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Operator: Hello and thank you for standing by for Baidu’s Second Quarter 2023 Earnings Conference Call. At this time, all participants are in a listen-only mode. After management’s prepared remarks, there will be a question-and-answer session. Today’s conference is being recorded. If you have any objections you may disconnect at this time. I would now like to turn the meeting over to host for today’s conference, Juan Lin, Baidu’s, Director of Investor Relations.

Juan Lin: Hello, everyone, and welcome to Baidu’s second quarter 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 call today, we have Robin Li, our Co-Founder and CEO; Rong Luo, our CFO; Dou Shen, our EVP, in charge of Baidu, AI, cloud Group, ACG; Zhenyu Li, our SVP, in-charge of Baidu’s Intelligent Driving. After our prepared remarks, we will hold a Q&A session. Please note that the discussion today will contain forward-looking statements made under the Safe-Harbor provisions of the U.S. 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 for detailed discussions of these risks and uncertainties, please refer to our latest Annual Report and other documents filed with the SEC and Hong-Kong Stock Exchange.

Baidu, does not undertake any obligation to update any forward-looking statements except as required under applicable law. Our earnings press release and this call includes discussions of certain unaudited non-GAAP financial measures. Our press release contains a reconciliation of the unaudited non-GAAP measures to the unaudited most directly comparable GAAP measures and is available on our IR website at ir.baidu.com. As a reminder, this conference is being recorded. In addition, a webcast of this conference call will be available on Baidu’s IR website. I will now turn the call over to our CEO, Robin.

Robin Li: Hello, everyone. I’m pleased with our financial performance in the second quarter. Revenue from online marketing increased by 15% year-over-year, reflecting improvement in advertiser segment. In Q2, non-GAAP operating profit for mobile ecosystem continued to strengthen and AI cloud, once again, delivered positive operating profit. At the same time, we are facing tremendous opportunities in foundation models or more broadly AGI. Today, I would like to share an update on our ongoing business transformation by utilizing ERNIE and ERNIE Bot as well as our achievements in the field. After that, I’ll briefly go over the operational highlights for each of our business. Over the past few months, foundation models have captured the imagination of people and businesses around the world.

It is becoming increasingly clear that foundation models will fundamentally transform work across the industry, boosting overall productivity and accelerate the wider democratization of AI innovation. Right now, we are in the midst of the rolling period. This is due to the fact that the hard work we poured into generative AI over the years is now beginning to bear fruit. This pivotal and transformative opportunity is setting the stage for Baidu’s future success and we couldn’t be more excited about it. On product and service front, we’re using ERNIE and ERNIE Bot to improve, review and create new offerings. On the product side, we are reinventing our products building AI native apps. Providing search, AI has played an important role for many years in driving innovation and improving user experience, resulting in a consistent increase in the percentage of third quarter satisfied by one-shot search results.

It means the first search results displayed on the result page that can provide a satisfactory response to a search query. We’re using ERNIE Bot to enhance search experience, making Baidu search capable of answering complex questions that were previously unanswerable. For example, please prompt a marketing campaign proposal for a smartphone launch event, or what kind of new energy vehicles would be suitable for a family six with a budget of RMB300,000. ERNIE Bot also enables Baidu’s search to assist users with more personalized and in-depth research on a topic or project. The feedback from users who have tested these new features has been positive. Another example of product innovation is Baidu Wenku, where many users search for articles, papers, books or campaigns to create documents of wide range of topics in many formats.

We’re currently beta testing an AI assistant feature that can generate a customized content for users based on their request. User engagement and retention among Baidu Wenku’s testing users for such feature solve significant improvement. For example, users have doubled their time spent on Wenku after trying out the AI assistant feature, and they are more likely to become paying users. Currently, Wenku has over 100 million monthly active users, and we believe such an intelligent feature will help Wenku attract even more users and convert non-paying users to paying users once it is rolled-out on a larger scale. Generative AI offers right horizons for our online marketing business and we are actively using the technology to build and review our marketing products.

Actually, our online marketing business has relied on AI for years to provide more value to advertisers. Last quarter, we shared on our progress on using the AIGC to automate ad creation in text format, which lead to an increase in conversion rate. This quarter, we further enable advertisers to use AIGC to generate image and video app with natural language. In Q2, we further improved our monetization system by yielding generative AI to broaden ad campaign keyword to user search queries, driving better monetization for advertisers. For example, an online professional education company’s ad conversion increased by about 16% in August after using these new features. We are consistently enhancing our system are using generative AI and we expect to introduce more and more new features in the coming months.

