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 your host for today's conference, Juan Lin, Baidu's Director of Investor Relations. Hello, everyone, and welcome to Baidu's Third 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, and Dou Shen, our EVP, in charge of Baidu AI Cloud Group, 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 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 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 non-GAAP financial measures. Our press release contains a reconciliation of certain non-GAAP measures to the most directly comparable GAAP measures and is available on our IR website at ir.baidu.com. As a reminder, this conference is being recorded. In addition, a webcast of this conference call will be available on Baidu's IR website. I will now turn the call over to our CEO, Robin. Hello, everyone. Baidu Core delivered solid revenues, profits, and cash flow in Q3, despite navigating in a challenging macroclimate for both our online marketing business and AI Cloud business. I'm proud that our team managed to strengthen operational efficiency and maintain stable margins amid a full-scale reinvention of our product portfolio with ERNIE and ERNIE Bot. Today, I would like to share an update on the new opportunities that ERNIE and ERNIE Bot have opened up for us. After that, I'll discuss some key highlights of each of our businesses. Presently, we are in the midst of a broad-based platform shift, driven by generative AI and foundation models that is set to revolutionize every industry. On August 31st, we received the approval to deploy ERNIE Bot on a large scale and open ERNIE API to enterprise customers. Since then, we've witnessed a significant increase in queries handled by ERNIE Bot and through ERNIE API. Moreover, we've received valuable feedback from these users and customers, enabling us to further refine our model's performance. At Baidu World in October, we showcased our progress in ERNIE Bot and AI-native products. During that event, we introduced ERNIE 4.0 or EB4, our most advanced foundation model. We believe that EB4 is a GPT-4 level model, displaying human-level performance in understanding, content generation, complex reason, reasoning, and memory retention. These capabilities are crucial for developing AI-native applications and solutions. We are pleased to launch EB4 earlier than our expectations. It resulted from our unique end-to-end four-layer AI infrastructure, which helped enhance efficiency in model training. The input and feedback from our users and customers also played a big role. In products, as I said in the past, we continue to use ERNIE to reinvent our entire portfolio and introduce an AI-native experience. On the customer front, ERNIE Bot enables Baidu's search by generating direct answers to search queries, complementing traditional search. In the quarter, we initiated tests on our new features that recommend newsfeed-like information together with the generated search results, and enable multi-round conversations to encourage further user expression. Our initial tests have received promising feedback. We believe these features will help deepen user engagement and prolong time spent, unleashing new monetization opportunities. In particular, they benefit verticals like healthcare, education, travel, legal, and auto, in which advertisers are willing to invest heavily in customer acquisition and re-engagement. ERNIE Bot, our new AI-native product, serves as a versatile multi-round conversational AI assistant on both desktop and mobile. Given the exceptional performance of our large language model, we are confident in monetizing our services. Starting from November 1st, EB4 was open to the public through ERNIE Bot at a subscription fee of about $8 per month. This marks us as the first company in China to implement user charges, distinguish us from other models in the market. Our primary focus is to encourage seamless collaboration between users and AI copilots, which we believe is a key trend in the new era. For example, with an AI copilot, Baidu Wenku has transformed into a one-stop shop for various document creation needs. We have already seen an increase in the paying user count, a trend that we expect to continue in the coming quarters. On the enterprise-facing product front, we recently introduced the GBI, Generative Business Intelligence, with ERNIE Bot. GBI simplifies data analysis using natural language interaction, facilitating faster decision-making for business operation. The introduction of GBI was prompted by this recognition that customers across various industries have the need for AI copilots to help them analyze data more efficiently. During our last earnings call, we also discussed how we use ERNIE Bot to create Baidu Comate, our AI coding assistant, and InfoFlow, our enterprise communication and collaboration platform. These products focus on boosting productivity and efficiency gains, and each of them presents upsell opportunities for our cloud customers. In fact, an increasing number of our cloud customers in China's traditional industries and public