百度 (BIDU) 2023 Q4 法說會逐字稿

Hello, and thank you for standing by for Baidu's Fourth Quarter and Fiscal Year 2023 Earnings Conference Call. (Operator Instructions) Today's conference is being recorded. If you have any objections, you may disconnect at this time.

您好，感謝您出席百度第四季及2023財年獲利電話會議。 （操作員指示）今天的會議正在錄音。如果您有任何異議，您可以此時斷開連接。

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

現在我想把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 Fourth Quarter and Fiscal Year 2023 Earnings Conference Call. Baidu's earnings release was distributed earlier today, and you can find a copy on our website as well as on newswire services. On the dcall today, we have Robin Li, our Co-Founder and our CEO; Rong Luo, our CFO; and Dou Shen, our EVP in charge of Baidu AI Cloud Group ACG.

大家好，歡迎參加百度第四季及2023財年獲利電話會議。百度的財報已於今天早些時候發布，您可以在我們的網站以及新聞專線服務上找到副本。今天的電話會議上有我們的共同創辦人兼執行長李彥宏；羅蓉，我們的財務長；竇深，我們的執行副總裁，負責百度AI雲集團ACG。

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 provision of the U.S. Private 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.

在我們準備好的發言之後，我們將舉行問答環節。請注意，今天的討論將包含根據1995 年美國私人證券訴訟改革法案的安全港條款做出的前瞻性陳述。前瞻性陳述受到風險和不確定性的影響，可能導致實際結果與我們當前的結果存在重大差異。期望。

For detailed discussions of these risks and uncertainties, please refer to our latest annual report and other documents filed 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.

有關這些風險和不確定性的詳細討論，請參閱我們向美國證券交易委員會和香港證券交易所提交的最新年度報告和其他文件。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 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.

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 GAAP 財務指標的討論。我們的新聞稿包含未經審計的非 GAAP 衡量標準與未經審計的最直接可比較的 GAAP 衡量標準的調整表，可在我們的 IR 網站 ir.baidu.com 上取得。

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.

提醒一下，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IR網站上進行。我現在將把電話轉給我們的執行長羅賓。

Lin. We concluded 2023 with solid quarter. Baidu Core's total revenue for the fiscal year increased by 8% year-over-year, and the non-GAAP operating margin expanded from 22% to 24%. This improvement highlighted the resilience of our core business, which serves as a strong foundation for our ventures in ERNIE and ERNIE bot.

林.我們以穩健的季度業績結束了 2023 年。百度核心本財年總營收年增8%，非美國通用會計準則營業利益率從22%擴大至24%。這項改進凸顯了我們核心業務的彈性，為我們在 ERNIE 和 ERNIE 機器人領域的業務奠定了堅實的基礎。

2023 marked a year of Gen AI and foundation models, a massive technology shift that will reengineer business process and bring about a real renaissance in every sector of the economy. Baidu is well prepared to benefit greatly from this groundbreaking economic revolution. We progressed from talking about the opportunities of Gen AI and foundation models to activity opine ERNIE and ERNIE bot at scale. As the front runner in AI, Baidu probably became the first public company globally to launch a GPT model with our EB 4.0 standing call as the most powerful foundation model in China. ERNIE continues to gain market recognition as evidenced by ERNIE API cost from multiple well-known companies.

2023 年是新一代人工智慧和基礎模型的一年，這是一場大規模的技術變革，將重新設計業務流程，並為每個經濟部門帶來真正的復興。百度已做好充分準備，從這場突破性的經濟革命中獲益匪淺。我們從討論 Gen AI 和基礎模型的機遇，發展到大規模活動觀點 ERNIE 和 ERNIE 機器人。身為人工智慧領域的領跑者，百度可能成為全球第一家推出 GPT 模型的上市公司，我們的 EB 4.0 長期呼籲成為中國最強大的基礎模型。 ERNIE 持續獲得市場認可，多家知名公司的 ERNIE API 成本證明了這一點。

Notably, Samsung uses ERNIE API on its Galaxy S24 5G series. Owner uses ERNIE API it's [MAGIC] 8.0 and Autohome using ERNIE API to power its multiple AIGC apps. The partnerships further solidify our leadership in Gen AI. Furthermore, we continued improving the efficiency of ERNIE. For example, the inference cost of EB 3.5 is only about 1% of the March 2023 version. With lower inference costs, ERNIE will become increasingly accessible to users and enterprises. We are able to do that primarily because of our unique 4-layer AI architecture and our strong ability in end-to-end optimization.

值得注意的是，三星在其 Galaxy S24 5G 系列上使用了 ERNIE API。擁有者使用 ERNIE API（[MAGIC] 8.0），而 Autohome 使用 ERNIE API 為其多個 AIGC 應用程式提供支援。這些合作關係進一步鞏固了我們在 Gen AI 領域的領導地位。此外，我們持續提高 ERNIE 的效率。例如，EB 3.5 的推理成本僅為 2023 年 3 月版本的 1% 左右。隨著推理成本的降低，ERNIE 將越來越容易被使用者和企業所使用。我們能夠做到這一點，主要是因為我們獨特的四層人工智慧架構和強大的端到端優化能力。

Additionally, we are offering LLMs in smaller sizes. This small model can balance between performance and efficiency, better serving various customer needs. Since Q2 2023, we have actively utilized ERNIE to revolutionize our products and services, creating AI native experiences. We believe real applications are essential to unleashing the full business potential of ERNIE and ERNIE bot. Recently, we began to generate incremental revenues from ERNIE and ERNIE bot. In the fourth quarter, we earned several hundred million RMB primarily from ad technology improvement and helping enterprises build their own models. I will provide a more detailed explanation in the business review section.

此外，我們也提供較小規模的法學碩士。這種小型模型可以在性能和效率之間取得平衡，以更好地滿足各種客戶需求。自 2023 年第二季以來，我們積極利用 ERNIE 徹底改變我們的產品和服務，創造 AI 原生體驗。我們相信，真正的應用程式對於釋放 ERNIE 和 ERNIE 機器人的全部業務潛力至關重要。最近，我們開始透過 ERNIE 和 ERNIE 機器人產生增量收入。第四季我們的收入有數億元，主要來自於廣告科技的改進和幫助企業建立自己的模型。我將在業務回顧部分提供更詳細的解釋。

Looking into 2024, we believe this incremental revenue were multiplied to several billion RMB, primarily from advertising and AI Cloud businesses. While we are beginning to commercialize Gen AI and foundation models, we see enormous monetization potential in this groundbreaking technology. We envision ERNIE as the future foundation system serving as the foundation for millions of AI native applications developed by third party and Baidu. This paradigm will enable us to create an ecosystem around ERNIE, which opens up various revenue sources.

展望2024年，我們認為增量營收將增加至數十億元人民幣，主要來自廣告和人工智慧雲端業務。當我們開始將 Gen AI 和基礎模型商業化時，我們看到了這項突破性技術的巨大獲利潛力。我們設想 ERNIE 作為未來的基礎系統，為第三方和百度開發的數百萬個 AI 原生應用程式奠定基礎。這種範例將使我們能夠圍繞 ERNIE 創建一個生態系統，從而開闢各種收入來源。

Now the key highlights in Baidu's AI native application. Equipped with an AI copilot, Baidu Wenku has become a platform for users to create content in a wide range of formats, helping them express their ideas. In addition to summarizing creating and expanding content, users particularly appreciate Baidu Wenku's features for assisting them in automatically turning their inspiration into PowerPoint. We have been consistently improving and enriching its AI features. For example, we recently introduced a new 1 such as Mind-Maps for organizing information. We are reconstructing Baidu Search using ERNIE. Last quarter, we talked about how we used ERNIE to generate such results, improving the one-shop experience. In Q4, Baidu Search introduced new feed like information alongside the generated search results at scale to offer users useful and relevant content to explore. In Q4, we also began facilitating certain search queries with multi-round conversations to dive deeper into understanding users' intention. Overall, Gen AI-enabled search complements traditional search, expanding the TAM of Baidu Search by serving our wider range of information need and answering content creation related questions. We are actively encouraging SMEs in service industries to build AI chatbot as new lending pages called Baidu Search. AI chatbots enable them to better serve potential buyers directed to them by us, driving transactions on our platform. At the same time, our AI chatbot can help merchants increase productivity. Currently, about 4,000 merchants are using our AI chatbot, particularly in health care, education, travel, legal, B2B and auto where users often interact with merchants to learn about their offerings before making purchasing decisions.