Additionally, we have been leveraging generative AI to enhance our auction system, so that it can better match ads to search queries and search intent. Such improvement help increase Baidu search ECPM in Q2 and contributed to the year-over-year growth in online marketing revenue in the quarter. We are also in active conversations with advertisers to get their input on how to further make our marketing products work best for them. Meanwhile, we will continue to leverage ERNIE and ERNIE Bot to help advertisers create sophisticated ad campaigns and improve ROI on Baidu. One other initiative, I’d like to mention here is that, internally, we introduced an AI assistant within inflow Baidu’s self-developed enterprise communication and collaboration platform.

The AI assistant automates various workflows such as summarizing meeting notes, chat history and workplace content, drafting documents, generating draft, facilitating knowledge Q&A and completing tasks such as creating meetings invite, applying for vacation days and conducting data analysis using natural language. This assistance helps our employees work more productively. We plan to open up the intelligent features of info flow to our customers in the future. Alongside our own products, we are empowering cloud customers to build their transformative products and services using ERNIE Bot. In Q2, the number of corporates connecting to ERNIE Bot continue to grow. Foundation models, large language models and generative AI are expanding our total addressable market, attracting new customers while also increasing sales to our existing customers.

We are also using ERNIE and ERNIE Bot to help customers in various industries, address real-world challenges with unprecedented effectively and competence. This further strengthens the capabilities of ERNIE and ERNIE Bot, empowering them to take on more significant role in solving industry-specific issues. For example, in the software development industry, we launched Baidu Comet, an AI coding assistant to the public in June. By the Comet eight people in coding and can be used in multiple programming languages. It has now been widely adopted Baidu’s own R&D team. Who have reported a meaningful improvement in their productivity after using Comet. As of today, more than 100 organizations have tested by the Comet, and some of them have already decided to purchase Baidu Comet to boost productivity and coding.

In the health care industry, we are solidifying our presence by utilizing industry expertise and sales network developed through our collaboration with leading hospitals in China. Chongqing limited a traditional Chinese medicine clinic chain is using our early based model, developed for the health care industry to support doctors and their patient care. Our AI assistant helps doctors write notes for patients analyze medical images and make informed clinical decisions among other tasks. It also helps patients find the most suitable doctor and department and provide pre-consultation service online. Furthermore, we’ve developed tools for model training and fine-training, data processing, labeling and more. These tools help to lower the threshold and cost for enterprises to use foundation models on Baidu and support them to train and operate their purpose-built models efficiently.

Additionally, Baidu AI cloud stands out as our AI optimized cloud infrastructure makes us a top performing platform for training and serving foundation models, including large lending model. This is why more and more enterprises are upping their digital spend on our cloud infrastructure to capture the new AI opportunities. This is particularly obvious among Internet and tech companies as they are early adopters of Gen AI and foundation models. Shifting our focus to technology, as Baidu we maintained an unwavering commitment to improve earnings. During Q2, we unveiled earning 3.5. Our latest state-of-the-art foundation model powered by PaddlePaddle. Notably, PaddlePaddle enhancements enabled our self-device four-layer AI architecture to operate more seamlessly than ever before.

Significantly improve the frameworks compatibility with ERNIE and demonstrating engineering excellence. As a result, compared to ERNIE 3.0% in March, ERNIE 3.5 past triple training throughput and its quest per second or QPS for inference has increased by more than 30 times. Additionally, I’m proud to note that IDC recently reported that ERNIE 3.5 surpassed peers in many areas such as algorithm, industry coverage, developer tools and ecosystem. As compared to ERNIE 3.0, 3.5 is capable of producing safer, more responsible and more creative responses, making significant improvements in question answering, reasoning and coding. ERNIE 3.5 is now powering ERNIE Bot, with plugging to expand its functionality to cover real-time and precise information, long taxed summary, data analysis and virilization, text-to-video conversion and facilitate pilot dialogues that include images.

We are committed to enriching our ecosystem by adding more high-quality plugging in particular from third-parties to contribute to the advancement of China’s foundation model. On the ecosystem front, we are determined to make ERNIE the most popular foundation model in China. Importantly, we believe foundation models should be able to well support problem solving capabilities for various industries. As a result, we need to work collaboratively with our partners such as enterprises and AI developers to continually build industry models and solutions. Our 8 million developers on PaddlePaddle are the anchor that we can leverage to build a community for ERNIE. To foster a vibrant ecosystem, we hosted Baidu ERNIE Cup Innovation Challenge. It attracted almost 1,000 startups to submit their ideas and prototypes, covering various fields, encompassing productivity towards developers, sales and marketing companies, entertainment companies, social platform, middleware developers, as well as applications across different industries, including education, health care, finance, et cetera.

