Core Insights - The article highlights various innovative AI-driven tools and platforms that cater to different market needs, emphasizing their unique value propositions and user benefits [3][8][12]. Group 1: Chat4Data - Chat4Data is an AI-based Chrome extension designed to simplify web data scraping for non-technical users, allowing them to extract structured data using natural language without coding [3]. - The tool addresses the complexities and technical barriers of traditional web scraping tools, capitalizing on the growing demand for data-driven decision-making and automation [3]. - It features a chat-based workflow, automatic handling of pagination, and strong compatibility with various list-type websites [3]. Group 2: Embedded iPaaS from Albato - Embedded iPaaS from Albato is an AI-driven platform that offers over 800 white-label integrations for SaaS products, aimed at reducing development and maintenance costs [8]. - It targets SaaS companies looking to enhance user engagement and market competitiveness, particularly small teams and startups [8]. - The platform addresses the long development cycles and high resource consumption associated with traditional API integrations [8]. Group 3: Cursor 1.0 - Cursor 1.0 is an AI-powered code editor that integrates automated code review and multi-scenario collaboration capabilities [12]. - It aims to enhance developer productivity and code quality, addressing efficiency bottlenecks in traditional code editors [12]. - Key features include automated bug detection, code memory functionality, and support for Jupyter Notebook [12]. Group 4: SocLeads 2.0 - SocLeads 2.0 is a no-code tool for efficient email scraping and lead generation across multiple social media platforms [17]. - It allows users to extract potential customer emails quickly and efficiently, addressing the challenges of traditional lead generation processes [17]. - The tool maintains a low email bounce rate, ensuring data validity and quality [17]. Group 5: Socialprofiler - Socialprofiler is an intelligent profiling tool that leverages public social data to help users understand others' interests and potential risks [21]. - It generates detailed interest profiles across various platforms, assisting users in making informed decisions in social interactions [21]. - The tool emphasizes transparency in handling privacy and misjudgment issues [21]. Group 6: Thiings - Thiings is a free, customizable AI-generated 3D icon library aimed at designers and developers [25]. - It offers over 1900 free icons and allows users to create custom icons, addressing the challenges of sourcing high-quality visual materials [25]. - The platform promotes community engagement through a flexible points system for icon generation [25]. Group 7: Long - Long is a decentralized crowdfunding platform for early-stage startup projects, allowing anyone to participate without approval [30]. - It aims to break down traditional barriers to entry in venture capital, facilitating immediate funding and user feedback for projects [30]. - The platform emphasizes a simple onboarding process and community-driven growth [30]. Group 8: VidAU - VidAU is an AI creative platform that enables e-commerce and marketing professionals to generate high-conversion video ads quickly [33]. - It addresses the challenges of traditional video ad production, such as high costs and lengthy timelines [33]. - The platform features AI-driven templates and a rich media library, allowing users to create diverse ads without manual editing [33]. Group 9: Wispr Flow for iOS - Wispr Flow is a voice input and smart text generation tool for iPhone users, enhancing writing efficiency across apps [39]. - It allows users to achieve four times the writing speed compared to typing, addressing common mobile input challenges [39]. - The tool features seamless voice input, real-time error correction, and privacy-focused design [39]. Group 10: Knowledge - Knowledge is a sales intelligence platform that helps B2B sales teams identify high-intent customers using behavioral and psychological data [42]. - It provides personalized communication guidance to enhance conversion rates and customer interactions [42]. - The platform focuses on data-driven sales processes and optimizing customer relationship management [42].