現在重點看一下百度AI原生應用程式。配備人工智慧副駕駛的百度文庫已成為用戶創建多種格式內容的平台，幫助他們表達自己的想法。除了總結創作和擴充內容之外，使用者還特別欣賞百度文庫的功能，幫助他們將靈感自動轉化為PowerPoint。我們一直在不斷改進和豐富其人工智慧功能。例如，我們最近推出了一種新的1，例如用於組織資訊的心智圖。我們正在使用ERNIE重構百度搜尋。上個季度，我們討論如何使用 ERNIE 產生這樣的結果，改善一站式體驗。在第四季度，百度搜尋在大規模產生的搜尋結果旁邊引入了新的提要訊息，為用戶提供有用且相關的內容供探索。在第四季度，我們也開始透過多輪對話來促進某些搜尋查詢，以更深入地了解用戶的意圖。總體而言，新一代人工智慧搜尋是對傳統搜尋的補充，透過滿足我們更廣泛的資訊需求並回答內容創建相關問題，擴展了百度搜尋的 TAM。我們積極鼓勵服務業的中小企業建立人工智慧聊天機器人，作為新的借貸頁面，稱為百度搜尋。人工智慧聊天機器人使他們能夠更好地為我們定向的潛在買家提供服務，從而推動我們平台上的交易。同時，我們的人工智慧聊天機器人可以幫助商家提高生產力。目前，約有 4,000 家商家正在使用我們的 AI 聊天機器人，特別是在醫療保健、教育、旅遊、法律、B2B 和汽車領域，用戶經常與商家互動，在做出購買決定之前了解他們的產品。

We believe the Gen AI-enabled search will help increase user intention on Baidu reinforcing our position as the primary entry point for users seeking information and services. We are also expanding the reach of ERNIE by enabling enterprises to easily divest AI native application on ERNIE. In December, we introduced App Builder and comprehensive set of tools on our public cloud to support enterprises to swiftly view AI-enabling applications from the ground up. These tools enable enterprises to incorporate capabilities such as organizing online messages for prioritization, creating draft, summarizing meeting notes and facilitating Gen AI-enabled data analysis.

我們相信，基於人工智慧的搜尋將有助於提高用戶對百度的使用意向，鞏固我們作為用戶尋求資訊和服務的主要入口點的地位。我們也透過讓企業能夠輕鬆剝離 ERNIE 上的 AI 原生應用程式來擴大 ERNIE 的覆蓋範圍。 12 月，我們在公有雲上推出了 App Builder 和一整套工具，以支援企業從頭開始快速查看支援 AI 的應用程式。這些工具使企業能夠整合多種功能，例如組織線上訊息以確定優先順序、建立草稿、總結會議記錄以及促進 Gen AI 資料分析。

Additionally, we have included several ready-made templates such as AI agent to enable enterprises to promptly create applications for validating their ideas. Such progress is in large part based on our own pioneering experience in developing AI native applications. In addition to the tools for app divestment, enterprises partnered with us because we have the most powerful and most efficient foundation models and the most cost-effective cloud platform for ERNIE apps. In December, about 26,000 enterprises are actively using ERNIE through API on a monthly basis, increasing 150% quarter-over-quarter. And ERNIE is now handling more than 50 million queries every day. That's up 190% quarter-over-quarter with a significant rise in third-party [comps].

此外，我們還提供了一些現成的模板，例如AI代理，使企業能夠快速創建應用程式來驗證他們的想法。這樣的進步很大程度上是基於我們自己在開發AI原生應用方面的開創性經驗。除了應用撤資工具之外，企業與我們合作也因為我們擁有最強大、最高效的基礎模型以及最具性價比的ERNIE應用雲端平台。 12月，每月約有26,000家企業透過API積極使用ERNIE，較上季成長150%。 ERNIE 現在每天處理超過 5000 萬個查詢。隨著第三方 [comps] 的大幅增長，該數字環比增長 190%。

As a number of AI native applications hosted on our public cloud continue to rise. We are poised to accelerate the enhancement of our model performance by incorporating feedback from our users and customers. This will further widen the gap between ERNIE and our domestic peers. Moreover, as more and more AI native applications on ERNIE become popular, ERNIE will likewise be successful and support a robust ecosystem around it, steerings multiyear growth forward.

隨著我們公有雲上託管的人工智慧原生應用程式的數量不斷增加。我們準備透過整合使用者和客戶的回饋來加速提高模型效能。這將進一步拉大ERNIE與國內同業的差距。此外，隨著 ERNIE 上越來越多的人工智慧原生應用程式變得流行，ERNIE 同樣會取得成功，並支援圍繞它的強大生態系統，引導多年的成長。

In conclusion, we find ourselves amidst a tremendous opportunity in Gen AI and foundation model. With the ERNIE and ERNIE bot, we have started generating incremental revenues. In 2024, we expect AI revenues contribution to become more meaningful, while our core business will remain resilient. Moreover, we are preparing to serve the next wave in the development of ERNIE. In the future, we believe that there will be millions of AI-native applications on ERNIE with a vast majority of them developed by our cloud customers. The expanding ERNIE ecosystem will then unlock numerous monetization potential for Baidu.

總之，我們發現自己處於 Gen AI 和基礎模型領域的巨大機會之中。借助 ERNIE 和 ERNIE 機器人，我們已經開始產生增量收入。到 2024 年，我們預計人工智慧收入貢獻將變得更有意義，而我們的核心業務將保持彈性。此外，我們正準備服務ERNIE的下一波發展。未來，我們相信ERNIE上將有數以百萬計的AI原生應用程序，其中絕大多數是由我們的雲端客戶開發的。不斷擴大的 ERNIE 生態系統將為百度釋放巨大的獲利潛力。

Now let me recap the key highlights for each business for the fourth quarter of 2023. Mobile ecosystem exhibited a solid performance across revenue, margin and cash flow. In the fourth quarter, Baidu Core's online marketing revenue increased by 6% year-over-year, driven by verticals in travel, health care, in services and others. In Q4, we generated several hundred million RMB incremental ad revenue due to improvements in ad tech. We continue to use ERNIE to enhance our monetization system, including targeting capability and bidding systems in the quarter.

現在讓我回顧一下 2023 年第四季每項業務的主要亮點。行動生態系統在收入、利潤率和現金流方面表現出穩健的表現。第四季度，在旅遊、醫療、服務等垂直產業的推動下，百度核心網路行銷收入較去年同期成長6%。第四季度，由於廣告技術的改進，我們實現了數億元人民幣的廣告收入增量。我們繼續使用 ERNIE 來增強我們的貨幣化系統，包括本季的定位能力和競價系統。

Starting from January, our monetization system has been able to generate real-time text-based ads for search queries demonstrating significant technology improvements in both targeting and ad creation. As of today, our new marketing platform has attracted about 10,000 advertisers. An advertiser in the medical aesthetics industry began to adopt our new marketing platform in Q4. With the AI copilot the advertiser can articulate its requirement comprehensively through natural language and multi-round conversations for further clarification and explanation. The conversational experience has assisted in building optimized search and feed campaigns by generating relevant ad content. Our platform has also helped them reach highly targeted audiences while dynamically allocating budget to drive conversion. The advertiser achieved an increase of 22% in conversion rate and a reduction of 5% in cost for sales lead acquisition after using this enhanced platform and capabilities.

從一月份開始，我們的獲利系統已經能夠為搜尋查詢產生基於文字的即時廣告，這在定位和廣告創建方面展示了重大的技術改進。截至目前，我們的新行銷平台已吸引了約 10,000 家廣告商。醫療美容行業的一家廣告商在第四季度開始採用我們的新行銷平台。透過AI副駕駛，廣告主可以透過自然語言和多輪對話全面表達自己的需求，並得到進一步的澄清和解釋。對話體驗透過產生相關廣告內容來幫助建立優化的搜尋和提要活動。我們的平台還幫助他們吸引了高度針對性的受眾，同時動態分配預算以推動轉換。使用此增強的平台和功能後，廣告客戶的轉換率提高了 22%，銷售線索獲取成本降低了 5%。

Currently, only a small portion of our entire advertiser base has adopted this new marketing platform, which means there is a significant opportunity for future growth. All these initiatives have helped advertisers improve their conversion leading to an increase in their ad budget on our platform in the quarter. We expect continued growth in ad revenue from Gen AI and foundation models in 2024 and beyond. While we enhance our ad technologies, we also introduced AI chatbot for brand and innovative ad product building on top of ERNIE bot in Q4. AI chatbot has further enriched our ad product portfolio. It can enhance user engagement and customer service while also capturing customer attention and driving customer demand. Since last October, China Feihe as local infant formula company has adopted AI chatbot to promote its brand. The AI chatbot has enabled Feihe to have multi-round interactions with our customers, increased brand recognition and gain valuable insights into its potential consumers. This profound insights have also helped Feihe understand customers' use of its brand and products, leading to an enhanced marketing strategy. AI chatbot for brands has one significant interest from brand advertisers, and we expect more and more businesses to embrace the AI chatbot in the future. As I previously mentioned, we're using ERNIE to build our apps. With continuous enhancement of our AI native product offerings, we believe more and more users will come to Baidu platform. This, in turn, will assist us in gaining more market share in both user engagement and online advertising revenues.

