智慧搜尋轉型，我們將模型能力導向生成和選擇多模式搜尋結果。我們的用戶非常喜歡它。我們的雲端客戶也喜歡它。他們為我們的搜尋 API 付費，以便在他們的 Gen AI 應用程式中使用 RAG。再例如我們的超逼真數位人技術，目前在直播電商場景下已經可以匹敵甚至超越真人的表現。我們的模式更能說服人們購買。

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 model. We also keep monitoring industry developments to ensure our technology road map captures the most promising market opportunities. Thank you.

雲端客戶也在為這些功能付費。隨著我們進入下半年及以後，我們將繼續這種加速。我們目前正在開發 ERNIE 的下一個旗艦版本，該版本對關鍵功能進行了重大改進，並希望在準備就緒後推出。同時，我們將繼續對現有模型進行持續的迭代和更新。我們也持續關注產業發展，以確保我們的技術路線圖抓住最有前景的市場機會。謝謝。

Alex Yao, JPMorgan.

摩根大通的 Alex Yao。

And Henry all the best to your new role. So here is my question, how is the AI-powered search upgrade progressing in Q2 and Q3? Could the management share update 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.

祝亨利在新的崗位上一切順利。所以我的問題是，第二季和第三季人工智慧搜尋升級進度如何？管理階層能否分享更新後的指標，說明使用者行為如何隨著新體驗而轉變，我們應該如何從產品格式使用者覆蓋範圍以及商業潛力的角度看待人工智慧搜尋的最終結果。

Alex, thank you so much for your question. This is Julius. I think Q2, we continue to accelerate transformation. And as Robin has just mentioned, Baidu leads globally in using AI to transfer search and we are maybe were the most aggressive in revolutionized search. And we're probably the only company that has completely replaced the traditional links with intelligent AI answers that start with the multimodal content. This creates a more efficient, intuitive user experiences and unlike the current AI answers -- chatbots that remains mostly still as a text-based.

亞歷克斯，非常感謝你的提問。這是朱利葉斯。我認為第二季我們將繼續加速轉型。正如羅賓剛才提到的，百度在使用人工智慧進行搜尋轉移方面處於全球領先地位，而我們也許是搜尋革命中最積極的。我們可能是唯一一家完全用從多模式內容開始的智慧 AI 答案取代傳統連結的公司。這創造了更有效率、更直觀的用戶體驗，與當前的人工智慧答案不同——聊天機器人仍然主要基於文字。

Our focus remains delivering the better user experiences beyond the MAUs and the time spend improvements and the user exposed to AI search now shows higher UV and retention indicating our next generation, search experience is driving the stronger user satisfaction. As for the end game of AI search, I think still an open question, but our path is quite clear. We are fundamentally restructuring search.

我們的重點仍然是提供超越 MAU 和時間花費改進的更好的用戶體驗，而接觸 AI 搜尋的用戶現在顯示出更高的 UV 和保留率，這表明我們的下一代搜尋體驗正在推動更高的用戶滿意度。至於人工智慧搜尋的最終結果，我認為仍然是一個懸而未決的問題，但我們的道路非常清晰。我們正在從根本上重組搜尋。

First, instead of just indexing or link to information, we are delivering the intelligent AI generated answers that began with the relevant multimodal content. Multimodal content now appears more at the very top of AI answers with increasing portion being AI generated. as high-quality AIGC content expands on our platform directly enrich search results and broaden what we can offer to the users.

首先，我們不只是索引或連結到訊息，還提供了從相關的多模式內容開始的智慧 AI 生成的答案。現在，多模式內容更多地出現在 AI 答案的最頂部，其中越來越多的部分是由 AI 產生的。隨著高品質 AIGC 內容在我們的平台上擴展，直接豐富了搜尋結果並擴大了我們可以為用戶提供的內容。

And meanwhile, the AI is also empowering the people across our ecosystem from users, content creators, advertisers and service providers to produce the more and better content. This includes enabling those who were not traditional content creators to participate in making our whole ecosystem more vibrant. And for example, in July, we have launched our Musesteamer our appropriate trade video generation model to facilitate AIGC video creation at scale. And the latest version of Musesteamer with significant update will be launched tomorrow afternoon and to stay tuned, we were moving fast.

