智东西1月21日报道，今天，刚刚成立3个月的美国AI创企Humans&宣布拿下一轮4.8亿美元（约合人民币33.41亿元）的种子轮融资，估值达 44.8亿美元（约合人民币311.86亿元），直接晋身独角兽行列。 这轮融资由SV Angel和谷歌第七号员工、Humans&联合创始人Georges Harik领投，参与投资的机构和个人包括英伟达、亚马逊创始人贝佐斯、 谷歌风投（GV）、Emerson Collective（乔布斯遗孀劳伦娜·鲍威尔·乔布斯旗下的公司）等。 与许多AI创企一样，Humans&中华人的存在感很强，18位创始成员中有6位华人，占比高达1/3。 Eric Zelikman和Yuchen He都是前xAI研究员。其中，Eric Zelikman曾深度参与Grok2、Grok3、Grok4的开发，并开创性地提出了STaR算法， 这是首个通过自我生成的推理链来训练语言模型进行推理的算法。目前，Eric Zelikman担任Humans&的CEO。 Humans&创始团队（图源：Humans&官网） Humans&的核心理念是：AI应该赋能人类，而不是取代人类。创始人们称，他们的目标是开发一种促进 ...

Market Landscape of Consumer AI in 2025 - The consumer AI market in 2025 is characterized by a "winner-takes-most" trend, with OpenAI and Google leading the charge in product launches and user engagement [3][5] - ChatGPT is currently the dominant player with weekly active users estimated between 800 million to 900 million, while Gemini's user base is approximately 35% of ChatGPT's on the web and 40% on mobile [4][6] - Only 9% of users are willing to pay for more than one product among leading LLMs like ChatGPT, Gemini, Claude 3, and Cursor, indicating a strong preference for a single dominant platform [5] Product Innovations and Core Technologies - Significant advancements in image and video generation models have been made, particularly in realism and reasoning capabilities, allowing for more lifelike and coherent outputs [10][11] - OpenAI's ChatGPT-4o and Google's VO series models, including Nano Banana, have gained substantial popularity, showcasing the competitive landscape of product offerings [8][9] - The integration of search capabilities into models like Nano Banana enhances their functionality, allowing for more accurate and contextually relevant outputs [12] User Experience and Product Design - The design of consumer AI products is crucial, with successful applications needing to balance content creation and consumption, as seen in platforms like TikTok and YouTube [33] - ChatGPT's user interface is noted for its engaging design, which encourages user interaction and exploration of features, contrasting with Gemini's more utilitarian approach [24][25] - The potential for "super apps" that integrate various functionalities is highlighted, with ChatGPT aiming to leverage its high user engagement for proactive service offerings [16][40] Competitive Dynamics and Emerging Players - Emerging players like Perplexity and Grok are making strides in the market, with Perplexity's Comet browser showing impressive user retention and engagement [20][21] - The competitive landscape is evolving, with companies like Anthropic focusing on niche markets and specialized user needs, while also facing challenges in broader consumer adoption [34][36] - Meta and Grok are also recognized as challengers, with Grok rapidly advancing in image and video generation capabilities, indicating a dynamic and competitive environment [37][39] Predictions for 2026 - The enterprise market is expected to see significant growth for ChatGPT, with a reported 7-8 times increase in enterprise users, which may drive further consumer adoption [40][41] - The trend towards multi-modal capabilities in AI is anticipated to continue, with expectations for models to handle diverse input types and generate rich, varied outputs [43][44] - Initial explorations into generative technologies by leading firms may pave the way for innovative applications, allowing startups to leverage advanced models for niche market opportunities [42][45]

韩国《关于 人工智能发展和构建信赖基础的基本法》1月22日起正式施行。该法规定，AI技术与服务提 供商在提供利用"高影响力AI"或生成式AI的产品或服务时，须提前告知用户该产品或服务基于相关技术 运行，并明确进行标注。与此同时，《基本法》还规定了AI须具备可解释性属性。 ...