目前，我們整個廣告客戶群中只有一小部分採用了這個新的行銷平台，這意味著未來存在巨大的成長機會。所有這些舉措都幫助廣告商提高了轉換率，從而增加了他們本季在我們平台上的廣告預算。我們預計 2024 年及以後 Gen AI 和基礎模型的廣告收入將持續成長。在我們增強廣告技術的同時，我們也在第四季度推出了基於 ERNIE 機器人的品牌人工智慧聊天機器人和創新廣告產品。 AI聊天機器人進一步豐富了我們的廣告產品組合。它可以增強用戶參與度和客戶服務，同時吸引客戶注意力並推動客戶需求。自去年10月起，中國飛鶴作為本土嬰幼兒配方奶粉企業，開始採用人工智慧聊天機器人來推廣其品牌。人工智慧聊天機器人使飛鶴能夠與客戶進行多輪互動，提高品牌認知度並獲得對潛在消費者的寶貴見解。這種深刻的洞察也幫助飛鶴了解客戶對其品牌和產品的使用情況，從而製定更好的行銷策略。品牌人工智慧聊天機器人引起了品牌廣告商的極大興趣，我們預計未來會有越來越多的企業接受人工智慧聊天機器人。正如我之前提到的，我們使用 ERNIE 來建立我們的應用程式。隨著我們AI原生產品的不斷增強，我們相信會有越來越多的使用者來到百度平台。反過來，這將幫助我們在用戶參與度和線上廣告收入方面獲得更多市場份額。

Looking into 2024, Mobile ecosystem should continue to generate steady profits and cash flow. AI Cloud revenue grew by 11% year-over-year to RMB 5.7 billion and continue to improve profitability in the fourth quarter. Revenue from Gen AI and foundation model represents 4.8% of our AI Cloud revenue in Q4. The increasing demand for model building played a significant role in this accelerated revenue growth, along with increasing distributions from inference. We have seen a growing number of enterprises, in particular, tech companies turning to our public cloud to build their models.

展望2024年，行動生態系統將持續產生穩定的利潤和現金流。 AI雲第四季營收年增11%至57億元人民幣，獲利能力持續提升。 Gen AI 和基礎模型的營收佔第四季 AI 雲端營收的 4.8%。對模型建構的需求不斷增長，以及推理分配的增加，在收入加速成長中發揮了重要作用。我們看到越來越多的企業，特別是科技公司轉向我們的公有雲來建立他們的模型。

Additionally, the AI cloud revenue generated by Baidu Core, other business groups, such as the Mobile Ecosystem Group and the Intelligent Driving Group was about RMB 2.7 billion in Q4. Within the Q4 internal cloud revenue, Gen AI and foundation model accounted for about 14%. On a combined basis, the total internal and external AI Cloud revenue was RMB 8.4 billion in Q4, with Gen AI and foundation model contributing around RMB 656 million.

此外，百度核心、行動生態事業群、智慧駕駛事業群等其他事業群在第四季產生的AI雲收入約為27億元。在Q4內部雲端收入中，Gen AI和基礎模型約佔14%。綜合來看，第四季內外AI雲總收入為84億元人民幣，其中Gen AI和基礎模型貢獻約6.56億元。

Gen AI and LLM have become pivotal considerations for many enterprises driving a shift in the cloud industry from general purpose computing to AI computing. This evolution is reshaping the competitive dynamics within the cloud industry strengthening our lead in AI and expanding our total addressable market. Enterprises choose us, thanks to our position of the most powerful and cost-effective AI infrastructure for both model training and inference in China. Thanks to our unique 4-layer AI infrastructure to drive consistent efficiency gains and years of experience in ERNIE. Last quarter, we explained that 98% of LLM training time on our AI infrastructure was valid. Moreover, our GPU networking is running at a 95% utilization for training LLMs. Both of these metrics have set industry benchmarks.

Gen AI和LLM已成為許多企業推動雲端產業從通用運算轉變為人工智慧運算的關鍵考量。這種演變正在重塑雲端產業內的競爭動態，加強我們在人工智慧領域的領先地位，並擴大我們的整體潛在市場。企業選擇我們，是因為我們擁有中國最強大、最具成本效益的模型訓練和推理人工智慧基礎設施。由於我們獨特的 4 層人工智慧基礎設施來推動持續的效率提升以及 ERNIE 的多年經驗。上個季度，我們解釋說，我們的 AI 基礎設施上 98% 的法學碩士培訓時間都是有效的。此外，我們的 GPU 網路在訓練 LLM 時的利用率為 95%。這兩個指標都設定了產業基準。

Within our MaaS, we offer model builder and app builder, which are 2 set of tools that help enterprises effortlessly build models and develop apps. As of now, enterprises have built about 10,000 models on our MaaS. Since its inception, App Builder has facilitated the creation of thousands of AI native apps. As more and more applications are being built on our MaaS, we will have greater revenue potential going forward.

在我們的 MaaS 中，我們提供模型建構器和應用程式建構器，這是兩套工具，可幫助企業輕鬆建立模型和開發應用程式。截至目前，企業已經在我們的 MaaS 上建立了約 10,000 個模型。自推出以來，App Builder 已協助創建了數以千計的 AI 原生應用程式。隨著越來越多的應用程式建構在我們的 MaaS 上，我們未來將擁有更大的收入潛力。

Looking into 2024, AI Cloud should maintain strong growth in revenue and generate profit as a non-GAAP operating level. Our intelligent driving business continued to focus on achieving newly breakeven for Apollo Go. In Wuhan, Apollo Go's largest operation, about 45% of our orders were provided by fully driverless vehicles in Q4. This metric surpassed 50% in January. The increase is because we intensified operations during peak hours in areas with complex traffic conditions and further expanding our operating area in the past few months. This development resulted from our ongoing efforts to improve technology through safety -- through safely operating Apollo Go on public routes. In China, Apollo Go provided about 839,000 rides in the public in Q4, marking up 49% year-over-year increase. In early January, the cumulative rise offered by Apollo Go exceeded 5 million. The substantial data collected from operations will further help us enhance the efficiency of safe operations.

展望2024年，AI Cloud應維持營收強勁成長，並以非GAAP營運水準產生利潤。我們的智慧駕駛業務持續專注於實現 Apollo Go 的新損益平衡。在 Apollo Go 最大的業務武漢，第四季度我們約 45% 的訂單是由完全無人駕駛車輛提供的。該指標 1 月超過了 50%。增加的原因是我們在過去幾個月加強了交通狀況複雜地區的高峰時段運營，並進一步擴大了運營區域。這一發展源於我們不斷努力透過安全來改進技術——透過在公共路線上安全運行 Apollo Go。在中國，Apollo Go第四季向民眾提供約83.9萬次乘車服務，較去年同期成長49%。 1月初，Apollo Go累計漲幅突破500萬。營運中收集到的大量數據將進一步幫助我們提高安全營運效率。

Looking into 2024, we will remain focused on getting closer to Apollo Go's UE break-even target and managing our costs and expenses to reduce losses in intelligent driving. Upon reaching UE breakeven, we plan to swiftly replicate our successful operations in Wuhan to other regions.

展望2024年，我們將繼續專注於接近Apollo Go的UE損益平衡目標，並管理我們的成本和費用以減少智慧駕駛的損失。在達到UE損益平衡後，我們計劃迅速將我們在武漢的成功業務複製到其他地區。

In summary, we are facing tremendous opportunities in Gen AI and foundation models. We will continue to invest in these opportunities. And at the same time, we will strive to optimize our cost and expense structure for each business line to improve operational efficiency.

綜上所述，我們在Gen AI和基礎模型方面面臨著巨大的機會。我們將繼續投資這些機會。同時，我們將努力優化各業務線的成本費用結構，提高營運效率。

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

接下來，讓我將電話轉給榮，以查看財務業績。

Thank you, Robin. Now let me walk through the details of our fourth quarter and full year 2023 financial results. We closed 2023 with solid financial results. Total revenues in the fourth quarter was RMB 35 billion, increasing 6% year-over-year. Total revenues for the full year 2023 were RMB 134.6 billion, increasing 9% year-over-year. Baidu Core's Q4 revenue was RMB 27.5 billion, increasing 7% year-over-year. In 2023, Baidu Core generated RMB 103.5 billion in revenue, increasing 8% year-over-year. Baidu Core's online marketing revenue increased 6% year-over-year to RMB 19.2 billion in Q4, accounting for [17%] of Baidu Core's total loan. Baidu Core online marketing revenue was up 8% year-over-year in 2023. Baidu Core's non-online marketing revenue was RMB 8.3 billion, up 9% year-over-year.

謝謝你，羅賓。現在讓我詳細介紹一下我們第四季和 2023 年全年財務表現。我們以穩健的財務表現結束了 2023 年。第四季總收入為人民幣350億元，較去年同期成長6%。 2023年全年總收入為人民幣1,346億元，較去年同期成長9%。百度核心第四季營收為人民幣275億元，年增7%。 2023年，百度核心營收1,035億元，年增8%。第四季百度核心網路行銷營收年增6%至192億元人民幣，佔百度核心貸款總額的[17%]。 2023年，百度核心網路行銷收入較去年同期成長8%。百度核心非網路行銷收入為人民幣83億元，較去年同期成長9%。

For the full year 2023, our online marketing business increased 9% year-over-year. The increase in our online marketing business was mainly driven by the AI Cloud business. Revenue from iQIYI was RMB 7.7 billion in Q4, increasing 2% year-over-year. Revenue from iQIYI was RMB 31.9 billion in 2023, increasing 10% year-over-year. Cost of revenue was RMB 17.4 billion in Q4, increasing 3% year-over-year, primarily due to an increase in costs related to AI cloud business, partially offset by a decrease in content costs. Cost of revenue was RMB 65 billion in 2023, increasing 2% year-over-year primarily due to an increase in traffic acquisition costs, partially offset by a decrease in the content costs and the costs related to AI Cloud business.