sector have used the trial version and shown interest in this product and features. Additionally, these products and features also allow us to acquire new customers across an even wider array of industries. In terms of ecosystem, we empower enterprises to leverage ERNIE through API to create their own AI-native applications and solutions that will drive the development of generative AI and LLM. As more and more AI-native applications built on top of ERNIE become successful, whether developed by us or by our customers, ERNIE will likewise be successful. Now, over 10,000 enterprises are actively using ERNIE through API on a monthly basis. This number has been growing quickly since we received the regulatory green light at the end of August. Currently, ERNIE is handling tens of millions of queries every day. Right now, a large and rising number of these queries come from the Baidu family of products, as we have been pioneers in building AI-native products and have put a lot of effort into reinventing our offerings. In the first half of November, the number of daily external queries has increased by over 50% compared to the same period in October. As we are actively assisting our cloud customers in creating AI-native applications, we believe there will be a continuous and significant rise in external queries in the future. We're also actively attracting developers to connect their information and services to ERNIE Bot through plugins. With plugins, Ernie can help people with more and more tasks, unlocking a wide range of possible use cases. As of today, hundreds of plugins have already been accessible to Ernie. The initial batch of third-party plugins include Ctrip.com, CITIC Press Group, China Justice Big Data Institute, New Oriental, Autoh ome, and TreeMind. In summary, during the quarter, we made significant progress in using GenAI to revolutionize product usage and transform business operations for our users and customers. We believe that this is just the beginning. In the future, we will realign resources to invest in this growth opportunity and shift away from lower priority efforts and improve efficiency for existing businesses, thus balancing investment and margins. We are excited about the possibilities for Baidu, for our users, customers, partners, and the entire ecosystem. Now, let me recap the key highlights of each of our businesses. Mobile ecosystem continued to exhibit steady growth for both user metrics and financial performance in the quarter. Baidu App MAUs increased by 5% year-over-year to 663 million in September. Search queries and content distributed by Baidu App remained resilient. In particular, videos distributed by search and feed within Baidu App both experienced a double-digit growth in third quarter. Baidu Core online marketing revenue increased by 5% year-over-year in the third quarter, consistently generating strong profit and cash flow for the group. This growth was driven by the continuous recovery in verticals such as healthcare and travel, among others. In the quarter, we continued to use Gen AI to help advertisers increase ROI and conversion on our platform. Starting from September, advertisers can engage with our new marketing platform. This platform supports natural language input and multi-round conversations, which help advertisers articulate their requirements more comprehensively, enabling us to formulate more effective campaign strategies for them. Moreover, we made ongoing enhancements to our monetization system, focusing on improving targeting capabilities and the auction system. For example, Tarena Education, an IT professional education company, achieved an increase of 23.3% in conversion rate and 22.7% boost in ROI after using this enhanced platform and capabilities. We are still in the early stages of using GenAI to help advertisers achieve higher conversions and ROIs on our platform. Our efforts will ultimately lead to significant improvement in monetization capabilities and contribute to future revenue growth. In the quarter, we also used our AI capabilities to help merchants grow their sales on Baidu. One example is how we help SMEs with live stream shopping. With ERNIE Bot, we introduced a tool that allow them to easily create their own digital human, generate live scripts and more, significantly lowering the barrier and cost for live streamers to sell merchandise on Baidu. Looking forward, we are optimistic that the growth of our online marketing revenue will continue to exceed China's GDP growth. At the same time, we will continue to test AI-native marketing products that could potentially open up more opportunities than traditional general search ads. This gives us confidence in Baidu's long-term online marketing growth prospects. Turning to AI Cloud, we continue to generate positive operating profit on a non-GAAP basis in the quarter, as we remained focused on the healthiness of our business. Gen AI and LLM have brought us a lot of opportunities, which have strengthened our competitive advantages in cloud and increased our TAM. A growing number of enterprises are using ERNIE API to develop