Core Insights - The article highlights the success story of Maor Shlomo and his product Base44, which is an AI-powered no-code platform that allows users to generate full-stack applications using natural language, achieving significant user growth and a successful exit in just six months [2][6][7]. Group 1: Product Development and Unique Approach - Base44 was developed to address real user needs, with 90% of its code generated by AI, showcasing a unique approach in the competitive AI startup landscape [2][6]. - The platform allows users to create applications without needing to integrate third-party services, providing a "self-contained" experience [6][7]. - The initial motivation for creating Base44 stemmed from personal experiences, including the challenges faced while building a website for a girlfriend's art studio and the software needs of a large volunteer organization [10][11][12]. Group 2: User Acquisition and Growth Strategies - The initial user base was built through personal connections, with early adopters providing feedback and sharing the product with others, leading to organic growth [15][16]. - The concept of "Build in Public" was effectively utilized, where sharing progress and updates on platforms like LinkedIn helped in gaining community support and user engagement [19][23]. - The product saw rapid user growth, reaching 4000 new users per day after implementing community-driven initiatives and incentives for sharing [20][19]. Group 3: Insights on Entrepreneurship and Market Dynamics - The article emphasizes that independent entrepreneurship can be advantageous in certain markets, especially when products have viral potential and can achieve product-market fit [38][42]. - It discusses the importance of focusing on tasks that align with personal strengths and interests, suggesting that at least 50% of time should be spent on enjoyable and proficient activities to maintain motivation [48][49]. - The narrative also reflects on the changing landscape of entrepreneurship, where smaller teams can leverage AI to compete effectively against larger companies, diminishing the absolute advantage of team size and funding [42][39].

明敏 克雷西 发自 凹非寺 量子位 | 公众号 CVPR 2025奖项出炉！谢赛宁苏昊齐获青年学者奖。 该奖项面向 获得博士学位不超过7年 的早期研究工作者，表彰他们在计算机视觉领域的 杰出研究贡献 。 其中，苏昊是 李飞飞 的博士生，他参与了对计算机视觉领域鼎鼎有名的 ImageNet 。 谢赛宁以一作身份和 何恺明 合作完成ResNeXt，同时也参与了MAE，都是计算机视觉领域影响深远的工作。 最值得关注的CVPR 2025 最佳论文奖 也新鲜出炉！ 今年只有一篇论文获奖： 《VGGT: Visual Geometry Grounded Transformer》 ，由Meta和牛津大学联合提出，第一作者为牛津大学 Meta联培博士王建元。 VGGT是首个能在单次前馈中端到端预测完整3D场景信息的大型Transformer，性能超越多项现有几何或深度学习方法，具有广泛的应用潜 力。 Best Student Paper 颁给《Neural Inverse Rendering from Propagating Light》，由多伦多大学、卡内基梅隆大学等联合带来。 它首次提出针对从多视角、时间分辨的光传播视频 ...

机器之心报道 机器之心编辑部 刚刚，在美国田纳西州纳什维尔举办的 CVPR 2025 公布了最佳论文等奖项。 今年共有 14 篇论文入围最佳论文评选，最终 5 篇论文摘得奖项 ，包括 1 篇最佳论文 、 4 篇最佳论文荣誉提名 。此外，大会还颁发了 1 篇最佳学生论文 、 1 篇最 佳学生论文荣誉提名 。 根据会方统计，今年大会共收到 4 万多名作者提交的 13008 份论文。相比去年（11532），今年的投稿数量增长了 13%，最终有 2872 篇论文被接收，整体接收率 约为 22.1%。在接收论文中，Oral 的数量是 96（3.3%），Highlights 的数量是 387（13.7%）。 计算机视觉技术的火热给大会审稿带来了空前的压力。本届投稿作者数量、论文评审者和领域主席（AC）数量均创下新高。 今年前来现场参会的学者也超过 9000 人，他们来自 70 余个国家和地区。 CVPR 官方公布了各个细分领域的论文接收情况，如下图所示。可以看到，图像与视频生成领域今年度的论文接收数量最多，而接收率最高的领域则是基于多视角 和传感器的 3D 以及基于单图像的 3D。 此次，最佳论文奖委员会成员中有 AI ...

Core Insights - Pixelworks has announced a strategic collaboration with PerfDog to introduce the "Frame Generation" index, a new benchmark for gaming performance evaluation that aims to redefine mobile game testing standards in the AI era [1][2][4] Group 1: Collaboration and Development - The collaboration between Pixelworks and PerfDog has led to the development of the Frame Generation index, which enhances performance testing capabilities for mobile games [1][2] - PerfDog 11.1 integrates the Frame Generation index, providing developers with richer and more precise testing data on smartphones equipped with Pixelworks' hardware rendering accelerators [1][4] Group 2: Industry Challenges and Solutions - Traditional mobile game performance testing often relies on average frame rate and frame stability, which limits the industry's ability to optimize gaming performance accurately [3] - The introduction of the hardware-accelerated frame rate evaluation standard by Pixelworks and PerfDog addresses these challenges by enabling real-time visualization of post-acceleration frame rate data [4] Group 3: Impact on Developers and Players - The new Frame Generation index allows developers and OEMs to identify rendering bottlenecks more precisely, streamlining performance optimization [4] - For gamers and reviewers, this index provides reliable measurements of system stability and visual smoothness, facilitating intuitive performance assessments [4] Group 4: Company Background - Pixelworks has over 20 years of experience in delivering visual processing innovations across various platforms, including consumer electronics and video streaming services [8] - PerfDog is recognized for its performance testing and analysis capabilities, supporting developers in optimizing application performance through real-time data monitoring and diagnostics [6]