2023年全年，我們的網路行銷業務年增9%。我們的線上行銷業務的成長主要由AI雲業務推動。愛奇藝第四季營收為77億元人民幣，較去年同期成長2%。 2023年愛奇藝收入為人民幣319億元，較去年成長10%。第四季營收成本為人民幣174億元，年增3%，主要是由於AI雲業務相關成本增加，但部分被內容成本下降所抵銷。 2023年收入成本為人民幣650億元，年增2%，主要是由於流量獲取成本增加，部分被內容成本和AI雲業務相關成本的下降所抵銷。

Operating expenses were RMB 12.1 billion in Q4, increasing 5% year-over-year, primarily due to an increase in server depreciation expenses and the server custody fees which support an AI research and development improves and channel spending and promotional marketing expenses. Operating expenses were RMB 47.7 billion in 2023, increasing 9% year-over-year, primarily due to an increase in channel spending and promotional marketing expenses and server depreciation expenses and sever custody fees, which support AI research and development inputs.

第四季營運費用為人民幣121億元，年增5%，主要是由於伺服器折舊費用和支援人工智慧研發改進的伺服器託管費用以及通路支出和促銷行銷費用的增加。 2023年營業費用為人民幣477億元，年增9%，主要是由於通路支出和促銷行銷費用以及伺服器折舊費用和伺服器託管費的增加，支持了人工智慧研發投入。

Operating income was RMB 5.4 billion in Q4. Baidu Core's operating income was RMB 4.7 billion, and Baidu Core's operating margin was 17%, 1-7, in Q4. Operating income was RMB 21.9 billion in 2023. Baidu Core's operating income was RMB 18.8 billion, and Baidu Core's operating margin was 18%, 1-8, in 2023. Non-GAAP operating income was RMB 7.1 billion in Q4. Non-GAAP Baidu Core operating income was RMB 6.2 billion, and non-GAAP Baidu Core operating margin was 23% in Q4.

第四季營業收入為54億元。百度核心第四季營業收入為人民幣47億元，營業利益率為17%，1-7。 2023 年營業收入為 219 億元。百度核心營業收入為 188 億元人民幣，2023 年百度核心營業利潤率為 18%，1-8。第四季非 GAAP 營業收入為 71 億元。第四季非 GAAP 百度核心營業收入為 62 億元人民幣，非 GAAP 百度核心營業利潤率為 23%。

Non-GAAP operating income was RMB 28.4 billion in 2023. Non-GAAP Baidu Core operating income was RMB 24.7 billion and non-GAAP Baidu Core operating margin was 24% in 2023. In Q4, total other loss net was RMB 2.5 billion compared to total other income net of RMB 1.8 billion for the same period last year mainly due to a pickup of losses from equity method investments as a result of a modification of the certain terms of underlying preferred shares. Income tax benefit is RMB 96 million.

2023 年非GAAP 營業收入為284 億元。2023 年非GAAP 百度核心營業收入為247 億元人民幣，2023 年非GAAP 百度核心營業利潤率為24%。第四季度，其他淨虧損總額為25 億元人民幣，而去年同期上年同期其他收益總額淨額為人民幣18億元，主要是由於優先股相關條款修改導致權益法投資虧損回升。所得稅優惠9600萬元。

In 2023, total other income net was RMB 3.3 billion compared to total other loss net of RMB 5.8 billion last year mainly due to a fair value gain of RMB 198 million from our long-term investments this year compared to a fair value loss of RMB 3.9 billion last year and a decrease of RMB 2.2 billion in impairment of long-term investments.

2023 年，其他淨收入總額為人民幣33 億元，而去年其他淨損失總額為人民幣58 億元，主要是由於今年我們的長期投資公允價值收益為人民幣1.98 億元，而公允價值損失為人民幣1.98億元。上年減少長期投資減損39億元，減少22億元。

Income tax expenses was RMB 3.6 billion. In Q4, net income attributable to Baidu was RMB 2.6 billion, and diluted earnings per ADS was RMB 6.77. Net income attributable to Baidu Core was RMB 2.4 billion, and net margin for Baidu Core was 9%. Non-GAAP net income attributable to Baidu was RMB 7.8 billion, non-GAAP diluted earnings per ADS was RMB 21.86. Non-GAAP net income attributable to Baidu Core was RMB 7.5 billion, and non-GAAP net margin for Baidu Core was 27%.

所得稅費用36億元。第四季度，歸屬於百度的淨利為人民幣26億元，每股ADS攤薄收益為人民幣6.77元。歸屬於百度核心的淨利為人民幣24億元，百度核心淨利率為9%。非 GAAP 歸屬於百度的淨利為人民幣 78 億元，非 GAAP 攤薄後每股美國存託憑證收益為 21.86 元。非美國通用會計準則歸屬於百度核心的淨利為人民幣75億元，非美國通用會計準則淨利率為27%。

In 2023, net income attributable to Baidu was RMB 20.3 billion and diluted earnings per ADS were RMB 55.08. Net income attributable to Baidu Core was RMB 19.4 billion, and net margin for Baidu Core was 19%, 1-9. Non-GAAP net income attributable to Baidu was RMB 28.7 billion, non-GAAP diluted earnings per ADS was RMB 80.85. Non-GAAP net income attributable to Baidu Core was RMB 27.4 billion, and non-GAAP net margin for Baidu Core was 26%.

2023年，歸屬於百度的淨利為203億元人民幣，每ADS攤薄收益為55.08元。歸屬於百度核心的淨利為人民幣194億元，百度核心淨利率為19%，1-9。非 GAAP 歸屬於百度的淨利潤為人民幣 287 億元，非 GAAP 攤薄後每股美國存託憑證收益為 80.85 元。非美國通用會計準則歸屬於百度核心的淨利為人民幣274億元，非美國通用會計準則淨利率為26%。

As of December 31, 2023, cash, cash equivalents, restricted cash and short-term investments were RMB 205.4 billion and cash, cash equivalents, restricted cash and short-term investments excluding iQIYI, were RMB 200 billion. Free cash flow was RMB 25.4 billion, and free cash flow, excluding iQIYI, was RMB 22.1 billion in 2023. Baidu Core had approximately 35,000 employees as of December 31, 2023.

截至2023年12月31日，現金、現金等價物、限制性現金及短期投資為人民幣2,054億元，除愛奇藝外的現金、現金等價物、限制性現金及短期投資為人民幣2,000億元。自由現金流為人民幣254億元，2023年自由現金流（不包括愛奇藝）為人民幣221億元。截至2023年12月31日，百度核心約有35,000名員工。

With that, operator, let's now open the call to questions.

接線員，現在讓我們開始提問。

(Operator Instructions) Our first question today will come from Alicia Yap of Citi.

（操作員說明）我們今天的第一個問題將來自花旗銀行的 Alicia Yap。

My question is on the outlook. How does management think about the macroeconomic landscape in China for 2024? What's management view on 2024 growth outlook for Baidu as a whole? And also, what is the percentage of total revenues of Baidu will be contributed from the AI-related revenue in 2024?

我的問題是關於前景。管理階層如何看待2024年中國宏觀經濟情勢？管理階層對百度 2024 年整體成長前景有何看法？另外，2024年AI相關收入佔百度總收入的比例是多少？

Alicia, this is Robin. Before we dive into the outlook, let's take a quick look back last year. We had a very challenging macroeconomic environment, but our business demonstrated very solid performance. We invested very aggressively in Gen AI, but our non-GAAP operating margin expanded year-over-year and revenue experienced solid growth. More importantly, we began to generate incremental revenue from Gen AI and foundation models. And for this year, we have noticed that both the central and local governments are putting efforts to grow the economy.

艾莉西亞，這是羅賓。在我們深入探討前景之前，讓我們先快速回顧一下去年。我們的宏觀經濟環境非常具有挑戰性，但我們的業務表現非常穩健。我們對 Gen AI 進行了非常積極的投資，但我們的非 GAAP 營業利潤率逐年擴大，收入也實現了穩健成長。更重要的是，我們開始從 Gen AI 和基礎模型中產生增量收入。今年以來，我們注意到中央和地方政府都在大力發展經濟。

And during the 8-day Chinese New Year holiday, we saw a growth in consumption, particularly in the travel sector. But we're still operating in a macro environment with a lot of uncertainty. We are closely monitoring significant economic stimulus plan, which we think is essential for achieving this year's goals. But that being said, Baidu is facing a lot of opportunities. Our core business remains solid, and the incremental revenue from Gen AI and foundation models were increased to several billion RMB in 2024. This will contribute to the growth of our total revenue.

在8天的春節假期期間，我們看到了消費的成長，尤其是旅遊領域。但我們仍處於充滿不確定性的宏觀環境。我們正在密切關注重要的經濟刺激計劃，我們認為這對實現今年的目標至關重要。但話雖如此，百度面臨著許多機會。我們的核心業務依然穩健，2024年Gen AI和基礎模型的增量收入將增至數十億元人民幣，這將有助於我們總收入的成長。

More specifically, thanks to our leading position in LLM and Gen AI, enterprises are increasingly building models and developing apps, the Baidu Cloud. And for our Mobile Ecosystem, we have already accumulated a huge user base and we keep renovating our products and enhancing our [monetized] reaching capabilities through AI innovation. So when we combine Cloud and Mobile, I think we will be able to sustain our long-term growth which we think will be faster than China's GDP growth. Thank you.