their own AI-native applications and solutions. We are also helping customers build their own models efficiently by leveraging our unique four-layer AI infrastructure and our years of experience in building and using foundation models. LLM training is very complicated. It requires a large number of GPUs working simultaneously. Any GPU failures can impact the entire process. We have developed ways to identify and address GPU failures quickly, leading to a significant reduction in training costs. Now, about 80%, about 98% of the training time on our platform is valid, setting an industry benchmark. We also have a set of different resources, including toolkit, data sets, for enterprise customers to easily fine-tune their customized models. GenAI has helped us grow our cloud customer base. A large number of cloud customers using ERNIE API are new customers. At the same time, some of our existing cloud customers have increased their spending with us because of generative AI. AI Cloud revenues declined by 2% year-over-year in the third quarter, mainly due to the weak demand in smart transportation projects. We believe AI Cloud revenue should rebound to positive growth in the fourth quarter, driven by the increasing momentum in generative AI-related benefits. Also, since smart transportation revenue started this slowdown in Q4 of last year, we will have an easier year-over-year comp base in Q4 this year. Moving on to intelligent driving. Our target remains unchanged, which is to achieve breakeven on the regional unit economics for robotaxi operation in a couple of years before turning operationally profitable. To this end, we are strategically concentrating our resources on pivotal regions. Wuhan remains our largest operational area, and we believe it is also the largest region globally, providing autonomous ride-hailing services, currently covering a population of about 2.7 million. In the third quarter, the portion of fully driverless orders within the overall order portfolio in Wuhan exceeded 40%. That's up from 35% in Q2. We are also particularly pleased to highlight that Apollo Go's operation in Wuhan continued to expand. In late August, Apollo Go remains the first company in China to provide autonomous ride-hailing services to the general public at Wuhan Tianhe International Airport, one of the busiest airports in central China. The extended reach into the airport transfer involves longer travel distances, presenting an excellent opportunity for the future improvement of unit economics. All of this development contributed to the UE improvement, and we aim to reach regional UE breakeven in a couple of years. In Q3, Apollo Go provided 821,000 rides to the public, marking a 73% increase year-over-year, and the cumulative order volume has surpassed 4.1 million by the end of Q3. As part of our executive reshuffle program, we have recently named Dr. Wang Yunpeng as Corporate VP of Baidu, who will lead the intelligent driving group. Yunpeng has been with us since 2012 and has been responsible for autonomous driving business since 2018. I take great pride in seeing another business leader developed within Baidu. Zhenyu has taken a rotational position as CEO Assistant and Chairman of the Technology Ethics Committee. Now, let's proceed with Rong's financial performance review. Thank you, Robin. Now let me walk through the details of our third quarter financial results. Total revenue was CNY 34.4 billion, increasing 6% year-over-year. Revenue from Baidu Core was CNY 26.6 billion, increasing 5% year-over-year. Baidu Core's online marketing revenue was CNY 19.7 billion, increasing 5% year-over-year. Baidu Core's non online marketing revenue was CNY 6.9 billion, up 6% year-over-year. Revenue from iQIYI was CNY 8 billion, increasing 7% year-over-year. Cost of revenue was CNY 16.3 billion, which remained essentially unchanged compared to the same period last year. Operating expenses were CNY 11.9 billion, increasing 8% year-over-year, primarily due to an increase in channel spending, promotional market expenses, server depreciation expenses, and the server custody fees, which support ERNIE Bot research increase. Baidu Core's operating expenses were CNY 10.5 billion, increasing 10% year-over-year. Baidu Core SG&A expenses were CNY 4.8 billion, increasing 14% year-over-year. SG&A accounting for 18% of Baidu Core revenue in the quarter, compared to 17% in the same period last year. Baidu Core R&D expenses were CNY 5.6 billion, increasing 7% year-over-year, R&D accounting for 21% of Baidu Core revenue in the quarter, which maintained unchanged from the same period last year. Operating income was CNY 6.3 billion. Baidu Core's operating income was CNY 5.5 billion, and Baidu Core's operating margin was 21%. Non-GAAP operating income was CNY 7.6 billion. Non-GAAP Baidu Core operating income was CNY 6.7 billion, and non-GAAP Baidu Core operating margin was 25%. Total other income and net was CNY 1.9 billion, compared to the total other loss, net of CNY 4.8 billion for the same period last year, mainly due to the first recognition of CNY 338 million gain versus CNY 