We have also launched a venture fund of RMB1 billion to support start-ups in divesting all kinds of AI native applications, which will complement our organic growth. On regulation, Baidu have recently up — Baidu was recently appointed as a leader of China’s LLM Standardization Task Force at the World AI Conference. This position signifies national-level recognition and endorsement of our foundation models and AI capabilities. While we are still waiting for the green light for large scale rollout of ERNIE Bot, we have observed that Chinese government have been increasingly supportive of the development opportunity of AI and LLM. As a market leader, we believe Baidu is well capable of benefiting from the opportunity and contributing to this megatrend in China.

Now let’s have a quick look of the second quarter operating highlights for each business. Revenue from AI Cloud increased by 5% year-over-year to RMB4.5 billion in the quarter. And AI Cloud maintained positive non-GAAP operating profit. Our business has become healthier than ever laying a solid foundation for future growth. On intelligent driving, in Q2, the rights provided by Apollo Goal increased by about 150% year-over-year to around 714,000, resulting in accumulated rights exceeding RMB3.3 million, which is greater than our closest competitor by order of magnitude. This leadership in operation implies competitive advantages in data quantity and quality, that better model and greater safety ratings. In addition, Apollo Go has widened footprint in fully driverless ride-hailing services in more settings.

In mid-June, Apollo Go received a permit from Shenzhen Pingshan government to offer 40 driverless ride-hailing services to the public. And in early July, in Shanghai, we were allowed to conduct fully driverless testing on open road as well. With the expansion of the area and fleet size for fully driverless operation along with the improvement of operational efficiency, we witnessed growth not only in the total average daily orders, but also in the portion of fully driverless orders within the overall order portfolio. This highlights a promising pathway for improving the unit economics of autonomous driving. In particular, in Wuhan, where we initiated fully driverless ride-hailing services one year ago, the UE continued to improve in the past few quarters.

On the revenue side, the average daily order volume and revenue per order have surged propelling total revenue to grow. Meanwhile, the cost per kilometer per car is decreasing as well, thanks to improved operational efficiency. Finally, our mobile ecosystem, our users continue to grow with Baidu Apps, MAUs increasing by 8% year-over-year to RMB677 million in June. Also in June, videos distributed by Baidu App achieved double-digit growth year-over-year. Baidu remained a significant platform for users, who are seeking a wide range of content such as information, products and services. The revenue growth rate for online marketing accelerated in Q2 aided by strengths in wireless verticals with offline exposure, including healthcare, business services, local services and travel.

At the same time, revenue from e-commerce demonstrated strength and outperformed in the quarter. Non-GAAP operating profit for mobile ecosystems grew steadily year-over-year in the quarter. Mobile ecosystem continued to generate robust cash flow to fund our investments in AI, particularly in foundation models and generated AI. We are confident that revenue, profit and cash flow generated from our mobile ecosystem will remain strong in the future. With that, let me turn the call over to Rong to go through our financial results.

Rong Luo: Thank you, Robin. Now let me walk us through the details of our second quarter financial results. Total revenue was RMB34.1 billion, increasing 15%, one-five year-over-year, revenue from Baidu Core was RMB26.4 billion, increasing 14%, one-four year-over-year. Baidu Core’s online marketing revenue was RMB19.6 billion, increasing 15%, one-five year-over-year. Baidu Core’s non-online marketing revenue was RMB6.8 billion, up 12% year-over-year. In Q2, AI cloud revenue increased by 5% year-over-year to RMB4.5 billion. Revenue for IT was RMB7.8 billion, increasing 17%, one-seven year-over-year. Cost of revenue was RMB16.2 billion, increasing 7% year-over-year. Baidu Core’s cost of revenue was RMB10.6 billion, increasing 4% year-over-year.

Operating expenses were RMB12.7 billion, increasing 14% one-four year-over-year, primarily due to an increase in channel spending promotional marketing expenses, server depreciation expenses and cloud-related expenses, which supports ERNIE Bot research improves and partially offset by a decrease in personnel-related expenses. Baidu cost operating expenses were RMB11.3 billion, increasing 15%, one-five year-over-year. Baidu Core SG&A expenses were RMB5.3 billion, increasing 34% year-over-year. SG&A accounting for 20% helps Baidu Core revenue in the quarter compared to 17%, one-seven same period last year. Baidu Core R&D expenses was RMB5.9 billion, increasing 2% year-over-year R&D, accounting for 23% of Baidu Core revenue in the quarter and decreased from 25% the same period last year.

