Core Insights - MiroMind team has launched MiroThinker 1.5, a flagship search intelligence model, which emphasizes "discovery-based intelligence" as a path to true general artificial intelligence [2][3] - The model aims to reconstruct understanding of the world under unknown conditions, focusing on research, verification, and correction rather than sheer data accumulation [2] Model Performance - MiroThinker 1.5 operates with 30 billion parameters, achieving performance comparable to larger models with 1 trillion parameters, demonstrating a high efficiency-to-intelligence ratio [3] - The model's cost per call is as low as $0.07, which is 1/20th of the cost of its competitor Kimi-K2-Thinking, while also providing faster inference [5] Interactive Scaling Concept - MiroThinker introduces "Interactive Scaling," shifting the focus from internal parameter expansion to external information interaction, enhancing reasoning capabilities [6][9] - The model is designed to function like a "scientist," emphasizing verification and correction over memorization, thus avoiding the pitfalls of traditional large models [8][10] Training Mechanism - The training process incorporates a "reason-verify-correct" loop, allowing the model to engage with external data for validation, which helps mitigate logical errors [9][12] - MiroThinker employs a time-sensitive training mechanism that restricts the model to only interact with information available before a given timestamp, ensuring realistic decision-making [12] Verification and Correction - The model encourages breaking down key judgments into verifiable sub-hypotheses and actively seeking external evidence, making the evidence-gathering process the primary training goal [11] - It emphasizes iterative verification, where reasoning is treated as a revisable process, allowing for adjustments based on conflicting evidence [11]

Group 1 - The core issue revolves around the public letter from Wang Hai, chairman of Qingdao Double Star Celebrity Group, announcing the severance of ties with his son Wang Jun and daughter-in-law Xu Ying, indicating doubts about Wang Jun's succession capabilities [1][3] - The Double Star Celebrity Group, originally a state-owned enterprise, has transformed into a leading brand in the sports shoe industry, but has faced increasing competition in recent years, leading to a decline in its market presence [3][4] - Wang Hai's public letter reflects broader challenges in the succession of private enterprises in China, highlighting the emotional and operational struggles faced by aging founders [3][4] Group 2 - Similar succession conflicts have occurred in other major consumer companies, such as Shuanghui Group, where founder Wan Long had a public dispute with his son over differing business philosophies [4][5] - The founders of these companies, including Wang Hai, Wan Long, Zhu Xinli, and Zong Qinghou, share common traits of having built their businesses during China's economic reforms, yet they now face difficulties in transitioning leadership to the next generation [5][6] - The aging founders are often reluctant to step back, leading to internal conflicts as they grapple with the future of their brands amidst changing market dynamics [10][11] Group 3 - The companies led by these founders have historically excelled in product quality, market channels, and scale, establishing strong brand identities in their respective sectors [10][11] - As the market evolves from scarcity to abundance, these once-dominant brands are encountering significant challenges, with some heirs willing to take over but facing resistance from their founders [11][12] - The ongoing legal disputes within Double Star indicate a deepening struggle for control, reflecting the complexities of succession planning in family-owned businesses [12]

据宜家中国表示，宜家中国在对现有顾客触点进行全面审视和评估之后，决定自2026年2月2日起停止运 营包括宜家上海宝山商场、宜家广州番禺商场、宜家天津中北商场、宜家南通商场、宜家徐州商场、宜 家宁波商场和宜家哈尔滨商场在内的七个线下触点。 此外，宜家中国还将从规模扩张转向精准深耕，以北京和深圳作为重点市场进行探索，在接下来的两年 内开设超过十家小型门店，包括将于2026年2月开业的宜家东莞商场和将于2026年4月开业的北京通州商 场。并且还将继续加强线上布局，并对现有商场进行投资。 宜家中国表示，将持续评估并优化全渠道生态系统，通过更聚焦、更灵活的投资实现更高效的运营和更 好业务成果。近期的举措包括：融合家居灵感与社交体验的上海徐汇商场改造项目、在全国多地新开的 五家不同规模的全新门店，以及新近上线的宜家京东旗舰店。 自2026年2月2日起，停止运营7个线下触点调整后，宜家在中国仍拥有 34 个线下顾客触点、3个自有数 字化渠道以及2家电商平台旗舰店。 从降价到多渠道探索 根据宜家母公司英格卡集团财报数据，宜家中国区销售额从2019财年巅峰期的157.7亿元，一路下滑至 2024财年的111.5亿元，缩水近三成 ...