3.1 billion loss for the same period last year from fair value change in long-term investments, and second, a decrease in impairment of the long-term investments by CNY 1.4 billion. Income tax, income tax, income tax expenses was CNY 1.3 billion, increasing 41% year-over-year, primarily due to an increase in profit before tax. Net income attributable to Baidu was CNY 6.7 billion, and diluted earnings per ADS were CNY 18.22. Net income attributable to Baidu Core was CNY 6.4 billion, and net margins for Baidu Core was 24%. Non-GAAP net income attributable to Baidu was CNY 7.3 billion, and non-GAAP diluted earnings per ADS were CNY 20.40. Non-GAAP net income attributable to Baidu Core was CNY 7 billion, and non-GAAP net margin for Baidu Core was 26%. As of September 13, 2023, cash, cash equivalents, restricted cash, and short-term investments were CNY 202.7 billion, and cash, cash equivalents, restricted cash, and short-term investments, excluding IT, was CNY 197.4 billion. Free cash flow was CNY 6 billion, and free cash flow, excluding IT, was CNY 5.2 billion. Baidu Core had approximately 35,000 employees as of September 13, 2023. With that, operator, let's now open the call to questions. Thank you. We will now begin the question and answer session. If you wish to ask a question, please press star then one on your telephone and wait for your name to be announced. If you wish to cancel your request, please press star then two. Your first question comes from Alicia Yap with Citi. Please go ahead. Hello. Thank you. Good evening, Robin, Julius, and management team. Thanks for taking my questions. My questions is on advertising. So it seems like Baidu ad revenue growth is tracking slower than some of the internet peers. So besides macro, can management elaborate on any other reasons that contributed to the softer ad revenue growth? And then looking into the fourth quarter, have you seen any demand picking up? What is the e-commerce sector contribution, and how will AI change the advertising outlook? Thank you. Hi, Alicia, this is Robin. In Q3, apart from the macro weakness, online marketing revenue from e-commerce platforms was also relatively weak. Revenue from e-commerce platforms is one of our top revenue contributors. It accounted for about 10% of our total online marketing revenue. Like many other internet platform companies, we are building our own native e-commerce business. Revenue growth from our native e-commerce business is tracking very strong as we continue to improve the shopping experience on Baidu. I would like to highlight the strides we have made in our ad business through GenAI. We are basically restructuring the overall ad platform, including creative construction, ad targeting, and the bidding methods. These efforts have started to pay off, and the incremental revenue from this kind of initiatives are expected to reach the level of hundreds of millions Chinese yuan in the current quarter, which is Q4 of this year. And looking forward, we are optimistic that the growth of our online marketing revenue will continue to exceed China's GDP growth. Thank you. The next question comes from Alex Yao with JP Morgan. Please go ahead. Thank you, management, for taking my question. I have a few questions on cloud revenue. I believe Robin mentioned that, despite of moderate revenue decline in 4Q, the growth rate will return to positive territory in Q4. And then from there, should we expect the cloud revenue to further accelerate into first half of 2024? With regard to the smart city projects, are there any more projects that are still at risk? And then more importantly, as you guys start to monetize the AI capability, when will AI start contribute to the cloud revenue meaningfully? Lastly, any preliminary view on cloud revenue growth outlook for 2024? Thank you. Hi, Alex. This is Dou. Thank you for your question. So actually, as we mentioned before, so we have been focusing on improving the health of our business for a sustainable development. And as a result, you know, we have achieved a non-GAAP operating profits in the past few quarters. As Robin already mentioned, right, due to the weak demand for intelligent transportation, you know, cloud revenue experienced slight decline in Q3. So while excluding excluding a small transportation, the rest of our AI Cloud business showed a pretty solid growth. And we believe, you know, AI Cloud revenue will return to positive growth in the fourth quarter, and the trend will continue, you know, down the road. What is even more exciting is that we keep seeing new opportunities brought up by generative AI and large language models. Actually, last quarter, we already said that, you know, more and more customers across various sectors came to us for model training, application development, and solution enhancement. You know, although the current revenue from generative AI and LLM, you know, related business is still very small, but it's growing very fast. You know, we have seen more and more enterprises proactively adopting these new technologies for productivity and efficiency gain. Some of these