Operating income was RMB5.2 billion, Baidu Core’s operating incomes RMB4.6 billion and Baidu Core’s operating margin was 17%, one-seven. Non-GAAP operating income was RMB7.3 billion, non-GAAP Baidu Core’s operating income was RMB6.5 billion and non-GAAP Baidu Core operating margin was 25%. Total other income net towards RMB1.4 billion compared to RMB151 million in the same-period last year, primarily due to the increase in net foreign exchange gain and net interest income, partially offset by the increase of fair value loss from long-term investments. The income tax expenses was RMB1.3 billion, compared to RMB25 million in the same period last year. The lower level for income tax expenses in the second quarter of 2022 is primarily due to the reversal of certain tax expenses based on the 2021 tax return.

Apart from the reversals, the net reason for the increase of income tax expenses is the increase in profit before-tax year-over-year. Net income attributable to Baidu was RMB5.2 billion and diluted earnings per ADS was RMB14.17. Net income attributable to Baidu Core was RMB5 billion and net margin for Baidu Core was 19%, one-nine. Non-GAAP net income attributable to Baidu was RMB8 billion, non-GAAP diluted earnings per ADS was RMB22.5. Non-GAAP net income attributable to Baidu Core was RMB7.7 billion. Non-GAAP net margin for Baidu Core was 29%. As of June 30, 2023, cash, cash equivalents, restricted cash and short-term investments were RMB201.5 billion in cash, cash equivalents, restricted cash and short-term investments excluding iQIYI, RMB196.9 billion.

Free cash flow was RMB7.9 billion and free cash flow excluding iQIYI was RMB7.1 billion. Baidu Core had approximately 35 solid employees as of June 30, 2023. With that, operator let’s now open the call to questions.

Operator: Thank you. We will now begin the question-and-answer session. [Operator Instructions] The first question today comes from Alicia Yap with Citigroup. Please go ahead.

Alicia Yap: Hi, thank you. Good evening, management, thanks for taking my questions. Congrats on the solid results. So can management provide update on the current state of the advertising industry, including how online and offline platforms are recovering? Can management also share about the pace of recovery for key industry and which one have stronger seasonality? And then in addition, can management also discuss the main drivers for the growth in this industry? And finally, what are the medium-term growth targets for at as we are now already behind the pandemic and with the current latest macro situation? Thank you.

Robin Li: Hi, Alicia, this is Robin. Let me answer your question. Our online marketing revenue increased by 15% year-over-year last quarter. I think a number of travelers contributed to this growth. On the vertical side as we are coming out of the pandemic, many offline verticals like healthcare, business services, local services and travel continue to outperform. For example, healthcare, we saw solid year-over-year growth in both search queries and ECPM, which leads to revenue trends. We think this momentum continue. Offline sector contributes to a sizable amount of total online marketing revenue to Baidu. And in the meantime, e-commerce continue to grow in Q2 and remain top revenue contributors. For market like e-commerce, it’s highly competitive.

So more and more merchants, they come to realize the value of Baidu, and they come to us to acquire new users and buyers and also invite their existing buyers to come back and buy more. For the second-half of the year, we should continue to see a pretty clear recovery trend for our online marketing business. Also remember, search remains the most effective form of performance-based ad. This is because users approach search with a clear intent and search ads allows us to connect this intention directly with the most relevant product service offerings. In fact, the ECPM for our search outgrow other ad formats in the quarter, reflecting the effectiveness. Due to the relatively high comp base in Q3, the growth rate might not be as high as Q2, but it should well outperform China’s GDP growth.

Additionally, we have more immersive video features. More and more users are watching the short videos on Baidu. Short videos distributed through the Baidu App, again grew by double-digit in Q2. As a result, revenue from short videos continue to grow quite well, contributing meaningfully to the overall online marketing revenue growth. Looking into the mid- to long term, I believe both user traffic growth and monetization upgrades are important growth drivers for our online marketing business. And on the user side, I talked about our MAU, it grew by 8% year-over-year in Baidu App growth rate in June — in the month of June. If we look at search, we are renovating the Baidu Search step-by-step using ERNIE Bot. We believe it will provide users with innovative and intuitive experience, which will help our mobile ecosystem gain traffic and increase user time spend.

And on the monetization side, we’ve been leveraging AI to improve ad targeting capabilities and our bidding system for a number of years. And now with ERNIE and ERNIE Bot, we are further upgrading the game. I mentioned earlier that we have made some major improvement in advertising technology by using LLM and Generative AI. Along for more innovative and personalized ads, I believe there are lots of room for growth in this aspect, and I look forward to further breakthroughs. Such improvement in monetization technology have started to contribute to revenue and ECPM growth starting from this quarter in Q3. Thank you.

Operator: The next question comes from Gary Yu with Morgan Stanley. Please go ahead.