同時，人工智慧也賦能於我們生態系統中的人們，包括使用者、內容創作者、廣告商和服務供應商，以創造更多更好的內容。這包括讓那些非傳統內容創作者參與進來，使我們的整個生態系統更加充滿活力。例如，今年 7 月，我們推出了 Musesteamer，這是一個適合貿易影片生成模型，旨在促進 AIGC 的大規模影片創作。具有重大更新的 Musesteamer 最新版本將於明天下午發布，敬請關注，我們的進展非常迅速。

And second, we're also evolving from providinginformation to completing tasks and connecting users with the real world services. For example, through the MCPs, we have connected search to external capabilities like our British Museum and metropolitan MCPs that can provide exhibit explanations right in search. For more complicated needs, our agents help understand the user's intent and connect them with right services providers when the off-line services are required. What we have done today is only the beginning and search will continue advancing in capabilities and reach over time.

其次，我們也正在從提供資訊發展到完成任務並將使用者與現實世界的服務連結起來。例如，透過 MCP，我們將搜尋與外部功能（如大英博物館和大都會 MCP）相連接，這些功能可以在搜尋中直接提供展覽說明。對於更複雜的需求，我們的代理商可以幫助了解用戶的意圖，並在需要離線服務時將他們與合適的服務提供者聯繫起來。我們今天所做的只是一個開始，隨著時間的推移，搜尋的功能和範圍將繼續提升。

In these places, we are also working towards the shift from the general results to personalized -- personalized pages. While AI search understands the individual context, memories and preference could generate the tailor-made responses delivering more intelligent and relevant and personalized answers while better matching users with the tools and services they need. And looking ahead, we will continue to accelerate transformation which, in the short term, will weign on our revenue. But over time, we believe that AI search will unlock exciting commercial possibilities and upside is substantial.

在這些地方，我們也在努力從一般結果轉向個人化——個人化頁面。雖然人工智慧搜尋可以理解個人的背景、記憶和偏好，但可以產生量身定制的回應，提供更聰明、更相關和個性化的答案，同時更好地為用戶匹配他們需要的工具和服務。展望未來，我們將繼續加快轉型，這在短期內將對我們的收入產生影響。但隨著時間的推移，我們相信人工智慧搜尋將釋放令人興奮的商業可能性，並且上升空間巨大。

Gary Yu, Morgan Stanley.

摩根士丹利的 Gary Yu。

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?

我有一個關於 AI 雲端收入的問題。管理階層能否提供當前收入結構和利潤狀況的明細。基於訂閱的收入和基於專案的收入如何分配？您認為它們在未來幾季將如何發展？短期和長期的利潤狀況如何？

Thank you, Gary. This is Dou. In Q2, AI cloud revenue grew 27% year over year to RMB6.5 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 remains the main growth driver. Then 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.

謝謝你，加里。這是竇。第二季度，AI雲營收年增27%至65億元。2025 年上半年，AI 雲端營收年增 34%，高於 2024 年上半年的低十幾個百分點的成長速度。企業雲端的成長速度一直超過我們的整體人工智慧雲端業務，並且仍然是主要的成長動力。在企業雲端中，基於訂閱的收入佔總收入的一半以上，並在第二季度繼續穩定成長。這一成長主要得益於基於訂閱的人工智慧基礎設施的強勁成長勢頭，該基礎設施同比增長超過 50%。

We are seeing a 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 this reflecting our broadening customer base. The other part of the enterprise cloud is project-based revenue. Project-based revenue 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.

我們看到高端和中端客戶都表現出良好的吸引力。尤其是我們的中端客戶，隨著業務的不斷擴張，他們的收入實現了顯著成長，這反映了我們客戶群的不斷擴大。企業雲端的另一部分是基於專案的收入。基於專案的收入通常與客戶部署相關，並且不可避免地會根據合約時間和專案進度而每季波動。我們目前正在仔細審查我們的專案組合，並旨在逐步減少基於專案的收入佔比，以提高收入穩定性。

Turning to Personal Cloud, which is a smaller part of our overall AI cloud business. Over the recent quarters, we've integrated Baidu 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 a broader AI adoption.