年底各大厂裁员消息满天飞，看似就业行情见底、机会变少，其实是：程序员的 高价值赛道变了 ！ 2026年，真正 稀缺 、 高薪 、 抗风险 的岗位，只有一个—— 大模型应用开发工程师 ！ 百度、华为重组AI项目架构， 全力投入应用层 腾讯三季度疯 狂扩招3000人 ，狂揽AI人才 DeepSeek年 薪154w 招大模型应用开发…… 这一切只说明一件事：大模型竞争，已从技术储备进入"应用落地"阶段了！如果你还只停留在"调API、写 Prompt"，很快会被淘汰…… 企业不缺大模型， 缺的是能 "把AI真正用起来的人" ——能交付企业级AI产品、解决实际业务难题的开发者！ 你不需要从头造AI，只需： 完课附赠求职大礼包：经典面试题库（笔试+面试）、还有高薪岗位解读、企业内推、直聘权益！！ 掌握AI大模型技术 开启高薪之路！ 「大模型应用开发实战营」 AI 技术原理 + 实战应用 + 职业发展 」 扫码 0元 报名 仅限 100 人 24小时 后关闭通道！速来！ 完课后还可领《大模型应用案例集》《 AI 商业落地白皮书》 ✅ 掌握 大模型应用开发 的核心逻辑 ✅学习完整 技术体系 ： —— Fine-tuning ...

0:00 《新华每日电讯》1月22日刊发文章《我国人工智能企业数量超6000家》。 2025年，我国人工智能产业活力迸发、亮点纷呈。国内企业发布多款人工智能芯片产品，智能算力规模 达1590EFLOPS，国内大模型引领全球开源生态，人工智能企业数量超过6000家，核心产业规模预计突 破1.2万亿元。 新华社音视频部制作 记者：周圆、王舒一 ...

Summary of OpenAI Conference Call Industry Overview - **Industry Focus**: Artificial Intelligence (AI) and its applications across various sectors including enterprise software, services, infrastructure, advertising, commerce, and hardware [1][2] - **Market Opportunity**: OpenAI is targeting a market opportunity exceeding **$3.5 trillion**, driven by the efficiency improvements in the **$60 trillion** global labor market [2][4] Company Insights - **OpenAI's Position**: OpenAI is seen as a foundational layer for the next era of computing, with a focus on creating a full-stack, AI-first cloud service for enterprises and a suite of AI tools for consumers [1] - **Revenue Growth**: The company is expected to scale revenue through enterprise adoption, subscriptions, and new product offerings, with a current partner ecosystem valued at **$1.4 trillion** [1][4] - **User Base**: OpenAI has **900 million** weekly active users, with significant growth in user engagement [1][23] Competitive Landscape - **Competition**: OpenAI faces intense competition from major tech companies like Google, Amazon, and Microsoft, which have rapidly developed their own AI models and services [3][12] - **Market Dynamics**: Unlike previous tech innovations, OpenAI's ChatGPT did not have a grace period before competitors entered the market, leading to a highly competitive environment [3][12] Financial Aspects - **Funding**: OpenAI has raised over **$60 billion** in funding, with significant commitments needed to support its ambitious infrastructure and ecosystem goals [15][20] - **Valuation**: The company's valuation has surged from **$157 billion** to **$500 billion**, with projections suggesting it could reach **$750 billion** or more [50][51] Enterprise and Consumer Markets - **Enterprise Market**: OpenAI aims to capture a share of the **$1.2 trillion** enterprise AI total addressable market (TAM) through subscriptions, APIs, and agents [4][52] - **Consumer Market**: The consumer TAM is estimated at **$2.29 trillion**, encompassing subscriptions, agentic commerce, and digital advertising [5][52] Challenges and Risks - **Execution Risks**: OpenAI faces high execution risks due to the complexity of building and deploying new technology while navigating a competitive landscape [20][21] - **Funding Sustainability**: The company must manage its funding effectively to compete against larger firms that may operate at a loss to undermine OpenAI's financial stability [21] Strategic Vision - **Long-term Goals**: OpenAI's vision includes becoming the preeminent operating system for AI, integrating various applications and services to enhance user experience and productivity [38][40] - **Ecosystem Development**: The company has built a robust ecosystem of partners and investors, which is crucial for its competitive positioning and operational success [23][28] Conclusion - OpenAI is positioned as a leader in the AI space with significant growth potential, but it must navigate a complex competitive landscape and manage substantial financial commitments to realize its vision and maintain its market position [1][20][66]

January 21, 2026 06:57 AM GMT Tech Bytes | Asia Pacific M Idea DeepSeek – Doing More With Less DeepSeek's latest innovation of Engram module reduces HBM constraints and infrastructure costs via decoupling storage from compute. This could address China's AI computing constraints, and demonstrates that the next AI frontier may not be simply bigger models but efficient hybrid architectures. More mileage out of scarce GPU resources. DeepSeek decoupling "Conditional Memory" from compute (Engram) unlocks a new le ...

