Market Overview - The active installed base of smartphones in India exceeds 740 million, representing more than half of the country's population of 1.45 billion [1] - India accounts for 14% of the global installed base of smartphones, while China leads with a 19% share, equating to approximately 1,005 million devices [2] Retention and Longevity - The average smartphone retention period in India is currently 42 months, which is slightly lower than the global average of 47 months [2][6] Brand Leadership - Xiaomi holds the largest active installed base in India, despite a decline in market share as it shifted focus from affordable devices to the premium segment [3] - Xiaomi's older Redmi and Note series continue to be widely used, indicating long shelf lives before users upgrade [3] - Globally, Xiaomi ranks third in terms of active installed base, with only Apple and Samsung surpassing the 1 billion mark [4] Competitive Landscape - Eight brands have active installed bases exceeding 200 million units globally, including Apple, Samsung, Xiaomi, Oppo, Vivo, Honor, Transsion, and Huawei, collectively controlling over 80% of the global smartphone installed base [5] - Motorola, Realme, and Google remain below the 200 million mark, with Motorola and Realme nearing that threshold [5]

Group 1 - Zhipu released the open-source GLM-5 model with a parameter scale expanded to 744 billion (activated 40 billion), ranking fourth globally in the Artificial Analysis leaderboard and first in open-source, with coding and agent capabilities approaching Claude Opus 4.5 [1] - The model achieved scores of 77.8 and 56.2 in SWE-bench-Verified and Terminal Bench 2.0, respectively, setting new open-source SOTA records, excelling in complex systems engineering and long-range agent tasks [1] - GLM-5 has been adapted to domestic chips such as Huawei Ascend, Cambricon, and Kunlun, and introduced Z Code full-process programming tools and AutoGLM universal agent assistant [1] Group 2 - MiniMax launched the M2.5 model with only 10 billion activated parameters, achieving flagship-level reasoning speed three times faster than Opus [2] - The model completed a full-stack learning website in 9 minutes and can independently perform physical simulations and enterprise-level CMS system setups, supporting cross-platform development for PC/App/React Native [2] - It utilizes a native agent RL training framework and CISPO algorithm, achieving approximately 40 times training acceleration and is compatible with mainstream development tools like Claude Code and OpenClaw [2] Group 3 - Xiaohongshu's foundational model team released the open-source FireRed-Image-Edit, achieving SOTA in multiple authoritative rankings such as ImgEdit and GEdit, with code and technical reports now available [3] - The model employs a three-stage training process to enhance capabilities and innovatively introduces Layout-Aware OCR-based Reward, significantly improving text editing accuracy and style retention [3] - It supports various complex editing scenarios, including instruction-following consistency, text editing, style transfer, multi-image fusion, and old photo restoration, with model weights set to be open-sourced [3] Group 4 - Xiaomi released the open-source VLA model Xiaomi-Robotics-0 with 4.7 billion parameters, excelling in visual language understanding and real-time execution capabilities, achieving optimal results in comparisons across 30 models including LIBERO, CALVIN, and SimplerEnv [4] - The model uses a