談到個人雲，它是我們整體 AI 雲業務的一小部分。最近幾季，我們將百度與文庫整合，並推出了多項新的人工智慧功能。最近，我們免費開放了精選的 AI 功能，以鼓勵更廣泛的採用。雖然這可能涉及一些短期的權衡，但我們相信它有助於加深用戶參與度，並使我們從更廣泛的人工智慧應用中受益。

On profitability, we achieved year over year growth in non-GAAP operating profit and maintained a healthy margin driven by a healthier revenue mix duty towards higher value offerings, while margins can move around from quarter to quarter due to dynamic market environments, we see clear potential for the future improvement over the long run as we scale and optimize our mix.

在獲利能力方面，我們的非公認會計準則營業利潤同比增長，並保持了健康的利潤率，這得益於更健康的收入組合對更高價值產品的重視，儘管由於市場環境的變化，利潤率可能會逐季度波動，但隨著我們擴大和優化組合，我們看到了長期未來改善的明顯潛力。

Lincoln Kong, Goldman Sachs.

林肯孔（Lincoln Kong），高盛。

So my question is about the search. So actually, can you management share more color on the recent AI search monetization testing because the following your earlier comments on AI search opening up new monetization opportunity. Could you elaborate on that? And how are adsformat and business model evolving? What will be the margin look like?

我的問題是關於搜尋的。那麼實際上，您管理層能否分享更多關於最近的 AI 搜尋貨幣化測試的細節，因為根據您先前關於 AI 搜尋開闢新的貨幣化機會的評論。能詳細說明一下嗎？廣告形式和商業模式如何演變？利潤會是什麼樣的？

Thank you, Lincoln, Let me answer your question this is Julius. I mentioned about the monetization opportunities earlier, and let me elaborate over here. And from a product side, while our air transformation already covers a large portion of search results. We are still in the early stage with substantial room for improvement. We aim to further increase the penetration of multimodal content search results and continue building and reaching our AI native ecosystem through MCP agents and on the foundation enable a deeper or broader or higher-quality connections to the real world services.

謝謝你，林肯，讓我來回答你的問題，我是朱利葉斯。我之前提到過貨幣化機會，讓我在這裡詳細說明一下。而從產品方面來說，我們的空中轉化已經涵蓋了很大一部分搜尋結果。我們仍處於早期階段，還有很大的進步空間。我們的目標是進一步提高多模態內容搜尋結果的滲透率，並透過MCP代理繼續建構和涵蓋我們的AI原生生態系統，並在此基礎上實現與現實世界服務更深、更廣或更高品質的連結。

As the transformation advances and the user experience improves monetization opportunities will naturally follow. And also, the AI search brings the native ads that feels intuitive and integrate, enhancing rather than interrupting the user experiences. So the vast majority of keywords that were previously very difficult to monetize now can be monetized under AI search, which should be significantly expand our advertisement inventory over time.

隨著轉型的推進和用戶體驗的改善，貨幣化機會自然會隨之而來。此外，人工智慧搜尋也帶來了直覺、整合的原生廣告，增強了使用者體驗，而不是打斷使用者體驗。因此，以前很難貨幣化的絕大多數關鍵字現在都可以透過人工智慧搜尋實現貨幣化，這將隨著時間的推移大大擴展我們的廣告庫存。

While initially, we will be very conservative with monetization to ensure we get the user experience right and by the long-term upside is much higher. And during our transformation, we are moving from simply generating sales leads to enabling the real world service delivery -- this is a shift made possible by new AI-native commercial products such as agents or digital humans. These innovative products allow us to better capture and serve the user needs through interactive conversations and while connecting the users service providers in verticals like health care, travel and education, where our agents and digital humans have already proven monetization capabilities and over the long term, the ability to fulfill the user needs end to end position us well to drive a gradual transition from CPC to CPS, which offers a much higher ceiling for monetization.

