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Labubu后,一款AI“毛球”潮玩火了:朱啸虎押注,定价399元开售就卖爆
量子位· 2025-06-28 05:09
Core Viewpoint - The article discusses the rapid success of a domestic AI toy named Fuzozo, highlighting its impressive sales performance and recent funding developments [1][2][3]. Group 1: Product Overview - Fuzozo, also known as 芙崽, features a cute design with large eyes and a fluffy appearance, available in five colors corresponding to the five elements of Chinese philosophy [4][5]. - The product is designed to appeal primarily to women aged 18-35, addressing their emotional needs for companionship through AI interaction [10][11]. Group 2: Sales and Market Performance - Fuzozo achieved over 1,000 orders within 10 minutes of its first pre-sale during the 618 shopping festival, ranking just behind established brands like Pop Mart and Miniso in the toy category on JD.com [2]. - The company behind Fuzozo, 洛博智能, has secured several million yuan in angel funding from notable investors, including 上影新视野基金 and 金沙江创投 [3]. Group 3: User Engagement and Subscription Model - The initial purchase price of Fuzozo is set at 399 yuan, which includes a daily free interaction quota, with additional subscription fees required for extended use [16][19]. - The product aims to foster emotional connections, encouraging users to pay for ongoing interaction once they establish a bond with Fuzozo [17][18]. Group 4: Unique Features and Technology - Fuzozo incorporates a long-term memory system that allows it to remember user interactions, enhancing the emotional connection and user experience [54][56]. - The product's design emphasizes a balance between physical interaction and voice communication, ensuring a rich user experience while managing costs and power consumption [70][71]. Group 5: Development and Iteration - The company conducted internal testing before the official launch, gathering valuable user feedback to refine the product [34][35]. - Significant improvements have been made since the initial prototype showcased at MWC, including enhancements in product design, hardware, and app functionality [40][42][44]. Group 6: Emotional Connection and Market Differentiation - Fuzozo's unique selling proposition lies in its ability to create a deep emotional bond with users, distinguishing it from other AI toys that lack a comprehensive understanding of long-term interactions [64][66]. - The product's design and functionality are tailored to provide a nurturing and healing experience, positioning it as more than just a toy but as a companion for users [27][66].
航空发动机用上大模型:解决复杂时序问题,性能超越ChatGPT-4o实现SOTA|上交创智复旦
量子位· 2025-06-28 04:42
ITFormer团队 投稿 量子位 | 公众号 QbitAI 时序数据分析在工业监控、医疗诊断等领域至关重要。 比如航空发动机监控这个复杂工业场景中,工程师需分析海量多通道传感器数据,以判断设备状态并制定维护决策。 然而,现有研究多聚焦于分类、预测等单一任务,与实际工业场景中专家通过自然语言进行复杂交互和决策的需求存在显著差异。 上海交通大学航空航天学院李元祥教授团队 、上海创智学院、复旦大学数据科学学院团队以航空发动机运维为背景,提出 高效、可迁移的时 序-语言桥接架构—— ITFormer ,将专家诊断过程抽象为"理解、感知、推理、决策"四个认知层次,并首次系统性地定义为"时序问答"任务 范式。 团队 基于NASA航空发动机数据,构建了包含11万余问答对的EngineMT-QA数据集。 该数据集的任务设计紧密贴合专家的认知流程,为评 估模型在真实工业场景下的推理能力提供了首个标准化基准。 结果显示,ITFormer以模块化设计实现了时序数据与大语言模型的高效融合,仅需训练不足1%的额外参数,便可在通用时序问答数据集上表 现出优越的性能和良好的迁移能力,展现了卓越的"即插即用"特性。 它可无缝适配Patch ...