Mixture-of-Transformers architecture, where the VLM brain understands instructions and the Diffusion Transformer generates high-frequency smooth actions [4] - It addresses action discontinuity issues through asynchronous reasoning and Λ-shape attention masks, enabling real-time inference on consumer-grade graphics cards, and has been open-sourced on GitHub and HuggingFace [4] Group 5 - Gaode launched the ABot series of embodied base models, with ABot-M0 responsible for operations and ABot-N0 for navigation, achieving comprehensive SOTA across 10 global authoritative evaluations [5][6] - ABot-M0 integrates 6 million cross-platform trajectory data through action language and proposes an action manifold learning algorithm, achieving an 80.5% success rate on Libero-Plus, surpassing pi0 by nearly 30% [6] - ABot-N0 unifies five core navigation tasks within a single VLA architecture, constructing 8,000 high-fidelity 3D scenes and 17 million expert examples, with a 40.5% improvement in SocNav success rate [6] Group 6 - Rokid Glasses launched the "customizable agent" feature on the Lingzhu platform, allowing integration with OpenClaw or privately deployed models like DeepSeek R1 and Qwen3 through a standard SSE interface [7] - Users can achieve local closed-loop processing of private data and switch model bases with one click, leveraging the ClawHub skill ecosystem to execute capabilities like file systems, browsers, and IM messaging [7] - The platform empowers users by allowing them to summon private agents via voice commands or shortcuts, creating a 24/7 intelligent assistant [7] Group 7 - Google DeepMind released the AI mathematician Aletheia based on Gemini Deep Think, achieving a score of 91.9% on IMO-ProofBench, setting a new SOTA and capable of independently writing and publishing academic papers [8] - Aletheia systematically evaluated 700 open problems in the Erdős conjecture database and autonomously solved 4 unsolved mysteries, demonstrating self-correction and acknowledgment of limitations [8] - Gemini Deep Think collaborated with experts to tackle 18 long-stagnant research challenges, resolving a decade-long submodel optimization conjecture, with one paper accepted by ICLR 2026 [8] Group 8 - HyperWrite's CEO published an article that garnered 70 million views, stating that the release of GPT-5.3-Codex and Claude Opus 4.6 marks a qualitative change in AI [9] - AI can now independently complete the workload of human experts in 5 hours, with this capability doubling every 4-7 months, and GPT-5.3 plays a crucial role in its self-training process, initiating a recursive self-improvement cycle [9] - Almost all cognitive work performed in front of screens will be affected, and it is advised to spend one hour daily experimenting with AI, as the current cognitive window period will not last long [9] Group 9 - Anthropic released a 53-page report warning that the risks associated with Claude Opus 4.6 are approaching ASL-4 levels, outlining 8 potential risk pathways that could lead to catastrophic harm, including autonomous escape and autonomous operation [10][11] - The report concludes that current models do not exhibit "sustained consistent malicious intent," and the risk of catastrophic damage is "very low but not zero," entering a "gray area" of capability assessment [10] - The head of Anthropic's safety research team resigned, stating that "the world is in crisis," and xAI co-founder predicts that recursive self-improvement cycles may be launched within 12 months [11]