文 | 红餐供应链指南 一纸公文，让全球牛肉贸易商、中国养殖户和无数餐饮老板同时屏住了呼吸。 几天前，商务部发布公告，决定以"国别配额及配额外加征关税"的形式对进口牛肉采取保障措施，自2026年1月1日起实施，为期三年。按照新规，超出配 额的进口牛肉将在现行适用关税税率基础上加征55%。 这意味着，占据中国牛肉消费三成份额的进口牛肉，将告别"无限量供应"时代，也预示着一个新的、更复杂、也更分层的牛肉市场，或将加速形成。 贸易商抢购，进口牛肉价格涨起来了！ 在上海从事牛肉贸易业务的李晓（化名）在跟红餐供应链指南交流时讲到，自己公司主要进口巴西牛肉，目前对外出售的这些进口牛肉价格已经上涨，1 月才过去几天，一斤价格已经涨了2、3块钱。 另据"中国新闻周刊"的报道，政策发布后，国内进口商争相"建仓"抢购，不少贸易商的联络清单从往常的两三家海外工厂，扩展到十几家，都想在配额用 光前尽快上车。 贸易商的紧张不是没有理由的。根据国别配额分配，2026年，巴西以110.6万吨居首，阿根廷、乌拉圭分别获得51.1万吨和32.4万吨，澳大利亚和新西兰各 约20万吨，合计约268.8万吨。 | 配额数量及加征关税税率表 | | ...

Core Insights - The statement "AI is not a choice but a matter of survival" emphasizes the critical importance of AI in digital transformation for enterprises by the end of 2025 [2] - The role of CIOs is evolving from a cost center to a strategic partner in driving AI integration within organizations, with ultimate decision-making power resting with top executives [2][5] Industry Trends - Enterprise AI is transitioning from a phase of "barbaric growth" to a critical period of "collaborative explosion" between foundational and application layers, indicating a significant market evolution [3] - Global AI investment is projected to reach $315.9 billion in 2024 and grow to $1.2619 trillion by 2029, with a compound annual growth rate (CAGR) of 31.9% [3] China Market Focus - The Chinese enterprise AI service market is expected to reach 45.6 billion yuan by 2025, with a CAGR of 38.2% [4] - The AI Agent application market in China is projected to grow to 23.2 billion yuan by 2025, with an astonishing CAGR of 120% from 2023 to 2027 [4] Shifts in AI Demand - Companies are shifting their AI needs from merely providing tools to delivering value, indicating a maturation in the understanding of AI's role in business [5] - The focus is now on customized AI applications and quantifiable business outcomes, moving beyond traditional cost-cutting perspectives [5] AI Application Challenges - Only 12% of global enterprises are expected to achieve normalized AI application in core business decisions by 2025, highlighting significant barriers to adoption [8] - The primary challenge in core decision-making applications is the need for a closed-loop system of "data-insight-action," which many current AI systems struggle to achieve [9][10] Service Provider Landscape - Four main types of service providers have emerged in the enterprise AI space: large model technology providers, agent service providers, traditional software vendors, and data + AI vertical service providers [6] - New entrants like Yuan Yuan Xing He are attempting to redefine the market by offering end-to-end process reconstruction and organizational change capabilities [7] Future Directions - The future of enterprise AI is expected to evolve towards "controllable, collaborative, and ecological" systems, moving from mere tool empowerment to comprehensive system reconstruction [13][14] - The integration of AI into business processes is anticipated to enhance productivity significantly, with predictions that 60% of manufacturing enterprises will adopt integrated AI models by 2028 [14] Value Verification in AI Projects - The shift from traditional project delivery to value verification models is becoming crucial, with success rates for value verification projects significantly higher than traditional methods [11] - The complexity of measuring ROI in AI projects is a major reason for hesitance in investment, with 68% of companies citing difficulties in accurately assessing ROI [12]