customers, especially those from the internet, education, and the tech sectors, they have started to see efficiency gains through working with us. You know, as a result, some of them have gradually increased their spending on our cloud services. Looking to Q4, you know, we aim to leverage our leadership in generative AI and large language models to continuously attract new customers and encourage the existing customers to increase their spending on Baidu AI Cloud. And we believe this should not only lead to long-term revenue growth, but also continuous margin improvement. Thank you, Alex. The next question comes from Miranda Zhuang with Bank of America. Please go ahead. Thank you. Good evening. Thanks, management, for taking my question and congratulations on the results. My question is about ERNIE. So can management share with us the latest feedback for ERNIE 4.0 since the rollout last month? And any color on the contract signed on adopting ERNIE 4.0, and also for consumer end, and how is the feedback after ERNIE Bot started to charge end users a subscription fee? And lastly, among the various opportunities you mentioned, which one do you think can become the biggest revenue driver? Thank you. Hi, Miranda. Let me answer your questions. Since the release of EB 4 in mid October, we're receiving positive feedbacks from both users and customers. Many enterprises have reached out to test EB 4 and have been impressed with its capabilities. EB 4 has gained a reputation for its advanced understanding and complex reasoning abilities. Comparing to EB 3. 5 and other LLMs in the market, we have noted that EB 4 generates more structured and clearer responses and excels in coding. From November 1st, we started to charging enterprises and end users for using EB 4, and we've seen a growing number of customers and users willing to pay for its use. We're proud to be the first company to introduce a GPT-4-level model in China. EB4 further widened our lead over other LLMs in the market, and we are the first LLM to charge end user fees that sets us apart from other peers. Regarding your question about monetization opportunity, we see significant opportunities in AI-native applications, either developed by Baidu or by our customers who leverage our AI capabilities. If you look at our own products, we see significant opportunities in the new search and the revamped ad platform. The new search complements traditional search. It can address complex questions that were previously unanswerable. It also enables users to conduct a more personalized and in-depth research various topics and projects. We will soon enable users to have multi-round conversations with us. As our search will be able to talk with users in natural language and in multi-round, it will create more potential on the commercial side, too. We are experimenting with a chatbot-type ad product for SMEs and the brand. We believe this will not only help drive effective conversion, but also allow us to eventually transform from a CPC model to a CPS model. At the same time, our capabilities will help our advertisers to better operate their business on Baidu. Our ongoing effort to revamp the ad platform have already shown positive results, and we will continue leveraging generative AI to assist advertisers in achieving durable ROI growth on Baidu. In terms of empowering our customers with GenAI, as Dou just mentioned, customer needs are different now. Some customers do prefer to train their own model, but the GPU export restrictions will put a brake on that. It will eventually become clear that training LLMs from scratch is very difficult, especially when trying to achieve emergent capabilities. So we will turn to advanced LLMs available on the market, like ERNIE, for developing applications. As customers become more advanced in using LLM to create applications and more AI-native applications powered by ERNIE become more widely used, we should be able to see continuous revenue growth through model inferencing. Over the long term, inferencing should become a major source of revenue for ERNIE. Meanwhile, we will also help customers to fine-tune our existing model offerings to suit their customized needs, in each scenario, because our models are better, faster, and more cost effective. So in summary, GenAI and LLM will bring us massive business opportunities. We have already made good progress in commercialization so far, and this is just the beginning of a promising future. Thank you. The next question comes from Gary Yu with Morgan Stanley. Please go ahead. Hi, thank you management for the opportunity to ask question. Could management share the latest, advertiser feedback, on the AI-powered ad system upgrade? And how do you think about the level of revenue boost, to the core ads in 2024, as it gets rolled out to more, even all advertisers? Thank you. Yeah, we are very happy with the rapid AI transformation of our ad system and thrilled by the positive feedback from our advertisers. Overall, I think advertisers appreciate our efforts to help them improve their ROIs on our platform. Also, they found out our new features, which