Core Viewpoint - The article emphasizes the importance of practical learning experiences in cutting-edge technology sectors, highlighting the value of direct engagement with leading companies and experts to enhance investment insights and opportunities [12][24]. Schedule Overview - The schedule for 2025 includes visits to major technology companies such as Huawei, BYD, Tencent, and others, focusing on sectors like artificial intelligence, new energy, and biotechnology [23][24]. - Specific events are planned, including closed-door investment research meetings and thematic explorations in various cities, showcasing advancements in robotics, autonomous driving, and digital ecosystems [8][9][10]. Learning Experience - Participants will engage in deep explorations of technology companies, gaining insights into the full chain of technology development from laboratory to industrialization [12]. - The program includes face-to-face dialogues with founders and executives, providing critical insights into strategic decisions and industry disruptions [12]. Participant Feedback - Feedback from participants highlights the transformative impact of the program on their understanding of macroeconomic trends and investment strategies, emphasizing the importance of continuous learning and adaptation in a rapidly changing environment [46][47][48].

Market Overview - The Hang Seng Index fell by 0.86%, closing at 27,032.54 points, with a total market turnover of 238.705 billion HKD [1] Southbound Trading Data - Tencent Holdings, Xiaomi Group-W, and Meituan-W saw net purchases of 1.429 billion HKD, 1.020 billion HKD, and 0.985 billion HKD respectively [1][2] - WuXi Biologics, Zijin Mining, and Pop Mart experienced net sales of 0.392 billion HKD, 0.346 billion HKD, and 0.301 billion HKD respectively [1][2] Individual Stock Performance - Tencent Holdings had a trading volume of 12.026 billion HKD, with a net buy of 1.429 billion HKD, closing at 535.50 HKD, down by 2.28% [2] - Xiaomi Group-W recorded a trading volume of 27.46 billion HKD, with a net buy of 1.020 billion HKD, closing at 36.52 HKD, down by 1.56% [2] - Meituan-W had a trading volume of 38.31 billion HKD, with a net buy of 0.985 billion HKD, closing at 84.85 HKD, down by 4.50% [2] - Pop Mart had a trading volume of 21.899 billion HKD, with a net sell of 0.301 billion HKD, closing at 252.20 HKD, down by 1.10% [2] - WuXi Biologics had a trading volume of 6.99 billion HKD, with a net sell of 0.392 billion HKD, closing at 41.34 HKD, down by 0.14% [2] - Zijin Mining had a trading volume of 9.64 billion HKD, with a net sell of 0.346 billion HKD, closing at 45.02 HKD, up by 3.45% [2]

Group 1 - The core message is that Xiaomi Automobile will continue to provide maintenance and repair services for the first-generation SU7 even after its production ceases [2] - Xiaomi Automobile has prepared sufficient spare parts and production capacity from suppliers for the first-generation SU7, ensuring at least 10 years of parts availability [2]

Group 1 - The first generation SU7 has been discontinued, but the company will continue to provide maintenance and service support, ensuring sufficient spare parts availability for at least 10 years [1][9] - The first generation SU7 was delivered from April 2024 to February 2026, with a total delivery exceeding 381,000 units in less than two years [1][9] - The new generation SU7 is currently on display in Beijing and will be showcased in select stores across several cities starting February 13, 2026 [2][10] Group 2 - During the Spring Festival, all Xiaomi car stores will remain open from 9:00 AM to 6:00 PM, providing opportunities for customers to view and test drive vehicles [6][14] - A total of 275 service centers will operate during the holiday, covering 158 cities, offering quick repair services and 24/7 online support [6][14] - Customers are advised to check their vehicle conditions before long trips, including systems like lighting, brakes, and tire pressure, especially in cold weather [7][15]

Core Viewpoint - The article discusses the significant impact of rising storage chip prices on the smartphone industry, particularly affecting mid-range and low-end models, as manufacturers shift focus to higher-margin products due to supply constraints driven by AI infrastructure demand [6][8][19]. Group 1: Market Dynamics - Since the second half of last year, storage chips have experienced a dramatic price surge, with consumer-grade memory modules increasing by over 600%, making them a highly valued investment product [6]. - Major storage chip manufacturers, including Samsung, Micron, and SK Hynix, have reported that their production capacities for DRAM, NAND Flash, and HBM products are fully booked until 2026 [6]. - The demand for HBM memory used in AI chips has led to prioritization in production, squeezing the supply of consumer-grade products and significantly impacting low-end smartphone manufacturers like Transsion [8][10]. Group 2: Financial Impact on Companies - Transsion, known for its cost-effective models, saw a 22.6% revenue increase in Q3 2025, but its net profit dropped by 11%, with a two-percentage-point decline in gross margin [8]. - Other smartphone manufacturers are also adjusting their strategies, with many opting to delay the launch of low-cost models and reducing overall order volumes by 10%-20% for 2026 [10]. - The rising costs of storage components have exposed the vulnerability of mid-range and low-end smartphones, which have less flexibility in pricing and profit margins compared to high-end models [13][14]. Group 3: Pricing Strategies and Market Trends - The average selling price (ASP) of smartphones is projected to exceed $400 for the first time, indicating a shift towards higher-priced models as manufacturers respond to rising component costs [19]. - Companies are likely to either increase prices to maintain margins or lower them to capture market share, particularly as the low-end market continues to shrink [19]. - The ongoing supply constraints and price increases in storage chips may signal the end of the "thousand-yuan phone era," pushing consumers towards higher-end devices [19].

