Core Viewpoint - DeepSeek has released an update to its model, DeepSeek-V3.1-Terminus, which aims to improve stability and consistency based on user feedback, but the anticipated release of the next-generation model, DeepSeek-R2, has been delayed, causing disappointment in the industry [1][2][3] Group 1: Market Expectations and Delays - The initial release of DeepSeek-R1 was a significant success, outperforming top models from OpenAI and establishing high expectations for the subsequent model, R2 [3][5] - Since the launch of R1, there have been over ten rumors regarding the release of R2, with initial expectations set for May 2025, but these have not materialized, leading to a sense of frustration in the market [5][6] - The delay in R2's release is attributed to internal performance issues and external pressures, including supply chain challenges related to NVIDIA chips [6][12] Group 2: Strategic Developments - Despite the delay of R2, DeepSeek has made significant strides in building an open-source ecosystem, launching several models and tools that lower the cost of AI technology [8][9] - The company has introduced various components aimed at enhancing training and inference efficiency, such as FlashMLA and DeepGEMM, which reportedly improve inference speed by approximately 30% [9][11] - DeepSeek's open-source strategy has positioned it as a key player in promoting accessible AI technology in China, although the absence of R2 raises concerns about its competitive edge [8][17] Group 3: Challenges Faced by DeepSeek - DeepSeek faces a "triple dilemma" regarding the delay of R2, including the need for technological breakthroughs, managing high market expectations, and navigating intense competition from domestic rivals like Alibaba and Baidu [11][12][13] - The company must overcome technical challenges related to transitioning from NVIDIA to Huawei's Ascend chips, which has hindered R2's development [11][12] - DeepSeek's lack of a robust content ecosystem compared to larger tech companies limits its ability to continuously improve its models, leading to issues such as "hallucinations" in its outputs [15][16]

Core Insights - Baidu's core revenues for FY25Q1 reached RMB 27,488 million, beating consensus estimates by 6.5% with a year-over-year growth of 7.1% [1] - The online marketing segment saw a decline of 6% year-over-year, while the cloud and other services experienced a significant growth of 18.2% [1][2] - The company reported a gross profit of RMB 15,439 million, with a gross margin of 56.2%, reflecting a year-over-year decline of 7 percentage points [1][2] - Operating income was RMB 4,668 million, representing a year-over-year growth of 23.4% [1] Financial Performance - Baidu's core revenues for FY25Q1 were RMB 27,488 million, with a year-over-year growth of 7.1% [1] - Online marketing revenues were RMB 19,227 million, down 6.6% year-over-year [1] - Cloud and other services generated RMB 8,262 million, with a year-over-year growth of 42% [1][2] - Gross profit was RMB 15,439 million, with a gross margin of 56.2% [1] - Operating income reached RMB 4,668 million, with an operating margin of 17% [1] User Growth and Engagement - Baidu's app monthly active users (MAU) reached 724 million, a net increase of 45 million from the previous month, marking a historical high [2][6] - The integration of DeepSeek into Baidu's search engine has significantly boosted user engagement and activity [2] Advertising and AI Monetization - Advertising revenue declined by 6% year-over-year, indicating challenges in the traditional advertising model [2][3] - Baidu plans to gradually implement AI search monetization strategies in Q2, focusing on enhancing revenue from AI-driven traffic [2][3] Cost Management and Capital Expenditure - R&D expenses have been decreasing, reflecting improved internal efficiency driven by AI [3] - Capital expenditures increased by 40% in Q1, as Baidu resumed expansion efforts after a period of contraction [3][4] Share Buyback and Cash Flow - Baidu's free cash flow was negative in Q1, influenced by short-term debt repayments and increased capital expenditures [3] - The company repurchased USD 445 million worth of shares in Q1, continuing its buyback program [3][4] AI Development and Strategy - Baidu has released several upgraded AI models, including ERNIE 4.5 and ERNIE X1, with plans to open-source these models by June 30 [5][11] - The company is focusing on application-driven innovation in AI, aiming to reduce inference costs through comprehensive AI capabilities [11][12] Business Expansion and Partnerships - Baidu is expanding its AI cloud business and deepening collaborations with major clients, including top e-commerce companies [9] - The company is also exploring new markets, such as the automotive industry and humanoid robotics [9]