Gary Yu: Hi, thank you for the opportunity to ask question and congrats on the solid set of results. I have a couple of questions related to AI product and monetization. First is, can management share some insight on how users have responded to the integration of ERNIE Bot in multiple products? Any new development of features that have come up with the ERNIE Bot offerings [Technical Difficulty] help with market growth in China Internet and specifically in the mobile Internet sector? And also, lastly, I would like to know more about the monetization [Technical Difficulty] we play a role in your advertising business? And also [Technical Difficulty] update in key industries and use cases related to B side. Can you provide additional information on the business model and also potential revenue specifically, I would like to gain a better understanding on financial impact on cloud performance.

Robin Li: Hi, Gary, let me answer the consumer-facing products part of your question, and I’ll have Dou talk about the enterprise side, especially cloud business. I think it’s clear we are in a paradigm shift in our business with our early commitment to AI, we saw this time coming. We are reinventing our consumer-facing products with an AI-native mindset. As I mentioned in my opening remarks, we are rebuilding our search experience. Users who are testing our ERNIE Bot enabled Baidu search and Baidu app tend to ask more questions that were not frequently searched in the past and we tend to have multi-round conversation and interaction. This is quite different from the user behavior for traditional search. Therefore, it’s an incremental business for us.

We are using generative AI to construct direct answers to user queries. This typically creates better and easier to understand answers than experts from existing web pages. We see increases in click-through rate and user retention rate for these kind of changes. We also launched the testing version of ERNIE Bot App, a step along app that is built upon our latest generative AI and LLM. And it aims to serve users as a personal assistant. We see ERNIE Bot a potential new traffic gateway that can connect users to various applications, including Baidu and other third-party applications, to address users’ needs. We also launched ERNIE Bot plug-ins like search, like chat [Indiscernible] e-card, et cetera. Developers will soon be able to submit their application as ERNIE Bot plug-in.

For Baidu Core is the AI assistant feature on average user time spend more than doubled and the seven-day retention rate has increased by almost 10%. With the AI assistant, I will not be surprised that we can convert more users into paying accounts and charge-off premium for the new AI function in the future. Overall, we are highly encouraged by user feedback. This is just the beginning for us to reconstruct all the products and businesses with LLM and Generative AI. Very importantly, we have also saying promising opportunities to lift the monetization capability by rebuilding our advertising system. As I mentioned in the prepared remarks, ERNIE and ERNIE Bot allow us to continue improving our targeting and a bidding system. All in all, I believe that generative AI will help us gain market share of many products and ultimately become a new growth driver for our online marketing business.

Dou Shen: Gary, for your second part, right? So for the impact on our cloud business, I would first mention that the beauty of the foundation model and Generative AI is that it can help organizations in many industry to increase productivity and efficiency. We see more and more enterprises willing to adopt such latest AI technologies and that’s why we will say the new technology is increasing our time. Specifically, ERNIE and ERNIE Bot has been helping our customers from different industries to handle their business challenges more effectively, ranging from like software, Internet health care, education, brand finance and even to the public sector. So they used ERNIE and ERNIE Bot to train models, to build applications and to improve solutions for efficiency gains, such as improving their customer service producing different kinds of content, ready coat, providing knowledge searches within their organizations as well as increasing their sales and marketing efforts.

As to the business models you just asked, I think it’s still at its very early stage, and it’s evolving. Though we have our preference, but we are pretty open and would like to take any effort to speed up the growth of generative AI. So in addition to providing AI computing infrastructure to our customers, we also consider charging customers for the usage of ERNIE and ERNIE Bot or using our AI applications such as [Indiscernible], Robin just mentioned. And also, we can charge our customers for retraining or operating their own models on our platform or we can deploy the foundation models to our customers’ private cloud on the project basis. So we expect the revenue generated from such new opportunity to be gradual, but we build the long-term potential is [Indiscernible].

So we’ll continue to invest in ERNIE and ERNIE bot to serve our customers well for the long-term. That’s it, Gary.

Operator: The next question comes from Lincoln Kong with Goldman Sachs. Please go ahead.

Lincoln Kong: Thank you, management for taking the question and congrats on the [Technical Difficulty] quarter. So my question is about the cloud business. So could management help us understand sort of the main reason for the revenue slowdown for cloud this quarter? And when do we expect the revenue to pick up accelerate again? When we’re looking ahead into the second-half of our entire year of 2023. How is the revenue growth trajectory expected to play out? And what factors will be driving that? And also on the profitability side, I’m also curious whether this profit breakeven on a non-GAAP operating level is sustainable? And what’s the current trend for the AI cloud profitability?