help them to be more productive. As I mentioned in the prepared remarks, we've put a lot of effort into using GenAI and LLMs to reinvent our ads system over the past few quarters. Now, we have an integrated advertiser-facing marketing platform. Advertisers can use it to generate creative advertising materials. These materials have proved to deliver higher conversion rates than materials created by humans. And our platform also allows advertisers to engage in natural language. By interacting with the advertisers in multiple rounds of conversation, our upgraded platform is able to better understand their intentions. This allows us to create campaign strategies that deliver higher ROI. Moreover, it significantly reduces the time that ad managers need to spend creating campaigns. Because even an experienced ad manager have to spend hours developing an advertising strategy, and now with an AI copilot, the process only takes, like, a few minutes. As of today, we have a few thousand of advertisers already migrated to our new platform. While this number is relatively small compared to our, you know, 500,000 advertiser base, it is certainly growing very fast. In addition, we continue to use AI to improve our bidding system and ad targeting capabilities. Such initiatives happened at the back end of the system, so advertisers may not directly perceive them, but they've observed improvements in their ad conversion and ROI. So on average, advertisers using these capabilities probably achieved a high single-digit increase in conversion in Q3. All of our efforts should eventually attract advertisers to allocate more of their advertising budget on Baidu. As I previously mentioned, online marketing revenue related to our upgraded ad platform has been growing rapidly and already became meaningful. And this is just the beginning, as I said. We are experimenting with AI chatbot, and chatbots could act as a replacement for landing page in the future. This is particularly useful in verticals, where users typically research and engage in a long decision process before purchasing. Imagine searching for a training program and being directed to a bot instead of a webpage. With our AI chatbots, users can quickly learn about brand-specific information, product details, and other stuff. Although, I think the multi-round conversation is also very engaging. And for advertisers, it helps them to stay connected with potential customers and guide them at key decision-making points, leading to better conversion and even direct sales. We believe AI chatbot could work well with Gen AI-powered new search and bring us more opportunities. I mentioned earlier that the incremental revenue from this kind of initiative are expected to reach the level of CNY hundreds of millions this current quarter, Q4, and this is certainly, you know, growing very fast. The trend should continue and further strengthen in the year of 2024. Thank you. The next question comes from Wei Xiong with UBS. Please go ahead. Good evening, management. Thank you for taking my question. I want to follow up on your Cloud business. So could management share more color on how to think about the industry competitive landscape in China cloud market, especially among the internet cloud vendors and as well as when competing with the telcos? And also with the development in generative AI and the large language model, how do we assess our competitive advantage against peers? Do we expect the competition to intensify next year as other companies try to make efforts and catch up with us? Thank you. Great question. This is Dou. As you actually may already noticed, right? The traditional Cloud business is slowing down, while generative AI and large language models are sliding in and reshaping the competitive landscape of the cloud business industry. In the past, right, the focus in the cloud market was actually on us, which is like a commodity, and people are competing on pricing. But now, you know, with the rise of generative AI and the large language models, things are changing. There's a growing interest, you know, among cloud customers coming to Baidu, to utilize these sophisticated technologies to increase productivity and efficiency. They came to us, you know, not only because we have the most advanced AI technology, but also because we have experience and track record in using AI to help enterprises to solve problems. There were some of them who are still in the product experimental stages, but they have firm belief in the new technology to rebuild their products and services, because they have seen, you know, successful stories, you know, overseas. That is why we are seeing the new technology is increasing our time and expanding our competitive edge. So as Robin mentioned, EB4 is China's first GPT-4 style model. He also shared the positive initial feedbacks we have garnered for EB4. So currently, our team are engaged in a dialogue with our clients, assisting them in understanding the technology, and utilizing ERNIE to redevelop their existing products and create new ones. So I can say that, you know, ERNIE has