Core Insights - The article emphasizes a shift in the AI industry from a model-centric competition to a delivery-centric competition, highlighting that while models determine the upper limits of capability, the infrastructure and delivery mechanisms are crucial for scaling and monetizing these capabilities [1][10][13] Group 1: Shift in Focus from Models to Delivery - The transition from model competition to delivery competition is driven by three constraints: rising costs of training and inference, accelerated capability diffusion, and the need for a robust commercial closure [2][8] - The marginal cost of achieving cutting-edge capabilities is increasing, making it essential for leading models to be supported by lower inference costs and stable delivery quality to realize their advantages in scalable scenarios [2][9] Group 2: xAI's $20 Billion Significance - xAI's $20 billion investment is aimed at enhancing its second and third layers of competitive capability, focusing on infrastructure and delivery systems rather than just model development [3][10] - The investment emphasizes the expansion of computational infrastructure and the establishment of a visible asset base with over one million H100 equivalent GPUs, thereby enhancing supply certainty [3][6] Group 3: Competitive Landscape and Capability Layers - The competitive landscape is structured into three layers: model and training methods (first layer), infrastructure and supply chain (second layer), and distribution and entry points (third layer) [3][4] - Major players like Google excel across all three layers, while others like OpenAI and Meta have strengths in specific areas, indicating a need for companies to enhance their infrastructure and delivery capabilities to remain competitive [6][10] Group 4: Future Competition Dynamics - The future competition is expected to resemble a platform war rather than a model elimination race, with a focus on scaling delivery capabilities and ensuring compliance and stability [10][11] - The probability of a single company dominating the global market is low due to the decentralized nature of user preferences and regulatory environments, leading to a scenario where platforms excel in delivery and compliance [11][13] Group 5: Key Indicators for Future Success - Companies should focus on three leading indicators: unit inference cost curves, entry penetration rates, and delivery capabilities to assess competitive positioning in the evolving landscape [9][13] - The ability to convert model capabilities into scalable cash flows will depend on performance in these three areas, marking a significant shift in how success is measured in the AI industry [9][10]

"这是为进一步协同作战、整合资源......未来，OPPO与realme、一加将共同为全球用户提供更具创新力 和差异化的产品，以及更便捷周到的服务。"上述人士如此表示。 智通财经也在报道中指出，realme回归OPPO后将与一加合并，realme CEO 李炳忠（Sky Li）将领导整 体子品牌业务，一加中国区总裁李杰职责不变。 此后，一加将专注国内和部分海外线上市场，非中国区海外市场由realme和主品牌OPPO承接。 从现有信息看，realme回归OPPO，尚未涉及到更深层次的高管变动及组织架构调整。 realme新品也将如期发布，同时将全面接入OPPO售后服务体系。真我已于1月5日官宣，其2026年首款 新品真我Neo 8将于本月发布。 文 | 听潮TI，作者 | 许雯雯，编辑 | 张晓 1月7日，多家媒体报道，智能手机品牌realme将回归OPPO，成为旗下子品牌。 听潮TI已向OPPO相关人士证实，此消息属实。 从一加到realme：不同的市场环境、相似的回归剧本 市场对realme回归OPPO不算陌生，一加也走过相似的路径： 不同的市场环境下，核心高管脱离OPPO体系独立创业，做出一定成绩、被市场 ...