Dou Shen: Okay. Thank you for the question. I’ll take it. So cloud revenue grew up 5% year-over-year in Q2, and we continue to generate profit on the non-GAAP operating level. It means that our business is becoming healthier, you know, laying a solid foundation for sustainable growth in the future. The growth rate was mainly dragged by government-related projects, in which early took a longer time to recover after the pandemic. But many enterprise related products in the key verticals like manufacturing, utilities and internet service has demonstrated quite solid growth in Q2. As I just mentioned before, we see strong interest from existing and new customers in Generative AI, so while some of them directly leverage ERNIE or ERNIE Bot to enhance their products to improve their operational efficiency.

So some of them actually choose our AI infrastructure as the foundation for their models and applications though it may take a little while to see significant revenue contribution, but this opens us a very new space for our cloud business where we’re already in a leading position. So on the profit side, we believe we can keep generating operating profit from AI Cloud as we did in the previous quarters. So this indicates that actually our business is becoming increasingly healthy. But we are going to keep standardize our AI solutions, that can effectively address AI critical pinpoints and then replicate them from one project to another, which will further grow the margin and profit.

Operator: The next question comes from Kenneth Fong with Credit Suisse. Please go ahead.

Kenneth Fong: Hi, good evening management. Thank you for taking my questions and congrats on the solid quarter results. I have a question regarding the generative AI, regarding the recent introduced interim measures to regulate generative AI service by the government. Could you provide insight into whether this suggests an imminent authorization of the large language models. Additionally, do you have a projected time line for the rollout of the applications utilizing these models? Thank you.

Robin Li: Thank you for your question, Ken. We’re seeing the government continue to support for tech innovation, including AI and foundation models. I think a good sign of this is that the new guidelines and specifications that came out in mid-July about how to use generating AI technology and related services in China. This is new version, and this version went effective, I think, in August 15, compared to the previous version, this version you can probably tell, it’s more of co-innovation than regulation. We are still waiting for the green light for large-scale rollout of ERNIE Bot. For its use in the consumer-facing acts. But as I said before, the government has increasingly recognized ERNIE and ERNIE Bot, which we believe provides a good foundation for the event release of ERNIE Bot on a large scale.

Generative AI is pretty new and it’s understandable that people might have concerns about things like user privacy, IP protection, AI ethics, so there should be certain regulatory requirements in place. And Baidu, we have accumulated extensive experience in providing appropriate information to the vast amount of Internet users. And we are a leader in not only AI technology for commercial purposes, but also using the AI for good. In fact, we are working closely with the regulators and other organizations to push the divestment and a proper usage of generative AI. So we believe we are well positioned to benefit from this opportunity and contribute to this mega trend of generative AI in China. So while we don’t have an exact date for everything, but the trend is very promising, and we are quite optimistic of the future of a better regulatory environment.

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

Wei Xiong: Hey, good evening management. Thank you for taking my questions and congrats on the solid results. My question is also related to the foundation model. How can we assess Baidu’s foundation model’s performance comparing to other Chinese peers? And also related to that, when we think about industry-specific models versus foundation models, how the balance between these two will shape up the broader AI landscape in the future? And now we have more companies offering or focusing on models tailored to specific industries. So how does management perceive the landscape in terms of opportunities and competition. So what are our competitive edges? Thank you.

Robin Li: These are very good questions. When it comes to foundation model in China, ERNIE 3.5 clearly stands out people have witnessed the fast iteration and improvement over the past five, six months. Our unique full-stack AI capabilities differentiate us from our competitors and give us an edge in the market. As mentioned in my prepared remarks, an IDC report recently published or named ERNIE 3.5 as a leader across various assets. Like many other technologies, foundation model, speed of innovation depends on the application that uses model. Baidu is an AI company with a strong portfolio of Internet products, these products are all being reviewed and reconstructed with ERNIE Bot, therefore, drive the innovation of ERNIE into the right direction.

In our work, we know what kind of problem to solve. And I think many other peers don’t really know they just open domain testing sets to evaluate the effectiveness of their models. We also have tens of thousands of cloud customers testing our ERNIE Bot. They provide valuable feedbacks that propel the improvement to. As for the industry-specific models you mentioned, they should be built upon the most powerful foundation model. I think that — with time, foundation models are rapidly evolve given its strong capabilities to learn new subjects and gain industry insights. And the stand-alone industry-specific models will have a hard time to keep up with the pace of innovation. In fact, since ERNIE 3.5 became available, an increasing number of customers have told us that ERNIE 3.5 is visibly more advanced than ERNIE 3.0 and it has helped them solve a growing number of pain points.

And as you can imagine, we are working towards ERNIE 4.0 and should launch it by the end of the year. I believe that ultimately, only a select few companies will reach this level of advancement for foundation models and Baidu will be one of them. During this transitional period, we are focused on multiple initiatives to drive the adoption of foundation model. We’re working hard to build early power applications and solutions for different industries and the scenarios Baidu Comet exception example. And with the upgrade to ERNIE 3.5, we are swiftly rolling out to empower enterprises to create industry-specific models and applications that tackle their own challenges. Also, we offer mass platform, which includes not only ERNIE, but also a variety of models.