拯救P图废柴,阿里上新多模态模型Qwen-VLo!人人免费可玩
量子位· 2025-06-28 04:42
Core Viewpoint - Alibaba has launched a new multimodal model, Qwen-VLo, which significantly enhances its image generation and understanding capabilities, outperforming previous models like GPT-4o in certain aspects [1][2]. Group 1: Model Features - Qwen-VLo supports arbitrary resolutions and aspect ratios, allowing for flexible input and output formats [2]. - The model exhibits improved understanding capabilities, not only in image generation but also in image recognition and interpretation [10][11]. - Enhanced detail capture and semantic consistency are key features, enabling users to edit images with a single command [11][12]. Group 2: User Experience and Testing - Users can generate images in a "series" format, allowing for continuous and coherent image creation [4][15]. - The model can perform complex editing tasks, such as replacing objects in images while maintaining background consistency [22][30]. - Qwen-VLo's progressive image generation method allows for real-time adjustments, enhancing the final output's harmony and visual appeal [56][58]. Group 3: Community Engagement - The model is currently available for free, encouraging users to experiment and share their creations [13][65]. - Users have demonstrated various creative applications, such as coloring sketches and generating themed images [59][62].
小扎千亿挖人名单下一位:硅谷华人AI高管第一人
量子位· 2025-06-28 04:42
Core Insights - Meta, led by Mark Zuckerberg, is aggressively recruiting AI talent, including those previously poached by competitors like OpenAI and Google [1][2] - Zuckerberg is reaching out to former Meta AI executives and researchers to encourage their return to the company [3][4] - The urgency in Meta's recruitment efforts is highlighted by the recent struggles of its AI projects, particularly the Llama 4 model [18][22] Recruitment Strategy - Meta has restructured its AI teams into two main groups: an AI product team and an AGI Foundations team [25][28] - A new superintelligence lab has been established to develop AI systems that surpass human cognitive abilities [29] - The company is willing to offer substantial compensation packages, reportedly reaching up to $100 million for top talent [33][34] Competitive Landscape - Bill Jia, a prominent AI figure who left Meta for Google, has been instrumental in Google's AI advancements, making his return to Meta uncertain [8][10][17] - Google has made significant strides with its Gemini models, contrasting with Meta's recent setbacks [11][18] - Meta's AI department has expanded to over a thousand employees, reflecting its commitment to rebuilding its capabilities [32] Financial Moves - Meta has made substantial investments, including a $14.3 billion acquisition of a stake in Scale AI and attempts to acquire other AI startups [37] - The company is actively pursuing high-profile AI talent, with reports of multiple recruitment efforts targeting OpenAI researchers [38][40] Future Outlook - Despite recent challenges, Meta remains committed to its open-source strategy and plans to continue developing the Llama series [44] - The competitive landscape in AI is intensifying, with both Meta and Google focusing on innovative models and talent acquisition [45]
Anthropic最新研究:Claude正悄悄进化为“情绪价值大师”
量子位· 2025-06-27 10:57
时令 发自 凹非寺 量子位 | 公众号 QbitAI 你有没有试过,深夜心情低落时,对着AI倾诉? Anthropic 最新研究发现,越来越多成年人正把AI当作情感陪伴。 而Claude,正在悄悄成为那个"温柔倾听"的存在。 △ Claude中不同情感类互动类型及其占比 研究显示,人们在面临更深层次的情感挑战时,例如存在恐惧、长期孤独和难以建立有意义的关系时,他们会明确地向Claude寻求陪伴。 Claude拒绝用户请求的情况非常少(不到10%),而当它确实这么做时,通常是出于保护用户免受潜在伤害的考虑。 也是很贴心了。 那么,Claude究竟是如何成为"情绪价值大师"的呢? Clio工作原理:大规模隐私保护分析 研究团队从Claude免费和专业账户约450万次对话中,提取出了 131484 条与情感相关的对话。 为了规避掉用户隐私问题,Claude专门使用了一种名为 Clio 的自动分析工具, 能够在保护用户隐私的前提下,深入了解其真实世界的使用 情况。 Clio采用了一种自下而上的方法,通过自动聚类对话主题,识别真实使用模式。 不同于传统依赖预设问题的安全策略,Clio无需预先设定关注点。 整个过程在严格 ...