Core Viewpoint - Multiverse Computing has successfully raised €189 million (approximately $215 million) in a Series B funding round, leveraging its technology "CompactifAI" to compress large language models (LLMs) significantly while maintaining performance [1][2]. Group 1: Funding and Investment - The Series B funding round was led by Bullhound Capital, with participation from various investors including HP Tech Ventures, SETT, Forgepoint Capital International, CDP Venture Capital, Santander Climate VC, Toshiba, and the Basque venture capital group [1]. - To date, the company has raised approximately $250 million in total funding [2]. Group 2: Technology and Product Offering - CompactifAI is a compression technology inspired by quantum computing, capable of reducing the size of LLMs by up to 95% without compromising model performance [2]. - Multiverse offers compressed versions of well-known open-source LLMs, including Llama 4 Scout, Llama 3.3 70B, Llama 3.1 8B, and Mistral Small 3.1, with plans to release more models soon [2]. - The company claims that its models operate 4 to 12 times faster than uncompressed versions, with inference costs reduced by 50% to 80% [3]. Group 3: Market Applications and Accessibility - Some of Multiverse's models are designed to be compact and energy-efficient, enabling them to run on personal computers, smartphones, cars, drones, and even Raspberry Pi devices [3]. - The Llama 4 Scout Slim version costs $0.10 per million tokens on AWS, compared to $0.14 for the original version, showcasing significant cost savings [3]. Group 4: Leadership and Expertise - The company is backed by strong technical expertise, with co-founder and CTO Román Orús known for his pioneering research in tensor networks, which are tools for simulating quantum computers on conventional machines [4]. - Co-founder and CEO Enrique Lizaso Olmos has a background in mathematics and extensive experience in the banking sector, previously serving as the Deputy CEO of Unnim Banc [4].

图片来源： Unsplash 据知情人士透露，OpenAI 已与沙特公共投资基金、印度信实工业集团及现有股东阿联酋 MGX，就参 与由软银主导的 400 亿美元新一轮融资进行商谈。这些投资者每家可能至少投入数亿美元。 • 本轮融资总额400亿美元，分两期执行——首期100亿美元已到位，二期300亿正在推进，沙特PIF、 印度信实、阿联酋MGX为主要谈判对象 • 领投方软银集团同时也在收购员工持股 OpenAI 正与沙特 PIF 及其他投资者洽谈融资 300 亿美元，以完成此前宣布的 400 亿美元融资轮。 此 轮融资对 ChatGPT 制造商的投前估值为 2600 亿美元。 OpenAI 已收到首期 100 亿美元全额注资， 其中除软银外其他投资者贡献了 25 亿美元。 红杉资本和安德森 ·霍洛维茨基金此前从其他股东处购入了 OpenAI 股份，新加坡主权财富基金 GIC 作为新晋投资者，在此轮融资中各自投入至少 2 亿美元。微软、 Thrive Capital 、 Coatue 、 Altimeter Capital 及老虎环球管理也参与了投资。 知情人士透露，得益于新增投资方加入，软银首轮出资额已从 4 ...

Core Insights - The article discusses the rise of Vibe Coding, a new AI-driven programming model that allows developers to focus on product innovation and user experience rather than being constrained by programming languages, with AI generating executable code from natural language inputs [2][3]. Group 1: Supabase Overview - Supabase, founded in 2020, is an open-source alternative to Google Firebase, providing backend services such as database management, authentication, and real-time capabilities, which significantly reduce the complexity and time required for backend development [3][6]. - The platform has gained substantial traction, with over 170,000 developers in its community and more than 80,000 stars on GitHub, indicating its popularity and utility among developers [6][12]. Group 2: Key Features of Supabase - Supabase offers a PostgreSQL-based database that provides stable data storage and built-in authentication for precise user access control [3]. - The platform simplifies the login process through social account integration, allowing developers to quickly establish multi-channel authentication systems [4]. - Supabase automates backend resource management, enabling startups to reduce labor costs and accelerate product launches without the need for extensive code rewrites [4]. - It includes a storage solution that integrates seamlessly with its authentication and database services, allowing for secure and efficient content management [4]. - The real-time data synchronization feature supports collaborative tools and applications, ensuring consistent user experiences across multiple devices [4]. Group 3: Funding and Growth - Supabase completed a $200 million Series D funding round in April 2025, achieving a post-money valuation of approximately $2 billion, with participation from notable investors such as Accel and Coatue [6][13]. - Prior to this, Supabase raised $80 million in a Series C round in September 2024, reflecting a rapid increase in valuation from an estimated $900 million to $2 billion within seven months [13]. - The growth in funding and valuation highlights the company's rapid development in the open-source and AI programming sectors, driven by a growing developer community [13].

