[Music] So, as you come in, we have here a server set up with everything you'll need. If you want to follow along, you should have gotten a post-it note. If you don't, just raise your hand and my colleague Alex over here will come find you and we'll provide you with one.Uh, basically what you're going to do is you're just going to go, if you have a number 160 or below, you go to this link here, the QR code on top as well. Um, and if you have a number that's 2011 or above, you go to the second link or the QR ...

[Music] My name is Bang. I'm the CTO and co-founder of a company called Source Graph. Uh we build developer tools and today I want to share with you some of the observations and insights that we've had on this sort of like emerging skill set of how to wield coding agents. That sound good to everyone? All right, cool. Um, okay. So, let's check in on the uh the the agent discourse. Uh, I don't know if you all saw this, but a couple days ago there were some spicy tweets about the the efficacy of AI coding agen ...

[Music] Hi, I'm Lizzie. I'm a developer advocate at Cloudflare. And I'm Nick. I'm a developer experience engineer at work OS. Yes. So, at Cloudflare, I make a lot of AI demos, AI MCP servers. Anyone here also making any of those? Yes. Agents. Nice. Of course, should have guessed because conference. So, I've been having fun making agents and MCP servers that act on behalf of me. I built an agent to auto vote in the NBA finals for me and then I got blocked eventually. Uh, anyways, like book tennis courts in S ...

Cursor launches a web app to manage AI coding agents | TechCrunch https://t.co/nvSiyhn2kZ ...

在AI技术快速渗透的今天，AI Agent已从实验室走向企业级应用，成为自动化解决方案的核心载体。从字节跳动的"扣子空间"到OpenManus的开源生态，从 AutoGLM的深度思考到实在智能的TARS-RPA-Agent，市面上的AI Agent产品呈现出百花齐放的格局。这些产品不仅定义了技术边界，更在不同场景中重塑 了人机协作的范式。 RPA与AI Agent的融合：从执行到决策的跃迁传统RPA（机器人流程自动化）曾以"规则驱动"为核心，依赖预设流程完成重复性任务。然而，随着AI技术的 成熟，RPA逐渐与AI Agent结合，形成"RPA+AI"的混合自动化模式。例如，Automation Anywhere推出的AI Agent Studio，通过低代码平台允许用户构建自定 义AI Agent，其核心在于将自然语言指令转化为可执行的自动化流程。而实在智能的TARS-RPA-Agent则进一步突破了这一框架，它不仅具备强大的意图理 解能力，还能在复杂操作系统及桌面软件环境下精准操作，甚至能通过"自主感知"调整策略，实现从"执行者"到"决策者"的跃迁。 垂直领域深耕：AI Agent的差异化优势在金融、政务、 ...

Hey there, Clia here from Lama Index and today we're going to see how a syllabus extraction agent uh can work. So this agent is basically designed to extract information from a university course syllabus and to give you some summary information about the syllable the syllabus. So let's uh start with this syllabus here. Let's submit it uh so that we can see basically the agent at work.And first is the syllabus extractor tool that use that uses slama extract from llama cloud and basically extracts the informa ...

Core Insights - Pearson's Generative AI Foundations Certification has experienced double-digit monthly growth since its launch in October 2024, attracting a global audience of learners [1][8] - The company is expanding its AI learning content portfolio to cater to K-12, higher education, professional, and enterprise learners, addressing the urgent need for advanced skills in the workforce [1][3] Company Initiatives - The expanded portfolio includes certification opportunities across various formats and disciplines, focusing on agentic AI, large language models, machine learning, and ethical AI implementation [2] - Pearson's AI-related live training hours have nearly doubled from 580 to 996 content hours in the past year, highlighting the company's commitment to enhancing AI understanding in educational settings [3] Industry Context - The skills gap is becoming a significant concern, with estimated annual economic losses of $1.1 trillion in the US and £100 billion in the UK due to a lack of relevant skills [4] - The emergence of agentic AI systems necessitates the development of essential skills for future success in both education and the workplace [4] Strategic Partnerships - Pearson has formed strategic partnerships with major tech companies such as Microsoft, Amazon Web Services, and Google to enhance its AI learning offerings and transform the learning experience [5] Learning Content Features - The expanded AI learning content includes modules on responsible AI use, with AI Literacy modules launching in select courses this fall, allowing students to earn recognized badges for completion [8]