更具體地說，由於我們在LLM和Gen AI方面的領先地位，企業越來越多地構建模型和開發應用程序，即百度雲。對於我們的行動生態系統，我們已經累積了龐大的用戶基礎，我們不斷更新我們的產品，並透過人工智慧創新增強我們的[貨幣化]觸達能力。因此，當我們將雲端和行動結合起來時，我認為我們將能夠維持長期成長，我們認為這種成長將快於中國的 GDP 成長。謝謝。

Okay. And our next question today will come from Alex Yao of JPMorgan. Hi, Alex, your line is open. Are you muted?

好的。今天我們的下一個問題將來自摩根大通的 Alex Yao。嗨，亞歷克斯，您的線路已開通。你靜音了嗎？

Yes. Sorry, I was muted. I have a couple of questions on cost structure and the margin trends. First of all, how much more room do we see in the cost cutting and optimization, how should we look at AI-related investments. In the past, you guys discussed that there will be a lag between chip investments and AI revenue contribution? How should we look at the margin trend into 2024, if you intend to expand?

是的。抱歉，我被靜音了。我有幾個關於成本結構和利潤趨勢的問題。首先，我們在成本削減和優化方面還有多少空間，我們應該如何看待人工智慧相關的投資。過去你們討論過晶片投資和AI收入貢獻之間會存在滯後嗎？如果您打算擴張，我們應該如何看待 2024 年的利潤趨勢？

Alex, thank you so much for your questions. This is Julius. I think alongside the investments in our Gen AI businesses, it's pretty sure that there is still room. We can manage the cost and the expenses in our legacy businesses. As we look into the 2024, we will continue to focus on our core businesses, and we also will be very firm to reduce our resource allocations to the nonstrategic businesses. Additionally, we are continuously enhancing our overall organization efficiencies by removing the layers, simplifying the executions and flattening the organization structures. So heading into this year, we are very committed to the ongoing optimization of our operations, ensuring we have a more productive and agile team. And with all these measures in plan, and we aim to keep Baidu Core's earnings solid with our Mobile Ecosystem continue to deliver the [wide range] of margins and generated very strong cash flows while the AI Cloud business continues its profitability.

亞歷克斯，非常感謝你的提問。這是朱利葉斯。我認為，除了對我們的 Gen AI 業務的投資之外，可以肯定的是仍然有空間。我們可以管理傳統業務的成本和開支。展望2024年，我們將持續專注於核心業務，同時也會非常堅定地減少對非策略性業務的資源配置。此外，我們透過消除層級、簡化執行和扁平化組織結構，不斷提高整體組織效率。因此，進入今年，我們非常致力於持續優化我們的運營，確保我們擁有一支更有效率和敏捷的團隊。透過計劃中的所有這些措施，我們的目標是保持百度核心的盈利穩健，我們的行動生態系統繼續提供[廣泛]的利潤並產生非常強勁的現金流，同時人工智慧雲端業務繼續保持盈利能力。

We have managed to maintain a solid operation profit margins despite our investments in AI, if you still remember from year 2023 and on, we started to invest in generative AI and large language models. This investment is primarily reflected in our CapEx and mainly related to the purchasing chips and servers for the model training and inference. As you know, the CapEx will be depreciated over several years, so despite a 58% year-over-year increase in Baidu's cost CapEx in 2023, our non-GAAP operating profit margins still saw a 2 percentage growth on a year-over-year basis.

儘管我們在人工智慧方面進行了投資，但如果你還記得從 2023 年起，我們就開始投資生成式人工智慧和大型語言模型，但我們仍設法保持了穩健的營運利潤率。這項投資主要反映在我們的資本支出中，主要與購買用於模型訓練和推理的晶片和伺服器有關。如您所知，資本支出將在幾年內貶值，因此儘管 2023 年百度的成本資本支出同比增長 58%，但我們的非 GAAP 營運利潤率仍同比增長 2%。年為基礎。

Looking forward in the process of developing our new AI business, it is inevitable that we will make new investments. However, these investments are not expected to significantly affect our margins or profits. And during the quite early stage of the market development, we also will now overly prioritize margins for our AI Cloud business. And as we believe that in the long run, this business is expected to yield much better margins.

展望未來，在發展人工智慧新業務的過程中，我們不可避免地會進行新的投資。然而，這些投資預計不會對我們的利潤或利潤產生重大影響。在市場發展的早期階段，我們現在也會過度優先考慮人工智慧雲端業務的利潤。我們相信，從長遠來看，這項業務預計將產生更好的利潤率。

And additionally, there may be some promotional activities for the AI native 2C products, but we will carefully manage and closely monitor the online to balance the investments and growth. We are happy to see that our efforts in investing in new initiatives have begun to hear the early results. As Robin has mentioned just now, the incremental revenue generated from the ad tech improvement have reached several million hundred RMB in Q4 and the incremental AI Cloud revenue generated from Gen AI and financial models also contributed to 4.8% of the total AI Cloud revenue.

另外，AI原生2C產品可能會有一些促銷活動，但我們會仔細管理和密切監控線上，以平衡投資和成長。我們很高興看到我們投資新措施的努力已開始收到早期成果。正如Robin剛才提到的，第四季廣告科技改進帶來的增量收入已經達到數百萬元人民幣，而Gen AI和金融模型帶來的AI雲增量收入也貢獻了AI Cloud總收入的4.8 %。

I think all of these promising and top line achievements have strengthened our confidence in our business strategy. So going forward, we will remain steadfast in our commitment to development -- to the development of the Gen AI and large language model use. Thank you, Alex.

我認為所有這些有前途的頂級成就增強了我們對業務策略的信心。因此，展望未來，我們將堅定不移地致力於開發——開發 Gen AI 和大型語言模型的使用。謝謝你，亞歷克斯。

Our next question today will come from Gary Yu of Morgan Stanley.

今天我們的下一個問題將來自摩根士丹利的 Gary Yu。

I have a question regarding AI contribution. So for AI-related revenue contribution, is there a way you can quantify or prove that the ad revenues Baidu will be generating is purely incremental contribution from AIGC and not cannibalizing from your existing search business. And if AI is purely incremental, should we be expecting faster than average growth. And excluding AI, how should we think about the Core such growth rate for 2024?

我有一個關於人工智慧貢獻的問題。那麼對於人工智慧相關的收入貢獻，有沒有一種方法可以量化或證明百度將產生的廣告收入純粹是AIGC的增量貢獻，而不是蠶食你現有的搜尋業務。如果人工智慧純粹是漸進式的，我們是否應該期待比平均更快的成長。排除人工智慧，我們該如何看待2024年核心的成長率？

Gary, this is Robin. We are the largest search engine in China. We have close to 700 million monthly active users and we have established a very robust brand presence among the Chinese Internet and mobile users. They rely on us for comprehensive and reliable information. So we have a strong and stable base revenue and profits. But we are also very sensitive to macro because our advertising business has very broad coverage of different verticals.

加里，這是羅賓。我們是中國最大的搜尋引擎。我們每月擁有近 7 億活躍用戶，並在中國網路和行動用戶中建立了非常強大的品牌影響力。他們依靠我們提供全面可靠的資訊。所以我們有強大而穩定的收入和利潤基礎。但我們對宏觀也非常敏感，因為我們的廣告業務對不同垂直領域的覆蓋範圍非常廣泛。

I mentioned earlier that there are still uncertainties with the macro environment. But Gen AI and LLM are unlocking new opportunities both at the monetization front and the user engagement front. I think it's easier to quantify the incremental revenue on the monetization front. I mentioned earlier that Gen AI has already helped increase advertising ECPM. And our upgraded monetization system has allowed us to improve targeting capabilities, thereby generating and presenting more relevant ads. We earned a several hundred millions in Q4 from this kind of initiative. And the incremental revenue will grow to several billion this year.

我剛才提到，宏觀環境還存在不確定性。但 Gen AI 和 LLM 正在貨幣化方面和用戶參與方面釋放新的機會。我認為量化貨幣化方面的增量收入更容易。我之前提到Gen AI已經幫助提高了廣告ECPM。升級後的獲利系統使我們能夠提高定位能力，從而產生和呈現更多相關的廣告。我們透過這種舉措在第四季度賺取了數億美元。今年增量收入將成長到數十億。

It's harder to quantify the user engagement part, Gen AI is helping us improve user experience. We have seen initial outcomes in search and one pool, and we will continue introducing new features going forward. These initiatives will help us improve the user mind share and time spent over time and bring us even larger potential. So I think the purely incremental revenue will come from both side and the user engagement side. Thank you.

使用者參與度部分比較難量化，Gen AI 正在幫助我們改善使用者體驗。我們已經在搜尋和一個池中看到了初步成果，我們將繼續推出新功能。這些措施將幫助我們隨著時間的推移提高用戶的心智份額和花費時間，並為我們帶來更大的潛力。所以我認為純粹的增量收入將來自雙方和用戶參與。謝謝。

Our next question today will come from Lincoln Kong of Goldman Sachs.

今天我們的下一個問題將來自高盛的林肯孔。

So my question is regarding the Cloud business. How should we look at the incremental revenue growth that's driven by Generative AI, so what is the product mix for Generative AI Cloud? And what exactly are the offerings that primary growth drivers here. And then when we're looking at 2024, how should we expect the overall AI Cloud revenue growth this year and that will be the margin trend this year as well.