图片来源：火山引擎发布会 字节跳动旗下火山引擎，于6月11日举办Force原动力大会，本次大会正式发布了豆包大模型1.6、视频生成模型 Seedance 1.0 Pro等新模型，同时升级了AI Agent开发平台等云原生服务。 Z Highlight ： 字节跳动CEO梁汝波在会上强调："公司致力成为领先的创新科技企业，将坚定长期投入技术突破，并借力火山引擎持 续将前沿模型与能力向企业客户开放，赋能产业智能化转型。" 火山引擎谭待：豆包1.6跻身全球第一梯队，中国大模型份额近半 会上，豆包 1.6 模型披露多项权威测评成绩。在复杂推理、竞赛级数学、多轮对话和指令遵循等测试集上，豆包 1.6- thinking 的表现已跻身全球前列。 据火山引擎总裁谭待介绍，豆包 1.6 系列模型支持多模态理解和图形界面操作，能够理解和处理真实世界问题。此 前，豆包 1.5 的多模态能力在 60 个公开评测基准中取得 38 项最佳成绩，已广泛应用在电商识图、自动驾驶数据标 注、门店巡检等场景。图形界面操作能力则让豆包 1.6 进一步具备 " 行动力 " 。演示案例显示，豆包 1.6 可自动操作 浏览器完成酒店预定，识别购物小票 ...

Core Insights - The article discusses the transition from traditional Search Engine Optimization (SEO) to Generative Engine Optimization (GEO), highlighting the impact of large language models (LLMs) on search behavior and marketing strategies [3][5][21] - It emphasizes that the SEO market, valued at over $80 billion, is facing challenges as search behavior shifts from browsers to LLM platforms, fundamentally altering how exposure and content optimization are defined [3][5][9] Transition from Links to Language Models - Traditional search relied on link-based ranking, while GEO focuses on language and direct answers generated by models [4][5] - The average query length has increased significantly to 23 words, compared to just 4 words in traditional searches, indicating deeper user engagement [4] - LLMs provide personalized responses through memory and reasoning capabilities, changing the content discovery and optimization logic [4][5] New Metrics and Competitive Focus - The focus of competition has shifted from click-through rates to "model citation rates," where brands need to be encoded into AI layers to build new competitive barriers [5][12] - Emerging platforms like Profound and Goodie help brands analyze their presence in AI-generated answers and track sentiment in model outputs [12][13] Brand Strategy Evolution - A new brand strategy is emerging that prioritizes model recognition over public recognition, with "unprompted awareness" becoming a key metric in the AI era [12][14] - Tools like Ahrefs' Brand Radar and Semrush's AI toolkit are adapting to help brands monitor their visibility and mentions in generative platforms [13][14] The Rise of GEO Tools - GEO tools are not just about data measurement but also about actively shaping LLM behavior through insights and iterative feedback loops [20] - Companies that excel in GEO will create actionable infrastructures for real-time marketing activities and content optimization [20][21] Timing and Market Dynamics - The article notes that the transition to GEO is still in its early stages, with significant opportunities for brands to adapt as advertising budgets shift rapidly [21][22] - The ultimate question for marketers in the AI-driven landscape is whether models will remember their brands [22]

Core Insights - Vast Data is seeking a new round of financing with a target valuation of approximately $25 billion, a significant increase from its previous $9 billion valuation in December 2023 [1] - The company has raised a total of $381 million from various investors, including Fidelity Management & Research, Envision Ventures, Bond Capital, and Drive Capital [1] - Vast Data's technology focuses on eliminating traditional tiered storage architectures, particularly in the flash storage domain [1][2] Business Performance - The company's platform centralizes structured, semi-structured, and unstructured data, enhancing data retrieval speed and reportedly reducing costs for model training and inference [2] - Vast Data's annual recurring revenue (ARR) reached $200 million 18 months ago, with a year-over-year growth rate maintained between 2.5 to 3 times [2] - The company has achieved positive free cash flow for four consecutive years [2] Competitive Landscape - Competitors in the data storage sector include Pure Storage, valued at nearly $17 billion, and Weka, which completed a $140 million financing round at a $1.6 billion valuation [2] - Vast Data is also developing a database architecture to compete with Databricks products [2]