already helped us attract new customers and additional IT spending from existing customers. So here I would like to briefly bring up two points for our advantage compared to the players in the market. The first one is our unique four-layer AI infrastructure, you know, which gives us the flexibility to make adjustments or innovations at every layer, you know, to be able to be compatible with other layers, to keep driving efficiency in both model training and inference. And the second one, more specifically, is our capability to develop GPU networks or clusters for large language model training. So as Robin just said, you know, 98% of the training time on our AI infrastructure is valid. As a result in our customers, including several leading internet and tech companies, for increasing their investments in our service. Furthermore, we will continue to leverage our unique advantage of AI architecture to drive efficiency gain. It will help us to greatly reduce costs in model training and inference on our cloud, giving us the flexibility to offer more compelling prices to our customers, and further strengthen our competitive edge in the market. You know, regarding the competition from telecom operators, I would like to highlight our focus is on different market segments since we differentiate ourselves with our AI capabilities, in particular, you know, ERNIE, as we have mentioned. Actually, it's worth noting that, you know, we can cooperate, and we are actually cooperating on many objects, products, as for other internet companies in China. So our strong AI capabilities and ERNIE are well-recognized by the market, you know, which will set us apart from our peers. To sum up, you know, we believe that our strong AI capabilities, and particularly in the generative AI and large language models, will allow us to eventually become the, you know, market leader and gain share in the cloud market. The next question comes from Lincoln Kong with Goldman Sachs. Please go ahead. Thank you, management, for taking my question. So my question is also about ERNIE. So given the successful upgrade of the ERNIE 4.0, what will be the future strategy for model iteration to solidify our tech leadership? So do we foresee any competition in the foundation model in the industry, either to stabilize or intensify in the future? Thank you. Hi, Lincoln. The AI chips we have in hand already allow us to launch EB4. We are ahead of the competition. To take our lead in our arms to the next level, we will take an application-driven approach. We will let the AI native apps tell us what to improve in ERNIE Bot capabilities. Given that there are only a very limited number of AI native apps on the market right now, the majority of ERNIE API calls are from internal apps, our internal apps like Search, Ads, Wenku, et cetera. T he rebuilding and restructuring of our existing products drive earning innovation in the right direction. What is equally important is that we are helping enterprises use ERNIE to build their offerings. We have seen that over 10,000 enterprises are using ERNIE through API calls on a monthly basis, which you know propels ERNIE's improvement too. We also continue to improve the efficiency of our models. For example, compared to ERNIE Bot version, the ERNIE Bot version in March, inference cost of the current version has been reduced by 98%, basically resulting in a 50x increase in QPS for the same amount of hardware computing power. We are also able to do this using our, you know, unique four-layer architecture, and leveraging our ability to do end-to-end optimization. Continued inference cost reduction has further strengthened our model's competitive advantage, and it gives us the flexibility to offer more and more compelling pricing. From a long-term perspective, taking into account factors such as the scarcity of high-performance chips, high demand for data, AI talent, and the huge upfront investments, the industry will soon transit into a consolidation stage. We believe there will only be a select few foundation models in the market, and Baidu will certainly be one of them. In this stage of industry development, more and more enterprises will begin to leverage advanced foundation models like ERNIE to create AI-native products, rather than, you know, spending resources on building their own large language models. So we expect that the number of native apps based on ERNIE will reach millions in the future. Thank you. The next question comes from James Lee with Mizuho. Please go ahead. Great, thanks for taking my questions. Can you guys maybe quantify the investment related to AI and how that affects various cost items in your P&L? And should we expect these investments to accelerate over the next few quarters? I was thinking, especially after the launch of ERNIE 4.0, and potentially higher inference costs as more people using it. And then if we extrapolate that over longer term, how should we think about Baidu Core OPM over the next few years, given all the moving parts, including, you know, revenue shift, AI investment, and also your continued improvement in cloud