This allows businesses to easily view, fine tune and operate their own models using their own data. We provide a set of valuable tools on our platform, enabling our customers to easily enhance their model, training and application development. Of course, enterprises can directly access ERNIE’s capabilities through API to enhance their businesses. Recognizing that in the early stages, enterprises prioritize security. So we do provide the flexibility of using our foundation model services on both public and private cloud. Our self-developed four-layer AI architecture is our core competitive advantage, because we deliver a better model performance when we serve our customers as shown in the testing phase over the past few months. Our strength is in model training efficiency and cost effectiveness in turn attract more enterprises to partner with us.

So we gain more and more industry know-how and insight and building a reinforcing positive cycle to further improve ERNIE. Our ultimate goal is to cultivate an AI-native ecosystem centered around ERNIE. We believe that the true power of foundation model lies in driving a wide array of high-quality AI native applications, much like an operating system. Some of the applications are built by us, while others were built by, I would say, most will be built by our ecosystem partner to address industry-specific challenges. To enhance this ecosystem, we’re happy to invest in other companies to complement our organic growth. Just as I mentioned in the prepared remarks, we hosted Baidu ERNIE Cup Innovation Challenge and large venture fund to support startups in developing all kind of AI native applications.

To sum up, we will continue to improve ERNIE, means ERNIE easy to use and help enterprises in any industry to not only retain or fine tune models on top of ERNIE, but more importantly, leverage ERNIE and ERNIE Bot to develop their own application. We aim to make ERNIE the preferred choice among AI developers, so that more and more applications will be built upon ERNIE and making our ecosystem vibrant. Thank you.

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

Miranda Zhuang: Thank you. Good evening, management. Thanks for taking my question. So lately, open source AI models have attracting significant market attention. So can management provide your insights into Baidu’s perspectives on this front and the strategy regarding the open source versus the closed AI models? Thanks.

Dou Shen: Thank you, Miranda. This is a very interesting question. And I believe there are quite different views on this. I think both open source and closed source foundation models will coexist for a while. In fact, actually, we have already seen many models trained on top of the open-source foundation models and powering tons of applications even today on our cloud platform. But it’s really tough actually for our open source foundation models to keep evolving and getting better due to the lack of effective feedback loops, which play a super important role in improving the foundation models. And additionally, building and upgrading foundation models can be very expensive. So it is really important to build a durable business model to fund the sustainable improvement of the foundation models, so that they can finally provide long-term value to the market.

So for us it’s our priority that ERNIE keeps evolving quickly and remains the market leader, which can then attract more and more customers to use our platform to create innovative apps and improve their business. With their feedback from the real word scenario, we can further improve our foundation models. Looking ahead, I believe that there will be a limited supply of advanced foundation models, whether open source or closed source or even industry-specific available in the market. So like we just talked to me, as the industry progresses and enterprises will need advanced models to develop more sophisticated applications. But ERNIE, we will be one of the few foundation models that can satisfy those evolving demands in the long run.

Operator: The next question comes from Alex Yao with JPMorgan. Please go ahead.

Alex Yao: Thank you, management for taking the question and congrats on the strong quarter. I have a couple of questions on the margin outlook. Considering the opportunity of AIGC and the large language models. How should we think about the investment trajectory for the second-half this year? Additionally, more — once we start large-scale rollouts, what direct cost will be incurred, how should we compare the margin of ERNIE Bot or large language model related to products — related products than the existing business, I search, et cetera? More broadly, could management also provide directional color on the trend of Baidu Core margins when we look into the second-half of this year after the significant cost reduction, efficiency improvement incremented last year, what will be the key drivers of the profit moving forward? Thank you.

Rong Luo: Thank you, Alex. Let me take your questions. This is Julius. I think previously, Rob has already talked about a large of our opportunities of the ERNIE and ERNIE Bot. So in the first place, I would like to reiterate that we are highly committed to the long-term investments in these promise areas. And to support the fast upgrade of [earnings] (ph), and we have invested in compensation infrastructures. If you look into our cash flow statement, you probably can see that the Baidu cost CapEx in Q2 have increased over last year. The increase is mainly due to the hardware purchase to support the training and iterations of all AI campaigns such as ERNIE and ERNIE Bot. But the impact on the income statement side, which is quite manageable, that’s because of such hardware depreciations in general will spread over the next few years and the impact on the near-term profitability is not substantial.