Regulatory Developments - The State Administration for Market Regulation and the National Internet Information Office jointly released the "Live E-commerce Supervision Management Measures," focusing on four main entities: platform operators, live room operators, marketing personnel, and service agencies, to enforce responsibilities and delineate behavioral boundaries [2][3] - The measures specify the responsibilities of live e-commerce platform operators, including identity verification, information reporting, training for marketing personnel, risk identification, and consumer rights protection [2] - Clear behavioral boundaries are established, prohibiting false advertising, commercial defamation, and the sale of illegal goods or services by live room operators and marketing personnel [2] Industry Impact - The measures aim to strengthen regulatory tools by incorporating traffic control and regulating AI-generated content, ensuring that new technologies do not facilitate the generation or dissemination of false information [3] - The implementation of these regulations is expected to enhance the operational integrity of the live e-commerce sector and protect consumer rights [2][3] Corporate Actions - ByteDance denied rumors regarding plans to enter the automotive industry, clarifying that there are no current intentions to manufacture vehicles [6] - Xiaomi's CEO Lei Jun confirmed that there are no plans for a new model, the Xiaomi SU3, amidst various speculations [7] Market Movements - The Chinese central bank reported an increase in gold reserves for the 14th consecutive month, with reserves reaching 7.415 million ounces (approximately 2306.323 tons) as of the end of December [27] - Domestic flight ticket prices have significantly dropped post-New Year, with some fares as low as 210 yuan (approximately 1.1% of the original price) for routes like Guangzhou to Shanghai [28]

文 | 极点商业，作者 | 杨 铭，编辑 | 刘珊珊 算力即国力，不是一句口号。全球地缘和科技争夺加剧、人工智能快速迭代的当下，已经成为全球AI 竞速赛的冰冷现实。 以美国为例，正通过芯片禁令、生态绑定与资本优势，构建"算力霸权"——川普就在签署的《赢得AI竞 赛:美国AI行动计划》中，用30项举措和100余条具体政策行动，应对中国AI竞争，"实现并保持全球技 术领域无可争议、无可挑战的主导地位。" 面对算力竞争的日益白热化，中国必须回答一个根本性问题：中国算力核心竞争力究竟来自哪里？是复 制烧钱军备竞赛，还是开辟一条更高效、更普惠、更可持续的智算新路？ 答案，正在浮出水面。 两大头部人工智能国家队——北京信息产业发展投资基金与北京市人工智能产业投资基金就罕见联手， 近日联合领投人工智能基础设施与智算云提供商九章云极，成为近期资本市场最受关注的交易之一。 业界普遍认为，这笔2025年中国算力领域"收官之作"的投资，更是一场关乎算力主权、产业效率与创新 公平的战略抉择：中国投资算力战略重心，正从追求规模，转向推动普惠，从"建多少算力"转向"用好 每一度算力"。 它要回答的，是中国已建成全球第二大规模算力背景下， ...

Core Insights - Tencent has officially launched the "AI Application and Online Tool Mini Program Growth Plan" to support developers in creating AI mini programs within the WeChat ecosystem [1][3] - This initiative is seen as a significant step towards the long-anticipated WeChat Agent, aiming to enhance the practical application of AI technology [2][10] Group 1: Tencent's Strategy and Support for Developers - Tencent is providing substantial resources to developers, including cloud development resources, AI computing power, data analysis, advertising monetization, and traffic incentives [1][3] - The plan aims to lower barriers for AI development, making it easier for independent developers and small teams to create AI applications without the burden of backend infrastructure [4][10] - Tencent is offering 100 million tokens and 10,000 image generation credits to alleviate the financial burden on developers, allowing them to focus on user interaction without worrying about API costs [6][10] Group 2: Addressing Key Challenges in AI Development - The initiative addresses critical issues faced by AI developers, such as high development costs, expensive computing power, difficulty in gaining traffic, and slow monetization [3][5] - Tencent's approach includes providing free cloud development environments and backend capabilities, promoting a serverless development model [4][10] - The plan also includes free access to "We Analysis Professional Version" to help developers understand user behavior and improve retention [8][10] Group 3: Future Implications and Market Position - The growth plan is viewed as a large-scale "crowdsourcing" effort to build a diverse range of AI applications that will contribute to the future WeChat Agent [11][19] - Tencent's recent organizational restructuring and the appointment of a young AI scientist signal a shift towards strengthening its core AI capabilities [16][17] - Despite the delays in launching the WeChat Agent, the market remains optimistic due to Tencent's unique social ecosystem, which provides a high-frequency and sticky environment for AI applications [18][19]