Summary of Key Points from the Conference Call Industry and Company Overview - The discussion revolves around **Agentic AI** frameworks, which enhance traditional Large Language Models (LLMs) by integrating decision-making orchestrators and external tools, transforming them into autonomous problem solvers [2][4]. Core Insights and Arguments - **Agentic AI Workloads**: The paper profiles five representative agentic AI workloads: **Haystack RAG**, **Toolformer**, **ChemCrow**, **LangChain**, and **SWE-Agent**. These workloads are analyzed for latency, throughput, and energy metrics, highlighting the significant role of CPUs in these metrics compared to GPUs [3][10][20]. - **Latency Contributions**: Tool processing on CPUs can account for up to **90.6%** of total latency in agentic workloads, indicating a need for joint CPU-GPU optimization rather than focusing solely on GPU improvements [10][34]. - **Throughput Bottlenecks**: Throughput is bottlenecked by both CPU factors (coherence, synchronization, core over-subscription) and GPU factors (memory capacity and bandwidth). This dual limitation affects the performance of agentic AI systems [10][45]. - **Energy Consumption**: At large batch sizes, CPU dynamic energy consumption can reach up to **44%** of total dynamic energy, emphasizing the inefficiency of CPU parallelism compared to GPU [10][49]. Important but Overlooked Content - **Optimizations Proposed**: The paper introduces two key optimizations: 1. **CPU and GPU-Aware Micro-batching (CGAM)**: This method aims to improve performance by capping batch sizes and using micro-batching to optimize latency [11][50]. 2. **Mixed Agentic Workload Scheduling (MAWS)**: This approach adapts scheduling strategies for heterogeneous workloads, balancing CPU-heavy and LLM-heavy tasks to enhance overall efficiency [11][58]. - **Profiling Insights**: The profiling of agentic AI workloads reveals that tool processing, rather than LLM inference, is the primary contributor to latency, which is a critical insight for future optimizations [32][34]. - **Diverse Computational Patterns**: The selected workloads represent a variety of applications and computational strategies, showcasing the breadth of agentic AI systems and their real-world relevance [21][22]. Conclusion - The findings underscore the importance of a CPU-centric perspective in optimizing agentic AI frameworks, highlighting the need for comprehensive strategies that address both CPU and GPU limitations to enhance performance, efficiency, and scalability in AI applications [3][10][11].

截至2026年1月22日 10:13，创业板人工智能ETF南方(159382)上涨2.21%，成交3496.02万元。跟踪指数 创业板人工智能指数成分股深信服上涨10.83%，万兴科技上涨4.84%，润泽科技上涨4.72%，天孚通 信，蓝色光标等个股跟涨。 消息面上，1月20日，国新办举行新闻发布会介绍2025年工业和信息化发展成效。相关负责人表示，目 前人工智能（AI）已渗透领航级智能工厂70%以上的业务场景，沉淀了超6000个垂直领域模型，带动 1700多项关键智能制造装备和工业软件规模化应用，形成一批具备感知、决策和执行能力的工业智能 体，推动智能制造从自动化向自主化改进。 据业内消息，在DeepSeek-R1发布一周年之际，新模型"MODEL1"的项目名在开源社区悄然出现。近 日，DeepSeek官方在GitHub更新了一系列FlashMLA代码，项目文件有数十处都提到了此前未公开 的"MODEL1"大模型标识符。 国联民生证券指出，2026年全球大模型仍处于加速迭代周期，中国AI发展具备强劲竞争力。国内方 面，DeepSeek有望在春节期间发布新一代模型，同时头部科技企业资本支出持续提升，为模型能力 ...

Group 1 - The core point of the article is the establishment of Yangzhou Artificial Intelligence Co., Ltd. with a registered capital of 100 million yuan [1] - The company's business scope includes the development of basic software, application software, theoretical and algorithm software related to artificial intelligence, as well as the sale of artificial intelligence hardware [1] - Yangzhou Big Data Group Co., Ltd. is the sole shareholder of Yangzhou Artificial Intelligence Co., Ltd. [1]