Core Insights - The article discusses the rising prominence of embodied intelligence and robotics, highlighting the increasing interest from both large and small companies, as well as capital investment and media coverage [2][3] - There is a growing expectation for embodied robots to transition from being merely demonstrative to becoming practical tools that enhance productivity in real-world applications [3][4] - Xiaomi's new embodied VLA model, Xiaomi-Robotics-0, addresses critical issues such as the frequent pauses and slow corrections in robotic execution, aiming for greater autonomy and efficiency [7][8] Group 1: Industry Trends - The embodied robotics sector is at a pivotal point, characterized by impressive demonstrations of capabilities while also facing scrutiny regarding their actual value in industrial settings [3][4] - The industry is experiencing a paradigm shift where the focus is on the autonomy of robots, moving beyond human-assisted operations to fully autonomous systems [4][6] Group 2: Xiaomi-Robotics-0 Innovations - Xiaomi-Robotics-0 features three core technological innovations: architecture design, pre-training strategies, and post-training mechanisms, all aimed at enabling robots to understand complex environments and execute actions continuously and accurately [12][13] - The model employs a dual-brain architecture, separating the "brain" for decision-making and the "small brain" for generating continuous action blocks, which enhances the smoothness and precision of robotic movements [16][21] - A two-phase pre-training approach is utilized to maintain the model's visual understanding while training it to perform actions, ensuring that the robot can interpret complex instructions and plan continuous movements [24][30] Group 3: Performance Metrics - Xiaomi-Robotics-0 has achieved outstanding results in various benchmarks, surpassing approximately 30 existing models in environments like LIBERO, CALVIN, and SimplerEnv [44][45] - The model demonstrated a 100% success rate in the Libero-Object task and maintained high throughput in real-world tasks such as towel folding and LEGO disassembly, showcasing its practical capabilities [47][54][57] - The model's performance indicates that it does not sacrifice understanding capabilities for control abilities, maintaining high scores across multiple evaluation metrics [49][58] Group 4: Strategic Direction - Xiaomi's approach in the embodied intelligence field appears to focus on practical applications rather than merely showcasing advanced technology, aiming to address real-world industrial challenges [61][65] - The company has recently open-sourced its models, including TacRefineNet, which enhances fine-grained control without relying on visual input, indicating a commitment to transparency and collaboration within the industry [74][76] - This open-source strategy lowers barriers for smaller developers, allowing them to build upon Xiaomi's foundational work and contribute to the development of specialized applications in robotics [78][79]

Core Viewpoint - The announcement by Xiaomi Auto supports the "Guidelines for Compliance with Pricing Behavior in the Automotive Industry," which aims to regulate competition in the automotive sector and promote high-quality development [1] Group 1 - The National Market Supervision Administration released the "Guidelines for Compliance with Pricing Behavior in the Automotive Industry" on February 12 [1] - The guidelines are an important measure to ensure fair competition in the automotive industry and protect consumer rights [1] - The initiative encourages the industry to transition towards value creation focused on technology and quality [1]

Core Viewpoint - The release of the "Guidelines for Compliance with Pricing Behavior in the Automotive Industry" by the National Market Supervision Administration is a significant measure to regulate competition in the automotive sector and promote high-quality development in the industry, ensuring consumer rights and shifting the focus towards value creation based on technology and quality [1][2]. Company Response - Xiaomi Auto expresses strong support and active response to the guidelines, committing to optimize its pricing management and compliance system in accordance with the guidelines [1][2]. - The company will strictly implement clear pricing requirements and resolutely eliminate price fraud and unfair competition practices [1][2]. - Xiaomi Auto aims to leverage its role in the industry chain to encourage partners to adhere to the guidelines, collaborating with industry peers to maintain fair competition and contribute to the high-quality development of China's automotive industry [1][2].