你的扫描全能王,作价217亿冲刺港股IPO
量子位· 2025-06-27 10:57
Core Viewpoint - The company, Shanghai Hehe Information Technology, is aiming to become the "first stock of intelligent text recognition" in Hong Kong, following its previous listing on the A-share Sci-Tech Innovation Board. The company has shown significant growth in revenue and user engagement, positioning itself as a leader in the AI sector with a focus on text intelligence technology [2][3][4]. Financial Performance - In 2024, the company reported a revenue of 1.438 billion RMB, a net profit of 400 million RMB, and a gross margin of 84.3% [4][25]. - The revenue growth from 2022 to 2024 was approximately 21% CAGR, with revenues of 989 million RMB, 1.187 billion RMB, and 1.438 billion RMB respectively [25]. - The C-end business accounted for a significant portion of total revenue, with contributions of 82.2%, 84.3%, and 83.8% from 2022 to 2024 [27]. User Engagement - The monthly active users (MAU) for C-end products reached 171 million in 2024, with a paid user ratio of 4.3% [21]. - The company ranks first in China and fifth globally among efficiency AI companies with MAU exceeding 100 million [21][22]. Product Portfolio - The company offers a range of products targeting both C-end and B-end markets, including "Scan All-in-One" and "Business Card All-in-One" for C-end, and "TextIn" and "Qixin Huayan" for B-end [8][12]. - The core technology is based on multi-modal text intelligence, which enhances efficiency in various applications [14][15]. Market Position - The company is positioned as a leading AI firm with a focus on text recognition and processing, competing with major players like OpenAI, Google, Adobe, and Microsoft [5][6][21]. - The global AI product market is projected to grow significantly, with estimates of 46.5 billion USD in 2024 and 228 billion USD by 2029, indicating a robust growth trajectory for the industry [66]. Research and Development - The company has been increasing its R&D investment, with expenditures of 280 million RMB, 323 million RMB, and 390 million RMB from 2022 to 2024, representing about 27% of total revenue [33]. - The workforce consists of 1,053 employees, with 60.6% in R&D roles, highlighting the company's commitment to innovation [35]. Future Plans - The funds raised from the Hong Kong listing will primarily be used for R&D, international expansion, and exploring investment and acquisition opportunities [50].
紫东太初开源视觉神经增强方法,即插即用终结多模态幻觉 | ACL 2025
量子位· 2025-06-27 10:57
Core Viewpoint - The article discusses a novel solution, Visual Head Reinforcement (VHR), to address the hallucination phenomenon in Large Visual Language Models (LVLMs) by enhancing the model's attention mechanisms to better utilize visual information rather than relying on language priors [1][2][3]. Group 1: Introduction and Background - LVLMs often generate factually incorrect outputs due to an over-reliance on language knowledge instead of actual visual content, leading to hallucinations [4][5]. - Experiments show that when models are prompted to describe images, they frequently include entities not present in the images, indicating a systemic reliance on language co-occurrence patterns [4][5][7]. Group 2: VHR Methodology - VHR identifies and strengthens attention heads that are sensitive to visual information, thereby reducing the model's dependency on language priors and significantly lowering hallucination occurrences [8]. - The Visual Head Divergence (VHD) metric is introduced to quantify each attention head's sensitivity to visual inputs, revealing that only a few heads are responsive to visual information while most rely on language patterns [9][11]. - The VHR process involves filtering out abnormal VHD scores, selecting and scaling the outputs of the top 50% of attention heads based on VHD scores, and applying a layer-wise enhancement strategy to avoid interference [14][15][16]. Group 3: Experimental Results - VHR has been tested against multiple benchmarks, showing superior performance compared to existing methods while maintaining efficiency with minimal additional time costs [16][17]. - The results indicate that VHR outperforms baseline methods in various evaluations, demonstrating its effectiveness in reducing hallucinations in LVLMs [17]. Group 4: SSL Method - The article also introduces a Semantic Guided Learning (SSL) method that analyzes the internal representation space of models to mitigate hallucinations by injecting real semantic directions and suppressing hallucination-related projections [19][22]. - This method shows cross-model applicability, enhancing the robustness of hallucination mitigation across different LVLM architectures [22].