雖然最初我們在貨幣化方面會非常保守，以確保獲得正確的用戶體驗，並且長期的收益會更高。在我們的轉型過程中，我們從簡單地產生銷售線索轉向實現現實世界的服務交付——這一轉變是透過代理或數位人類等新的人工智慧原生商業產品實現的。這些創新產品使我們能夠透過互動式對話更好地捕捉和滿足用戶需求，同時連接醫療保健、旅遊和教育等垂直領域的用戶服務提供商，我們的代理和數位人類已經證明了其貨幣化能力，從長遠來看，端到端滿足用戶需求的能力使我們能夠推動從 CPC 到 CPS 的逐步過渡，這為貨幣化提供了更高的上限。

And in Q2, we have already begun the early testing of the AI search monetization. While it's still in early days, we have seen the more encouraging signals, and we believe this trend will continue over time. that say that we always put user experiences first. So we took a very deliberate approach to AI search monetization and large-scale monetization has not started yet. And at the same time, we have been aggressively accelerating the AI search transformation, including changing those queries with the highest monetization capabilities. So in the near term, we do expect the revenue margin will remain under significant pressure. But long term, we believe this positions us well for stronger growth.

並且在第二季度，我們已經開始了AI搜尋貨幣化的早期測試。雖然還處於早期階段，但我們已經看到了更令人鼓舞的訊號，我們相信這種趨勢將持續下去。這顯示我們始終把使用者體驗放在第一位。因此，我們對 AI 搜尋貨幣化採取了非常謹慎的方法，但大規模貨幣化尚未開始。同時，我們也積極加速人工智慧搜尋轉型，包括改變那些具有最高貨幣化能力的查詢。因此，在短期內，我們確實預期收入利潤率仍將面臨巨大壓力。但從長遠來看，我們相信這將為我們實現更強勁的成長做好準備。

Miranda Zhuang, Bank of America Securities.

美國銀行證券公司的米蘭達·莊 (Miranda Zhuang)。

My question is about cloud and GPU. So how should we assess the sustainability of the AI patent cloud demand especially against the backdrop of a soft economy and intensifying market competition and also 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 as a limiting factor for growth going forward?

我的問題是關於雲端和 GPU 的。那麼，我們應該如何評估人工智慧專利雲端需求的可持續性，尤其是在經濟疲軟、市場競爭加劇的背景下，以及隨著 H20 晶片限制的放寬，管理層是否看到供應方面有任何有意義的改善？您如何看待晶片約束？它會繼續成為未來成長的限制因素嗎？

Miranda, I would do questions. Actually, we were seeing strong and growing demand for AI driven cloud services as the 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 tech, Internet companies, but also from a broader set of the industries like utilities, financial services and the public sector, where interested in AI-driven cloud solution is rising quickly.

米蘭達，我會問問題。事實上，隨著中國雲端市場持續朝向以人工智慧為中心的運算轉變，我們看到對人工智慧驅動的雲端服務的需求強勁且不斷成長。通用人工智慧和基礎模型的應用正在加速，人工智慧已成為越來越多企業的策略重點。據我們觀察，各行各業的需求都在增長，不僅包括科技、互聯網公司等早期採用者，還包括公用事業、金融服務和公共部門等更廣泛的行業，這些行業對人工智慧驅動的雲端解決方案的興趣正在迅速增長。

Meanwhile, technological advances fuel 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 startups and four which are China's top humanoid robot companies. The reason we were able to 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 abilities.

同時，技術進步推動了人工智慧等新興領域的強勁新需求。我們正在有效地抓住新機遇，並與該領域的領先企業合作，其中包括 20 家中國有前途的具身人工智慧新創公司和 4 家中國頂尖的人形機器人公司。我們之所以能夠如此迅速地抓住機遇，是因為我們獨特的競爭定位。我們的獨特之處在於，憑藉全端能力，我們能夠提供極具成本效益的端到端 AI 雲端產品和解決方案。

Taking our AI infra 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 the suitable resources and manage demand fluctuations, delivering better performance at lower costs. As a result, we can provide cost-efficient, reliable and scalable cloud services that makes it really 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 maximize GPU utilization and supports a variety of chips, including domestic chips. This enables us to better serve customers as the supply environment evolves.

以我們的人工智慧基礎設施為例，我們透過業界領先的資源管理能力不斷提高利用率和效率，透過動態分配運算資源，我們可以更好地將工作負載與合適的資源匹配，並管理需求波動，以更低的成本提供更好的效能。因此，我們可以提供經濟高效、可靠且可擴展的雲端服務，使公司能夠以最少的努力輕鬆採用人工智慧並將其擴展到實際的業務影響。關於你提到的晶片的問題。我們的重點仍然是建立一個靈活的AI架構，最大限度地提高GPU利用率並支援各種晶片，包括國產晶片。這使我們能夠隨著供應環境的發展更好地服務客戶。

Looking ahead, we believe that a self-sufficient supply chain together with increasingly mature homegrown software stacks will form a solid foundation for sustainable innovation in China's ecosystem. And clearly, Baidu is well positioned to lead the transition.