The investment is expected to continue and the magnitude of the future investments will be highly correlated to the pace of the actual business expansions rather than only supporting the model training. Which means that in the near future, the spending will be sponsored by the incremental revenue, which is generated from our ERNIE Bots and formulates our positive virtual circles. And regarding to the margin for the financial model and related products, I believe it’s a little bit earlier to discuss at the current stage as the business model is still evolving. But as Rob has mentioned earlier, in part by the earnings, the search advertising could become more customized and which will result in increased ROI for advertisers. The additions for cloud services, as Dou has just talked about that, the [Indiscernible] and the financial models will import various industry and enhance the efficiencies across different industries.

So from a long-term perspective, we believe that the customers will be increasingly motivated to leverage our services to enhance their efficiencies and increasing our pricing power and resulting in higher margins as compared to the current cloud business. If we go into the second-half of this year for mobile ecosystem, we will continue to serve as cash cost for the group in the long run. Our goal for mobile systems is to consistently achieve high margins. For the AI cloud side, we aim to achieve the profitability on a non-GAAP OP level and improve margins over time, for the intelligent driving, while we firmly believe that there’s a huge long-term opportunities, we will continue to make sure we invest and measure pace. As a whole, our main focus is on developing a sustainable growth strategy for each businesses, which prioritize the long-term thinking.

In addition, we plan to invest in ERNIE and ERNIE Bot to take advantage of the huge opportunities presented by the foundation models at [Indiscernible]. Thank you, Alex.

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

Thomas Chong: Good evening. Thanks management for taking my questions. And congratulations I have two questions. The first is about our Robo taxi business. Management mentioned that the unit economics in some cities are improving. Could management share the logic and the efforts taken behind it. What’s your plan in terms of the city expansion and the volume market for fully drive operations in the upcoming quarters. In addition, when can we expect the Altice 6 vehicle to be launched, what’s the projected size of the vehicle fit for this year? And how could it potentially impact the cost? My second question is on Auto Solutions, which vehicle models will hit the role in the later half of this year and next year? And how should we size up the financial impact on the books?

Robin Li: Thanks for the attention. This is Jan. I will start from the low tax section. Our autonomous train service is rapidly gaining traction in major cities, providing valuable data that to the development of our drivers technology. This data is instrumenting in [Indiscernible] facility, efficiency and overall experience our operations. As a result, we have guided a strong part from both customers and regulators, enabling us to expand into new locations and significant increase of rates. This positive feedback to our large operations also drove the improvement our model and the improved model drove the expansion of our operations, providing us to the forefront of the global leading home autonomous driving technology. On the logic behind the improvement, here, I would like to take Wuhan’s operation as example.

We have continued to scale up service in Wuhan in the past year. If you compare with the situation 1 year ago, you may notice that firstly, our fully [Indiscernible] have expanded significantly growing from five week [Indiscernible] one year ago to almost 200 in August this year. Secondly, the operation area for free service has expanded by around fifteen-fold in Wuhan. Meanwhile, the operation also has been further expanded, covering both [Indiscernible] and morning and the evening, as well as later net operation. Certainly, [Indiscernible] is now selling more passengers to tear becoming one of the largest areas of providing fully travelling service in the world. And firstly, in terms of the order, the proportion of fee rate orders to all our operations has increased from 10% in last August to 55% in July this year.

All the progress mentioned about contribute to the improvement of OUE. Looking ahead, we will continue to focus on the operation intensities and average regions like Beijing and Wuhan to further expand the fleet side and operation areas of driverless operations, and thus gladly improved the unit economically. Next year, we aim to enter into [Indiscernible] tool to conduct full [Indiscernible] ride hailing services and expanded the skill of fleet drives commercial operations. [Indiscernible] the time line for market production is proceeding as planned. It brings us a significant cost advantage with mass production costs lowered by 50, compared with the previous generation. Though it will be great to come the majority in our operation recovery, preparing the unit economics closer to profitability point.

Last, on auto solutions business, currently providing assistant driving product to note [Indiscernible] standards in terms of generalization and safety, failing to testified consumer demand for convince and efficiency producing this the [Indiscernible] competition in China’s EV market has led to a general decline in the profitability within the automotive sector. And OEMs have been showing softened demand for integrating drilling and leading more towards cost cutting measures to the cumulated sales. Which has affected and is also expected to our [Indiscernible] auto solutions in the short-term. However, we believe that our market opportunity ahead in the long run driven by the consumer demand for intelligent driving. We plan to launch our safety navigation pilot product, Apollo safety driving market at our place later this year.

As we look ahead, we believe the change in the auto industry is hiding towards intelligent driving with exciting opportunities in the future, and we will capitalize on this change with cutting edge technologies and sensible business model. Thank you.

Operator: This concludes our question-and-answer session and does conclude our conference for today. Thank you for participating. You may now disconnect.