我的問題是關於雲端業務的。我們該如何看待Generative AI帶來的增量營收成長，那麼Generative AI Cloud的產品組合是什麼呢？而主要推動成長的產品到底是什麼？然後，當我們展望 2024 年時，我們應該如何預期今年人工智慧雲端的整體營收成長，這也將是今年的利潤率趨勢。

Thank you for the question. This is Julius. As Robin just mentioned, the total revenue from our -- from the Gen AI and the foundation model related businesses, including both internal and external revenue already reached RMB 656 million in Q4, and this number should grow to several billion RMB for the full year 2024.

感謝你的提問。這是朱利葉斯。正如Robin剛才所提到的，我們的－來自Gen AI和基礎模型相關業務的總收入，包括內部和外部收入，在第四季度已經達到6.56億元人民幣，全年這個數字應該會增長到幾十億元人民幣2024 年。

We have seen increasing interest from enterprises in using Gen AI and LLM to develop new applications and features. To achieve this goal, so they are actively building models to power their products and solutions. So this is how we generate the majority of the revenue from external customers. Meanwhile, we were seeing a significant increase in model inferencing revenue from external customers. So the revenue from inferencing is still small. We believe that over the long term, it will become a significant and sustainable revenue driver.

我們看到企業對使用 Gen AI 和 LLM 開發新應用程式和功能越來越感興趣。為了實現這一目標，他們正在積極建立模型來支持他們的產品和解決方案。這就是我們從外部客戶獲得大部分收入的方式。同時，我們看到來自外部客戶的模型推理收入顯著增加。所以推理的收入還是很小的。我們相信，從長遠來看，它將成為一個重要且可持續的收入驅動因素。

We think revenue generated by internal customers is also quite important because a significant portion of such revenue is for model inferencing, so Baidu is the first company to use Gen AI and LLM to reconstruct all the businesses and products. So with the number of products and features powered by Gen AI and ILM continue to increase ERNIE API costs from internal customers have been increasing rapidly and have reached a significant magnitude.

我們認為內部客戶產生的收入也很重要，因為其中很大一部分收入是模型推理，所以百度是第一家使用Gen AI和LLM來重建所有業務和產品的公司。因此，隨著 Gen AI 和 ILM 支援的產品和功能數量不斷增加，來自內部客戶的 ERNIE API 成本一直在迅速增加，並達到了相當大的程度。

As such development has proven that ERNIE and ERNIE bot can well enhance the productivity and efficiency in real-world applications. And we also believe a growing number of external customers will use ERNIE to develop their own apps and drive our external revenue in the future.

這樣的發展已經證明 ERNIE 和 ERNIE bot 可以很好地提高實際應用中的生產力和效率。我們也相信越來越多的外部客戶將使用 ERNIE 開發自己的應用程式並在未來推動我們的外部收入。

So regarding your question about our product offerings, we have the most powerful AI infrastructure for model training and inferencing in China. So this infrastructure helps our customers build and run models cost effectively. Additionally, as Robin mentioned earlier, our months offers various models and a full set of tools in terms of model builder and app builder for model building and application development.

因此，關於您關於我們產品的問題，我們擁有中國最強大的模型訓練和推理人工智慧基礎設施。因此，該基礎設施可以幫助我們的客戶經濟高效地建立和運行模型。此外，正如 Robin 之前提到的，我們的月份在模型建構器和應用程式建構器方面提供了各種模型和全套工具，用於模型建置和應用程式開發。

So in addition to that, we have developed our own AI native solutions, such as GBI, that is a generative business intelligence. So those applications are helping enterprises increased productivity and efficiency. In addition to the incremental opportunity related to AI, Gen AI and foundation models also bring new opportunities to our legacy cloud businesses. So firstly, we continue to win customers and projects for super centric cloud because we are being highly recognized for our AI infrastructure and the CPU-centric cloud offerings, especially in the Internet and tech and education sectors.

除此之外，我們也開發了自己的人工智慧原生解決方案，例如GBI，這是一種生成式商業智慧。因此，這些應用程式正在幫助企業提高生產力和效率。除了與人工智慧相關的增量機會外，Gen AI和基礎模型也為我們的傳統雲端業務帶來了新的機會。首先，我們繼續贏得超級中心雲端的客戶和項目，因為我們的人工智慧基礎設施和以CPU為中心的雲端產品得到了高度認可，特別是在網路、科技和教育領域。

Secondly, Gen AI and foundation models have allowed us to build AI solutions for our customers more efficiently than before, facilitating digital and intelligent transformations for traditional industries. So both of these 2 factors are driving growth for our cloud revenue. And overall, we should see cloud revenue growth accelerate in 2024 over last year.

其次，Gen AI和基礎模型使我們能夠比以前更有效率地為客戶建立人工智慧解決方案，促進傳統產業的數位化和智慧轉型。因此，這兩個因素都在推動我們的雲端收入成長。總體而言，我們應該會看到 2024 年雲端收入成長將比去年加速。

Additionally, we are pretty confident in maintaining profitability for our AI Cloud. For Enterprise Cloud, we should be able to consistently improve gross margins for the Lexi Cloud businesses. As for Gen AI and LLM businesses, the market is still at a very early stage of development. So we should hold a pretty dynamic pricing strategy to quickly educate the market and expand our penetration into more enterprise customers.

此外，我們對維持人工智慧雲端的獲利能力非常有信心。對於企業雲，我們應該能夠持續提高Lexi Cloud業務的毛利率。至於Gen AI和LLM業務，市場仍處於非常早期的發展階段。因此，我們應該採取相當動態的定價策略，以快速教育市場並擴大我們對更多企業客戶的滲透。

So we believe over the long term, the new business should have a higher normalized margins than the traditional cloud businesses. Thank you.

因此，我們認為，從長遠來看，新業務應該比傳統雲端業務擁有更高的正常化利潤率。謝謝。

Our next question today will come from Thomas Chong of Jefferies.

今天我們的下一個問題將來自 Jefferies 的 Thomas Chong。

May I ask about the pace for our AI 2C product development how has the traffic growth been? And any key metrics which can be shared on the new generative search? How AI benefits search traffic time spent? And when should we see the exposure of traffic or super app?

請問我們AI 2C產品的開發進度，流量成長如何？以及可以在新的生成搜尋中共享的任何關鍵指標？人工智慧如何使搜尋流量所花費的時間受益？而我們什麼時候該看到流量或超級應用的曝光呢？

Yes, we are reconstructing all of our 2C products using generative AI. I think Gen AI and foundation models are making all of our products more powerful. Over the past few months, we made significant strides in this kind of efforts and the initial user feedback has been encouraging. For search, the introduction of Gen AI has enabled Baidu to answer a broader range of questions, including more complex, open-ended and comparative queries.

是的，我們正在使用生成式人工智慧重建我們所有的 2C 產品。我認為 Gen AI 和基礎模型正在使我們所有的產品變得更強大。在過去的幾個月裡，我們在這方面的努力取得了重大進展，最初的用戶回饋也令人鼓舞。在搜尋方面，Gen AI的引入使百度能夠回答更廣泛的問題，包括更複雜、開放和比較性的查詢。

With ERNIE bot, we can provide direct and clear answers in a more interactive way. During the past few months, instead of just lending some content and providing some links, more and more search results were generated by ERNIE bot. As a result, users are engaging with Baidu more frequently and asking new questions. For example, more and more users are coming to Baidu for content creation, be it text or images.

透過 ERNIE 機器人，我們可以以更互動的方式提供直接、清晰的答案。在過去的幾個月裡，ERNIE 機器人不再只是藉出一些內容和提供一些鏈接，而是產生了越來越多的搜尋結果。因此，使用者更頻繁地與百度互動並提出新問題。例如，越來越多的使用者來到百度進行內容創作，無論是文字或圖像。

During the Chinese New Year holiday, Baidu helped users create new year greeting messages and generate personalized e-card for their loved ones. This is not a typical use case for search engine, but we see a large number of users rely on Baidu for this kind of needs. Going forward, we will increasingly use ERNIE bot to generic answers for search queries and then use multiround conversation to clarify user intent, so that complicated user needs can be addressed through natura l language.

春節期間，百度幫助使用者製作新年祝福語，並為親人製作個人化電子賀卡。這不是搜尋引擎的典型用例，但我們看到大量用戶依賴百度來滿足這種需求。展望未來，我們將越來越多地使用 ERNIE 機器人來通用回答搜尋查詢，然後使用多輪對話來闡明用戶意圖，以便透過自然語言來解決複雜的用戶需求。

While these initiatives have resulted in an enhanced search experience, we are still in the early stages of using ERNIE bot to reconstruct Baidu search. We will continue to test and iterate Gen AI enabled features based on user feedback. And we will follow our typical playbook for testing and fine-tuning new experiences before upgrades are ready for a larger scale rollout.