profitability? Thanks. Hi, James. Let me take your questions. This is Julius. Currently, the primary investments for generative AI and large language models are centered around the computing power, which is recorded as part of CapEx. I think the past few quarters, we have put a lot of chip resources to in training our new ERNIE models. And in the future, as more AI-native applications, which is powered by our ERNIE, become more widely used, we should, which also put more resources in model inferences. However, please know that all of this impact for the AI-related hardware investments or P&L is quite manageable, because all the hardware depreciations are spread out over a few years. For example, like, all expenses linked to the computing power we use in the training ERNIE are recorded through the R&D depreciation. And the model inference costs, which is highly related to the usage of the models, either internally or externally, and it should be supported with funding by the future business developments. And moreover, as well, we're happy to see that our investment in generative AI and large language models are beginning to bear fruit. As Robin has mentioned just earlier, since we're receiving the approval from regulators and more additional revenue generated from ERNIEs powered by 2C or 2B businesses has been growing quite fast. While we're using the generative AI and large language models to renovate our businesses, we are still keeping a close eye on making sure our Baidu Core earnings stay solid. In Q3, we can see that mobile ecosystem continue its high margin, ensuring a very strong generation of cash flow. AI Cloud businesses continue its healthy growth and achieve profitability one more time. Look ahead, we expect the traditional cloud business to remain quite profitable, and the new opportunity arising from the generative AI and large language models are also expected to have a favorable margin in the long term. For intelligent driving businesses, our long-term growth opportunity will continue to invest with a measured pace. All in all, we will concentrate our resources by reallocating them from non-core businesses to AI-related businesses. All of these will be quite beneficial for our long-term growth. Thank you, James. The next question comes from Thomas Chong with Jefferies. Please go ahead. Hi. Good evening. Thanks management for taking my questions, and congratulations on a solid set of results. My question is on the chip side. Can management comment about the impact on AI development after the further restriction of the chip export from the U.S.? How does that affect our AI product offerings and user experience, if any? Thank you. Yeah, the restrictions on the chip export to China actually have limited impact on Baidu in the near term. We have successfully launched EB4 in mid-October, our most advanced foundation model in China. It is a milestone for us, and as I just said earlier, we have a substantial reserve of AI chips, which can help us keep improving ERNIE Bot for the next year or two. Also, inference requires less powerful chips, and we believe our chip reserve, as well as other alternatives, will be sufficient to support a lot of AI-native apps for the end users. And in the long run, having difficulties in acquiring the most advanced chips inevitably impacts the pace of AI development in China. So we are proactively seeking alternatives. While these options are not as advanced as the best chips in the U.S., our unique four-layer AI architecture and strength in AI algorithm will continue to help us improve efficiency and mitigate some of these challenges. For example, we have made some innovations in PaddlePaddle, our deep learning framework, and ERNIE, our foundation model, to allow them to be better compatible with different types of AI chips on both model training and inference tasks. But given that all the other Chinese companies face the same challenge, we believe we are actually best positioned to serve this market. As you probably know, in the past, some of our peers, they, they tried to ride on the GenAI wave by investing in those startups to train foundation models. They basically sell the computing power to those startups. We didn't do that. You know, we tried to optimize everything from the infrastructure layer to framework layer, then to model layer, then to app. So we've invested in this kind of end-to-end optimization approach. Therefore, we can, for the same amount of computing power, we can do training more efficiently, more cost effectively, and we can do inferencing faster and cheaper. As time passes by, I think more and more company will realize that they don't need to train their foundation models. They just need to develop AI-native apps based on Baidu's foundation model, which is the best on the market. So I'm really happy that we basically invested on this kind of end-to-end optimization front for many, many years, and it's time for us to show that the investment is worth it. Thank you. Ladies and gentlemen, that does conclude our conference for today. Thank you for participating. You may all disconnect.