展望未來，我們相信，自給自足的供應鏈和日益成熟的本土軟體堆疊將為中國生態系統的可持續創新奠定堅實的基礎。顯然，百度已做好準備引領這項轉變。

Wei Xiong, UBS.

熊偉，瑞銀。

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.

考慮到近期廣告收入面臨的阻力以及對人工智慧的持續投資。我想知道有哪些成本優化和效率提高計劃可以幫助保護利潤率？我們應該如何看待2026年及以後的利潤趨勢。

Thank you. This is Henry. First of all, on the AI investment, we remain committed to investing in AI and have made substantial investments throughout this year particularly in 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.

謝謝。這是亨利。首先，在人工智慧投資方面，我們仍然致力於人工智慧的投資，並在今年全年進行了大量投資，特別是在搜尋的人工智慧轉型方面。正如 Julius 之前提到的，我們的核心遺留產品搜尋正在經歷徹底的轉變。在過去的幾個季度中，我們加大了投資以加速這一轉型，我們認為這對於推動長期價值至關重要。

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 cushion 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.

然而，由於人工智慧搜尋貨幣化仍處於非常早期的階段並且尚未擴大規模，我們的收入和利潤率在短期內面臨相當大的壓力，預計第三季將尤其具有挑戰性。為了緩解短期影響，我們將積極推動內部效率的提升。包括加強不同業務集團間的資源協調，提高整體資源利用效率。

But also on the other hand, while we are remaining committed to long-term AI investment, we'll be very prudent in managing the pace to avoid future deterioration of fluctuation in margins. Looking further ahead, we see potential for margin improvement as our core advertising business recovers and stabilized and our non-advertising business both expand their revenue share and improving their own profitability. We believe our strategic direction and the disciplined execution should support a gradual recovery in profitability over time. on the outlook front, I think before or around end of this year, we expect to have a greater visibility into next year. And at that time, we will have -- we will provide a clear outlook beyond the current quarters for the long term.

但另一方面，雖然我們仍然致力於長期人工智慧投資，但我們會非常謹慎地管理步伐，以避免未來利潤率波動的惡化。展望未來，隨著我們的核心廣告業務復甦和穩定，以及我們的非廣告業務擴大其收入份額並提高自身盈利能力，我們看到利潤率提高的潛力。我們相信，我們的策略方向和嚴格的執行應該能夠支持獲利能力隨著時間的推移而逐步恢復。就前景而言，我認為在今年年底之前或左右，我們預計明年的前景會更加明朗。到那時，我們將提供超越當前季度的長期清晰展望。

In parallel, we are carefully assessing different approaches to present and to unlock the hidden and unstated value of our assets. By doing so, we aim to strengthen our portfolio, create significant long-term value for shareholders, but also support sustainable growth over the long term of business. Thank you.

同時，我們正在仔細評估不同的方法來呈現和釋放我們資產的隱藏和未聲明的價值。透過這樣做，我們的目標是加強我們的投資組合，為股東創造重大的長期價值，同時也支持業務的長期永續成長。謝謝。

Thomas Chong, Jefferies.

湯瑪斯‧張 (Thomas Chong)，傑富瑞 (Jefferies)。

My question is about the global autonomous driving landscape. We see it becomes increasingly competitive -- how does Apollo Go assess its long-term differentiation against peers? And how do the recent Uber and its partnership fits into your global expansion strategy? And what is the road map for achieving sustainable profitability.

我的問題是關於全球自動駕駛格局的。我們看到它的競爭力越來越強——Apollo Go 如何評估其與同行的長期差異化？最近的 Uber 及其合作夥伴關係與您的全球擴張策略有何契合？以及實現永續獲利的路線圖是什麼。

Yeah. I think autonomous driving is one of the most exciting frontiers where AI is transforming the physical world. and 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.