雖然這些舉措增強了搜尋體驗，但我們仍處於使用 ERNIE 機器人重構百度搜尋的早期階段。我們將根據用戶回饋繼續測試和迭代 Gen AI 支援的功能。在升級準備好大規模部署之前，我們將遵循我們的典型策略來測試和微調新體驗。

Overall, we believe Gen AI will complement to traditional search. Ultimately, increasing user retention engagement and time spent on Baidu. And in addition to search, ERNIE bot acting as a copilot Wenku has transformed from an application for users to find tablets and documents to a one-stop-shop for users to create content in a wide range of format. And year-to-date, I think about 18% of new paying users were attracted by Gen AI features for Wenku.

總體而言，我們相信 Gen AI 將補充傳統搜尋。最終，提高用戶留存度以及在百度上花費的時間。除了搜尋之外，作為副駕駛文庫的ERNIE機器人已經從一個供用戶尋找平板電腦和文件的應用程式轉變為供用戶創建各種格式內容的一站式商店。今年迄今為止，我認為大約有 18% 的新付費用戶被文庫的 Gen AI 功能所吸引。

I want to emphasize that we are in the early stages of using ERNIE bots to reconstruct our apps and build new ones. And at the same time, we are attracting and helping enterprises build apps on learning. We believe the success of ERNIE depend on its wide and active adoption, whether through Baidu app or through third-party apps.

我想強調的是，我們正處於使用 ERNIE 機器人重建我們的應用程式並建立新應用程式的早期階段。同時，我們正在吸引並幫助企業建立學習應用程式。我們相信 ERNIE 的成功取決於其廣泛且積極的採用，無論是透過百度應用程式還是透過第三方應用程式。

Our next question today will come from James Lee of Mizuho.

今天我們的下一個問題將來自瑞穗銀行的詹姆斯李。

Can you guys maybe talk about ERNIE's technology road map for 2024. Does it include multimodal feature, maybe similar to Sora or maybe opening up an AI store or potentially launching AI engine. Is there any sort of milestone or key metrics you can speak to?

你們能否談談 ERNIE 2024 年的技術路線圖。它是否包括多模式功能，可能類似於 Sora，或者可能開設 AI 商店或可能推出 AI 引擎。您可以談談任何類型的里程碑或關鍵指標嗎？

And the second part to that question is on the cost of running Gen AI, how should we think about maybe puts and take on managing inferencing costs going forward? Obviously, you talked about some ways to make it more efficient. Are there any additional levers to optimize this process?

這個問題的第二部分是關於運行 Gen AI 的成本，我們應該如何考慮未來的推理成本管理？顯然，您談到了一些提高效率的方法。是否有其他手段來優化此流程？

Yes, the chips we have on hand should enable us to advance EB4 to the next level. As I mentioned earlier, we will take an application-driven approach to inference ERNIE and that our users and customers tell us where we should improve and adjust for our models. It could be building multi-modalities, agents increasing reliability and so on.

是的，我們手邊的晶片應該能讓我們將 EB4 推進到一個新的水平。正如我之前提到的，我們將採用應用程式驅動的方法來推理 ERNIE，我們的用戶和客戶會告訴我們應該在哪些方面改進和調整我們的模型。它可以建立多模式、提高可靠性的代理程式等等。

It's important to note that we are focusing on using ERNIE to bring real value to users and customers rather than simply achieving high ranking on most research publication. And you're right, price is a very important issue, making high-performance foundation model affordable is critical for large-scale operations. I mentioned earlier that we have been continuously reducing model inference cost. Now the interest cost of EB 3.5 is about 1% of March of 2023 version.

值得注意的是，我們專注於使用 ERNIE 為使用者和客戶帶來真正的價值，而不是簡單地在大多數研究出版物上獲得高排名。你說得對，價格是一個非常重要的問題，讓高性能基礎模型價格實惠對於大規模營運至關重要。我之前提到，我們一直在不斷降低模型推理成本。現在EB 3.5的利息成本約為2023年3月版本的1%。

By doing so, more and more enterprises are increasingly willing to test, develop and iterate their applications on ERNIE. We understand that for many customers, they tend to balance efficiency with cost and speed. So we also offer smaller language model and help our customers leverage MOE that's a mixture of experts for our best performance.

透過這樣做，越來越多的企業越來越願意在 ERNIE 上測試、開發和迭代他們的應用程式。我們了解，對於許多客戶來說，他們傾向於在效率與成本和速度之間取得平衡。因此，我們也提供更小的語言模型，並幫助我們的客戶利用由專家組成的 MOE 來實現最佳效能。

With our end-to-end approach, we believe there is still ample room to reduce the cost of our most powerful models and make them increasingly affordable to our customers. And this will help further drive the adoption of ERNIE. Internally, we are closely monitoring the number of apps developed by -- developed on ERNIE. As I mentioned previously, ERNIE now handling over 50 million queries per day. And right now, ERNIE API costs from internal application are still larger than external app cost. But cost for ERNIE in different sizes from external apps have been increasingly -- have been increasing rapidly. We're just at the beginning of this journey, ERNIE will only become more powerful, smarter and more useful as more and more end users use it be it through Baidu apps or through third-party apps.

透過我們的端到端方法，我們相信仍有足夠的空間來降低我們最強大模型的成本，並使我們的客戶越來越負擔得起它們。這將有助於進一步推動 ERNIE 的採用。在內部，我們正在密切監視在 ERNIE 上開發的應用程式的數量。正如我之前提到的，ERNIE 現在每天處理超過 5000 萬個查詢。目前，內部應用程式的 ERNIE API 成本仍然高於外部應用程式成本。但來自外部應用程式的不同大小的 ERNIE 的成本一直在快速增長。我們才剛開始這個旅程，隨著越來越多的最終用戶透過百度應用程式或第三方應用程式使用 ERNIE，ERNIE 只會變得更強大、更聰明、更有用。

This will enable us to cultivate an ecosystem around ERNIE. As these apps and models are actively used by end users, they will also generate significant inferencing revenue for us. Thank you.

這將使我們能夠圍繞 ERNIE 培育一個生態系統。由於這些應用程式和模型被最終用戶積極使用，它們也將為我們帶來可觀的推理收入。謝謝。

Our next question today will come from Charlene Liu of HSBC.

今天我們的下一個問題將來自匯豐銀行的 Charlene Liu。

Thank you. Good evening, management, and thank you again for the opportunity I have a question related to ERNIE. How does earnings enterprise adoption compared to its peers? Can you please kindly share with us the latest number of enterprises that are using ERNIE to build models and applications and help us understand how that has gone versus last quarter and what the underlying drivers may be? Lastly, can you help us also understand whether we can assume that enterprises who apply the ERNIE API integration will very unlikely be using other elements.

謝謝。晚上好，管理層，再次感謝您給我這個機會，我有一個與 ERNIE 有關的問題。與同業相比，企業採用率的獲利情況如何？您能否與我們分享使用 ERNIE 建立模型和應用程式的最新企業數量，並幫助我們了解上季度的情況以及潛在的驅動因素是什麼？最後，您能否幫助我們了解我們是否可以假設應用 ERNIE API 整合的企業不太可能使用其他元素。

Great question, Charlene. So as Robin just mentioned, right, about 26,000 enterprises of different sizes, spreading over different verticals, caught our ERNIE API from our cloud in December marking a 150% increase quarter-over-quarter. The ERNIE API costs have exceeded 50 million on a daily basis, and we believe no one else in China has gained so many customers and received such a high volume of API requests.

很好的問題，夏琳。正如 Robin 剛才提到的，大約 26,000 家不同規模、分佈在不同垂直領域的企業在 12 月從我們的雲端中獲取了我們的 ERNIE API，環比增長了 150%。 ERNIE API 每天的費用已超過 5,000 萬，我們相信在中國沒有其他公司能夠獲得如此多的客戶並收到如此大量的 API 請求。

The enterprises choosers primarily for the following reasons. Firstly, we have the most cost-efficient AI infrastructure for model inferencing and inferencing in China, primarily because of our strong ability of end-to-end optimization. Just mentioned before, Gen AI and large language models are reshaping the competitive landscape China's public cloud inventory and enhancing our competitive advantage. So our strong ability in managing extensive GPU-centric cloud with very high GPU utilization reach has continuously enhanced our AI infrastructure. So as a result, we can help enterprises build and run their models and develop AI native apps at low cost on our cloud.

企業選擇的原因主要有以下幾點。首先，我們擁有中國最具成本效益的模型推理和推理的人工智慧基礎設施，主要是因為我們強大的端到端優化能力。剛才提到，Gen AI和大語言模型正在重塑中國公有雲存量的競爭格局，增強我們的競爭優勢。因此，我們管理廣泛的以 GPU 為中心的雲端以及極高的 GPU 利用率的強大能力不斷增強了我們的人工智慧基礎設施。因此，我們可以幫助企業在我們的雲端上以低成本建置和運行他們的模型並開發人工智慧原生應用程式。

Secondly, the EB family of models have attracted many customers to our cloud. Over the past few months, we have consistently enhanced ERNIE performance, receiving positive feedback from the customers. We also offer ERNIE models in different sizes to better accommodated customers' needs regarding cost structures.

其次，EB系列模型吸引了許多客戶使用我們的雲端。在過去的幾個月裡，我們不斷提高 ERNIE 的效能，並收到了客戶的正面回饋。我們也提供不同尺寸的 ERNIE 型號，以更好地滿足客戶對成本結構的需求。

Thirdly, we were the first company in China to launch a model as a service offering, which is a one-stop-shop for LLM and AI native application development. So our models makes it easy for enterprises to use LLMs. We're also providing toolkit to help enterprises easily trim or fine-tune their models and develop applications on our cloud.