Group 1: Platform Demand - The rise of AI has created new possibilities for consumer agents, as traditional search methods are not user-friendly, particularly for vague product needs [2][6] - Users often prefer to search social media for product recommendations before making purchases on e-commerce platforms, leading to a shift in marketing budgets from traditional search to social media [6][10] - The traditional search model struggles to address the issue of vague consumer needs, resulting in a significant time investment for users to find suitable products [10][11] Group 2: User Demand - Users desire a simple purchasing process that effectively resolves their problems while also seeking reliable products at lower prices, leading to a preference for comparative evaluations [7][9] - Independent evaluations are less common, as most users engage in comparative assessments of similar products to feel secure in their purchasing decisions [9][10] - The ideal number of products for comparison is limited to 3-5, as excessive options can overwhelm users [10] Group 3: AI Integration in E-commerce - Alibaba's recent organizational changes signal a move towards integrating various consumer services, aiming for a one-stop shopping experience that could be enhanced by AI [12][14] - The potential for AI to streamline the consumer experience by understanding and fulfilling user needs in a comprehensive manner is highlighted, with AI universal search seen as a precursor to consumer agents [12][20] - The success of AI in e-commerce will depend on leveraging extensive internal and external data, with potential partnerships or acquisitions of platforms like Xiaohongshu to enhance data collection [13][21] Group 4: User Experience with AI - Current AI search experiences are noted to be suboptimal, as users prioritize product recommendations over simple answers, indicating a need for smarter search functionalities [15][20] - AI universal search has shown promise in addressing vague and specific user needs, providing a more convenient shopping experience akin to a combination of Xiaohongshu and Taobao [15][20] - The expectation is that 2024 will be a significant year for AI integration in e-commerce, with competitors unable to ignore the resulting differences in user experience [20]

Core Viewpoint - The commercialization of robotics is entering a critical phase, with companies like Zhifang and Digital Huaxia taking different approaches in industrial and commercial applications, respectively [1][2][3] Group 1: Scene Selection - The industry consensus is that embodied robots will first penetrate industrial applications, followed by commercial and household uses, due to the controlled and repetitive nature of industrial environments [2] - Zhifang focuses on industrial scenarios, developing the AlphaBot series with a self-developed end-to-end VLA embodied model, while Digital Huaxia targets commercial applications with humanoid robots designed for interactive experiences [2][3] - The challenges in commercial environments are greater due to safety and interaction complexities, necessitating continuous optimization of technologies like voice and visual recognition [3][4] Group 2: Supply Chain Layout - Zhifang emphasizes full-stack self-research of its VLA model and plans to establish its own production line, learning from the early stages of the electric vehicle industry [6][7] - Digital Huaxia is building a software ecosystem by creating PaaS and RaaS platforms, allowing third-party developers to enhance their humanoid robots' capabilities [6][7] - The two companies represent different business models: Zhifang operates like a direct store with a focus on self-research, while Digital Huaxia resembles a franchise model, promoting ecosystem collaboration [7] Group 3: Capital Perspective - Investment focus varies by stage; early-stage investors prioritize team background and technology, while later stages emphasize scene delivery capabilities and technology generalization [9] - The U.S. market favors AI software companies, while the Chinese market is more mature in hardware ecosystems, leading to a greater emphasis on the practical application of embodied robots [9][10] - Future business models are expected to shift from selling hardware to offering collaborative services, which could unlock significant market potential [10][11]

去年 6 月份，HeyGen 正式以 5 亿美金估值完成由 Benchmark 领投的 6000 万美金 A 轮融资，当时其公 布的 ARR 为 3500 万美金《 3500 万美金 ARR，什么驱动了 HeyGen 的新一轮快速增长？ 》。 之后基本上就没有公布除了产品更新以外的其它数据了，不过我最新了解到的信息是， HeyGen 的 ARR 已经达到 8000 万美金，今年有望突破 1 亿美金，团队 100 人左右 。 由于公司一直盈利，据说 HeyGen 上一轮融的钱基本上都在银行里吃利息。这和 Benchmark 投资的 AI 招 聘平台 Mercor 类似，已经有投资人给 Mercor 报价 100 亿美金估值，但是被创始人拒绝，原因是公司本 身盈利，融资过程太分心《 拿 6000 万美金的 AI 语音产品在 VC 圈火了，Mercor 最新估值 100 亿美金 》。 按照最新的营收来估算，HeyGen 估值超过 10 亿美金应该很正常了。根据 HeyGen 最新提供的信息， 目 前其全球用户超过了 1500 万，付费用户则超过了 10 万，其中企业客户 4.5 万 ，涵盖了多个行业，比方 说欧洲的 ...