Group 1 - Glean, an enterprise search chatbot developer, raised $150 million in Series F funding led by Wellington Management, indicating investor optimism in the enterprise search market, which includes competitors like Amazon Web Services, Google, and Snowflake [1] - The funding round increased Glean's valuation to $7.2 billion, up from $4.3 billion in September last year, despite slower revenue growth compared to other AI startups [2] - Glean reported an annual recurring revenue (ARR) of over $100 million in Q4 last year, while OpenAI's ARR surged from $5.5 billion to $10 billion [2]

Core Viewpoint - The article discusses the rapid evolution of AI technology and its applications, highlighting the challenges of energy consumption, model size, and learning mechanisms. Aizip, a company focused on on-device AI models, aims to overcome these efficiency bottlenecks and drive the integration of AI into everyday life [1]. Group 1: AI Efficiency and Innovation - Aizip's mission is to enhance energy efficiency, model efficiency, and learning efficiency in AI systems, moving from "usable" to "efficiently usable" AI [3][10]. - The company emphasizes creating the "smallest and most efficient" AI systems, contrasting with the mainstream focus on general artificial intelligence (AGI) [3][14]. - Aizip's approach is to support businesses that require AI capabilities but lack full-stack AI expertise, allowing them to focus on application development [3][32]. Group 2: Founder's Background and Vision - The founder, Chen Yubei, has a strong academic background in AI and has shifted from theoretical research to practical applications, driven by a desire to see AI implemented in real-world products [4][16]. - The founding of Aizip was catalyzed by the COVID-19 pandemic, which disrupted initial plans for postdoctoral research and prompted discussions about entrepreneurship [6][16]. - Aizip's team comprises experienced individuals with diverse backgrounds, emphasizing a culture of collaboration and long-term value over short-term gains [17][18]. Group 3: On-Device AI Revolution - The article predicts that over 50% of AI reasoning will occur on-device in the near future, driven by advancements in hardware and user demand for low-latency, privacy-focused AI products [30][31]. - Aizip's product line includes multi-modal perception models and language models, focusing on seamless integration into various devices to enhance user experience without overtly displaying AI functionality [22][23]. - The company aims to create a comprehensive AI model ecosystem compatible with mainstream hardware, facilitating easier integration for clients [34][36]. Group 4: Market Position and Future Outlook - Aizip positions itself as a foundational support for companies lacking the resources to build their own on-device AI teams, anticipating a growing market for such capabilities [32][34]. - The company has established partnerships with leading hardware manufacturers and has achieved recognition for its innovative AI products [38]. - Aizip's strategy focuses on gradual commercialization, prioritizing technology validation and model stability before scaling operations [35][36].

中科创星招聘投资研究实习生（AI、北上深） 中科创星早期VC，市场化双币基金（人民币+港币），管理规模近150亿，国内最活跃的早期VC，出 手非常活跃，效率极高，组织扁平化，实习生招聘： 1、AI底层技术，关键词：LLM、AIGC、视频生成、3D生成、多模态、强化学习、Agent、Coding。 需要有技术深度，有技术广度，能看懂前沿论文、算法代码，对技术趋势有判断力。 2、AI应用层：对AI行业、AI项目有很强的认知，toB、toC不限。 base 北上深可选，希望尽快入职 邮箱：wangchao@casstar.com.cn 对创业、投资、战略、互联网等行业实习感兴趣的同学，添加小助手发送"实习群"加入Z Intern社 群。需要发布实习生招聘信息（免费）可以联系小助手或者填写表单。 加小助手发送"实习群" ✅招聘需求收集表 关于 Z Potentials -----------END----------- 我们正在招募新一期的实习生 我们正在寻找有创造力的00后创业者 ...