第三，我們是中國第一家推出模型即服務的公司，這是LLM和AI原生應用程式開發的一站式商店。所以我們的模型讓企業可以輕鬆使用LLM。我們還提供工具包來幫助企業輕鬆修剪或微調其模型並在我們的雲端上開發應用程式。

So with the toolkits, customers can [train] purpose build model cost effectively by incorporating their proprietary data, and they can directly use ERNIE's API to power their own applications as well. We can also help them to support different product features using different models adopting the MOE approach in the app development.

因此，借助這些工具包，客戶可以透過整合其專有資料來經濟高效地[訓練]專用建立模型，並且他們還可以直接使用 ERNIE 的 API 來為自己的應用程式提供支援。我們還可以幫助他們在應用程式開發中採用 MOE 方法，使用不同的模型來支援不同的產品功能。

So as a result, enterprises can focus on identifying customers' pinpoints rather than expanding their efforts on the program. So all of these initiatives have helped us establish a first-mover advantage in Gen AI and LLMs.

因此，企業可以專注於識別客戶的需求，而不是擴大在該計劃上的努力。因此，所有這些舉措都幫助我們在 Gen AI 和 LLM 領域建立了先發優勢。

For your last question, as more customers use our MaaS platform to develop AI native applications aimed at attracting users, substantial user and customer insights will be generated and accumulated on our cloud. So these insights will also allow us to further refine the toolkits. As our tools become increasingly customer friendly and help enterprises effortlessly fine tune models and create apps. They will be more inclined to stay with us.

對於你的最後一個問題，隨著越來越多的客戶使用我們的 MaaS 平台來開發旨在吸引用戶的 AI 原生應用程序，大量的用戶和客戶洞察將在我們的雲端上產生和累積。因此，這些見解也將使我們能夠進一步完善工具包。隨著我們的工具變得越來越對客戶友好，並幫助企業輕鬆調整模型和創建應用程式。他們會更願意留在我們身邊。

Additionally, it is worth noting that at the current stage of employing large language models, it is crucial for customers to create suitable prompts for their chosen models. So since they had to invest a considerable effort in building and accumulating their best props -- prompts for using large language models. And it becomes intelligent for them to switch to another model because they will have to reestablish their prompt portfolio. So as a result with increasing adoption and active usage of our platform, customer satisfaction and switching costs will help us increase the customer retention.

此外，值得注意的是，在使用大型語言模型的現階段，客戶為自己選擇的模型創建合適的提示至關重要。因此，由於他們必須投入大量精力來建造和累積最好的道具——提示使用大型語言模型。他們轉向另一種模式變得明智，因為他們將不得不重新建立他們的即時投資組合。因此，隨著我們平台的採用和積極使用的增加，客戶滿意度和轉換成本將幫助我們提高客戶保留率。

Our next question today will come from Miranda Zhuang of Bank of America Securities.

今天我們的下一個問題將來自美國銀行證券的 Miranda Zhuang。

About the AI chip, wondering what's the impact on your AI development after the recent further chip restriction from U.S. Is there any update on the alternative chips. Given the chip constraint, how is Baidu developing the AI model product and monetization differently versus the overseas peers, what can be achieved and what may become difficult? And what will the company do to keep up with the overseas peers in the next few years?

關於AI晶片，想知道最近美國進一步限制晶片後，對你們的AI發展有什麼影響，替代晶片有什麼更新嗎？考慮到晶片的限制，百度在AI模型產品和變現方面與國外同行有何不同，可以實現什麼，可能會變得困難什麼？未來幾年，公司將如何做才能跟上海外同業的腳步？

In the near term, the impact is minimal for our model development or product inventions or monetization. As I mentioned last quarter, we already have the most powerful foundation model in China and our AI chip reserve enables us to continue enhancing ERNIE for the next 1 or 2 years. And for model inference, it requires less powerful chips. Our reserve and the chips available on the market are sufficient for us to power many AI native application for end users and customers.

短期內，對我們的模型開發、產品發明或貨幣化的影響很小。正如我上季度提到的，我們已經擁有國內最強大的基礎模型，我們的AI晶片儲備使我們能夠在未來一兩年內繼續增強ERNIE。而對於模型推理來說，它需要的晶片功能不太強大。我們的儲備和市場上可用的晶片足以讓我們為最終用戶和客戶提供許多人工智慧原生應用程式的支援。

And in the long run, we may not have access to the most cutting-edge GPUs, but with the most efficient homegrown software stack. Net-net, the user experience will not be compromised. There's ample room for innovation in the application layer, the model layer and the framework layer.

從長遠來看，我們可能無法使用最先進的 GPU，但可以使用最高效的本土軟體堆疊。 Net-net，使用者體驗不會受到損害。應用層、模型層、框架層都有很大的創新空間。

Our end-to-end self-developed 4-layer AI architecture along with our strong R&D team will support us in using less advanced chips for efficient model training and inferencing. This provides Baidu with a unique competitive advantage over our domestic peers. And for enterprises and developers, building applications on ERNIE, will be the best and most efficient way to embrace AI.

我們端到端自主開發的四層人工智慧架構以及強大的研發團隊將支援我們使用不太先進的晶片進行高效的模型訓練和推理。這為百度提供了相對於國內同行獨特的競爭優勢。而對於企業和開發者來說，在 ERNIE 上建立應用程序，將是擁抱 AI 的最佳、最高效的方式。

Our next question today will come from Ken Wan of UBS.

今天我們的下一個問題將來自瑞銀集團的 Ken Wan。

This is (inaudible) on behalf of Kenneth. So my question is, recent days, we have seen numerous developments in text to video or video generation technology. So how do you envision this technology impacting the broader AI industry development in China and what implications that it would hold for ERNIE. Could you elaborate on your strategic road map for ERNIE moving forward?

這是（聽不清楚）代表肯尼思。所以我的問題是，最近幾天，我們看到文字到影片或影片產生技術的許多發展。那麼，您如何看待這項技術對中國更廣泛的人工智慧產業發展的影響以及它將對 ERNIE 產生什麼影響。能否詳細說明一下 ERNIE 前進的策略路線圖？

Furthermore, how does ERNIE currently perform in text generation and text to image, text to video generation task? And what improvements do you foresee in these areas.

此外，ERNIE目前在文字生成以及文字轉圖像、文字轉影片生成任務方面表現如何？您預計這些領域會有哪些改進？

This is Robin. First of all, multi model or the integration of multi-modalities such as text to audio and video is an important direction for future foundation model development. It is a must have for AGI. And Baidu has already invested in this area, and will continue to do so in the future.

這是羅賓。首先，多模型或文字到音訊、視訊等多模態的融合是未來基礎模型發展的重要方向。這是 AGI 的必備條件。而百度已經在這方面進行了投入，未來還會繼續這樣做。

Secondly, if we look at the development of foundation models, the market for large language models is huge and still at very early stages. Even the most powerful language models in the world are still not good enough for a lot of applications. There are plenty of room for innovation. Smaller-sized models, MOE and agents are all evolving very quickly. We strive to make this offering more accessible to all type of enterprises and solve real world problems in various scenarios.

其次，如果我們看一下基礎模型的發展，大型語言模型的市場龐大，而且還處於非常早期的階段。即使世界上最強大的語言模型對於許多應用程式來說仍然不夠好。有很大的創新空間。較小規模的模型、MOE 和代理程式都在快速發展。我們努力讓所有類型的企業更容易使用此產品，並解決各種場景中的現實問題。

And thirdly, in the realm of visual foundation model. One, notably, a significant application with vast market potential is autonomous driving, in which Baidu is a pioneer and global leader. We have been using diffusion and transformer to train our video generation models for self-driving purposes. We have also consistently made strides in object classification, detection and segmentation, thereby better understanding the physical world and the rule of the physical world. This has enabled us to translate images and videos captured on the road into specific tasks resulting in more intelligent, adaptable and safe autonomous driving technology.

第三，在視覺基礎模型領域。值得注意的是，一個具有巨大市場潛力的重要應用是自動駕駛，百度是其中的先驅和全球領導者。我們一直在使用擴散和變壓器來訓練我們的視訊生成模型以用於自動駕駛目的。我們在物件分類、檢測和分割方面也不斷取得進步，從而更好地理解物理世界和物理世界的規則。這使我們能夠將道路上捕獲的圖像和視訊轉化為特定任務，從而實現更智慧、適應性強和安全的自動駕駛技術。

Overall, our strategy is to divest the most powerful foundation models to solve real-world problems, and we continue to invest in this area to ensure our leadership position. Thank you.

總體而言，我們的策略是剝離最強大的基礎模型來解決現實世界的問題，並且我們繼續在該領域進行投資以確保我們的領導地位。謝謝。

Thank you. And ladies and gentlemen, at this time, we will conclude the question-and-answer session and conclude Baidu's Fourth Quarter and Fiscal Year 2023 Earnings Conference Call. We do thank you for attending today's presentation. You may now disconnect your lines.

謝謝。女士們、先生們，此時，我們將結束問答環節，結束百度第四季及2023財年獲利電話會議。我們非常感謝您參加今天的演講。現在您可以斷開線路。