谷歌AI试穿神器真神了!上传照片秒出OOTD,视频效果和照镜子没区别
量子位· 2025-06-27 08:09
闻乐 发自 凹非寺 量子位 | 公众号 QbitAI 担心网购衣服不合身?谷歌帮你云试穿! 谷歌推出最新应用 Doppl ,只需要上传一张照片,随时随地都能看到喜欢的衣服"穿"在自己身上。 还能选择生成动态视频看效果,再也不用试衣间门口排长队了。 这和照镜子有什么区别!甚至看后背比照镜子转身扭头还轻松(doge)。 谷歌负责虚拟试穿、购物生成式视觉的首席科学家ira kemelmacher晒出了自己的试穿效果: 网友们也来测试了一下 (右边是网友自己找的想试穿的衣服图片,左边是Doppl试穿效果) : 任何人任何时间任何地点,云逛街这不就来了~ 不仅能"试穿",还能帮忙搭配 只不过,先前推出的这个功能只支持"静态试穿"。而现在的Doppl支持 "动态试穿" ,效果更直观。 有网友"试穿"后问有没有什么使用建议能达到最佳效果,官网也来积极回应。 这里给大家总结一下。 首先,上传一张仅包含本人的全身照(确保从头顶到脚部),照片服装尽量选贴身服装,以便后续能生成更真实的效果,如果没有合适的照 片,也可以使用Doppl预设的AI模特。 然后,在选择"衣服"的照片时,尽量选择光线自然,无过多褶皱的衣服,如果是模特截图, ...
OpenAI连丢4位大将!Ilya合作者/o1核心贡献者加入Meta,苏黎世三人组回应跳槽:集体做出的选择
量子位· 2025-06-27 08:09
梦晨 发自 凹非寺 量子位 | 公众号 QbitAI 扎克伯格未免有点太针对奥特曼了! 又有OpenAI核心研究员被挖走,而且做的是最前沿推理大模型。 最新跳槽到Meta的是 Trapit Bansal ,他在2022年加入OpemnAI, 曾与Ilya合作,在大模型强化学习研究的启动过程中发挥了关键作用 , 也被列为 o1的核心贡献者 。 △ Trapit Bansal 加入Meta后,Trapit Bansal在新成立的超级智能部门继续研究推理大模型。 Trapit Bansal博士毕业于马萨诸塞大学阿默斯特分校。 毕业后他加入OpenAI,与Ilya合作启动了强化学习在推理大模型上的研究。 目前他在谷歌学术上有2800+被引用数量,多篇论文与Ilya合著。 读博期间他就在OpenAI实习过,参与了多智能体强化学习研究:通过自我对弈让AI发现新的技能,无需专门为这些技能设计奖励。 | Trapit Bansal | | FOLLOW | | GET MY OWN PROFILE | | | --- | --- | --- | --- | --- | --- | | OpenAl | | | | | | | ...
DeepSeek-R2为什么还没发?
量子位· 2025-06-27 08:09
Core Viewpoint - The release of DeepSeek-R2 has been delayed due to CEO Liang Wenfeng's dissatisfaction with its performance and a shortage of Nvidia H20 chips, which are critical for its development [1][2][4]. Development Timeline - The anticipation for R2 began after the release of the DeepSeek-V3 model in December last year, which was considered a benchmark for cost-performance [5]. - An upgrade to V3 was announced in March 2023, leading to speculation that R2 would be released in April [11]. - Despite the release of a paper on scaling laws in early April, there has been no official update on R2 since then [12][16]. Technical Specifications - R1's training utilized 30,000 H20 chips, 10,000 H800 chips, and 10,000 H100 chips, indicating the significant computational resources required for R2 [3]. - Leaked parameters for R2 suggested it would have 1.2 trillion parameters and utilize 5.2 petabytes of training data, although the authenticity of these claims remains uncertain [17]. Community Reactions - Following the news of the delay, community responses varied, with some expressing belief that the delay is justified, while others speculated that R2 might wait for the release of V4 [26][30].