是的。我認為自動駕駛是人工智慧改變物理世界的最令人興奮的前沿領域之一。這一領域的成功需要尖端技術、大量持續的投資和多年的嚴格執行，才能實現規模化的商業運作。作為最早進入該領域的企業之一，我們在所有這些領域都建立了無與倫比的基礎，並成為該領域無可爭議的全球領導者。

With our business model validated, our current focus is on running real-world operations at scale. And we have established global leadership in both left-hand and the right-hand drive robotaxi market. In the left-hand drive market, we were the first to achieve UE breakeven and all of our current operations in China, in Mainland China are fully driverless.

我們的商業模式得到驗證後，我們目前的重點是大規模地開展現實世界的業務。而我們在左側駕駛和右側駕駛的自動駕駛計程車市場都確立了全球領導地位。在左側駕駛市場，我們是第一個實現 UE 損益平衡的公司，我們目前在中國大陸的所有業務都已完全無人駕駛。

Globally, we are among the very few capable of scaled fully driverless and commercial operations in a single complex, large population area. And in the right-hand drive market, we lead the industry globally. In Hong Kong, we've rapidly expanded our open-road 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 environment.

在全球範圍內，我們是極少數能夠在單一複雜、人口密集的地區實現規模化完全無人駕駛和商業運營的國家之一。在右側駕駛市場，我們在全球處於行業領先地位。在香港，我們在獲得監管部門批准後，迅速擴大了開放道路測試，並進入日益複雜的城市場景。我們的技術堆疊和營運專業知識具有跨地域高度可轉移性，使我們能夠有效地適應新市場和監管環境。

We also built a major advantage with RT6, the world's first and only production vehicle designed especially for level 4 autonomous driving from day one. Unlike some retrofitted cars, RT6 is a purpose-built from the ground up is a focus on safety system integration and cost efficiency. It has the lowest unit cost globally for Level 4 and is already running on 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.

我們也憑藉 RT6 建立了巨大的優勢，它是世界上第一輛也是唯一一輛從第一天起就專為 4 級自動駕駛設計的量產車。與一些改裝車不同，RT6 是一款從頭開始專門打造的車型，注重安全系統整合和成本效益。它擁有全球 4 級自動駕駛最低的單位成本，並且已經在我們的商業運營中大規模運行，這為我們更廣泛的推廣提供了巨大優勢。憑藉這一優勢，我們有信心將其擴展到全球更多城市，尤其是那些乘車費用較高的城市。

Here's the picture. We have the lowest cost level four vehicle and most efficient operation. We first achieved UE breakeven in Wuhan where taxi fares over 30% cheaper than the Tier 1 cities in China and far below many overseas markets. Yet we still managed to prove 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 fare several times higher. Our huge cost advantage can deliver much stronger unit economics in most major cities worldwide.

這是圖片。我們擁有成本最低的四級車輛和最高效的營運。我們首先在武漢實現了歐盟收支平衡，那裡的計程車費用比中國一線城市便宜 30% 以上，遠低於許多海外市場。但我們仍然設法在那裡證明了商業模式。這種卓越的營運和成本效率在全球範圍內是無與倫比的。對我們來說，拓展海外市場意味著從低價市場進入高價市場，而且價格通常會高出好幾倍。我們龐大的成本優勢可以在全球大多數主要城市帶來更強勁的單位經濟效益。

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 this world's leading mobility platforms will help us enter and scale more quickly into global markets like Middle East, like Asia and Europe. Looking ahead, we anticipate accelerating growth in ride volumes with our global operational fleet size multiply. 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.

為了加速我們的全球擴張，我們也積極主動地建立全球合作夥伴關係。正如我們在準備好的演講中提到的那樣，我們在 7 月宣布與 Uber 建立合作夥伴關係，並在 8 月宣布與 Lyft 建立合作夥伴關係。我們與世界領先的行動平台的合作將幫助我們更快地進入和擴展中東、亞洲和歐洲等全球市場。展望未來，我們預期隨著全球營運車隊規模的擴大，乘車量也將加速成長。憑藉這一勢頭，我們相信 Apollo Go 將繼續引領市場並在全球自動駕駛領域保持領先地位。謝謝。

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

今天的會議就到此結束了。感謝您的參與。您現在可以斷開連線。