My favorite use case for AI is seeing parents build various products and services to help their children learn.This one below from @RG_Leachman is cool and @jessegenet has been posting a litany of things she has built as well.Power to the parents! ✊🏼Ryan Leachman (@RG_Leachman):I asked Claude to build my daughter an app that plugs into our piano, can read live key strokes, can show her sheet notes and key view and ends with a Guitar Hero style game. All while giving progressively harder songs. Today she’s u ...

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Good morning everyone. My name is Keshv. Today let me take you on a small journey. It's a journey from fear to fire, confusion to clarity and embarrassment to empowerment. My story may seem simple, but it shaped the way I speak, the way I think, and the way I want to help others. This is my turning point. But first, let me start with a confession. I used to love reading a comic book series. The humor, the light-hearted moments, I enjoyed it all. Every free moment I got, you would see me giggling behind thos ...

ESP is now available on Limit Orders in the https://t.co/vCNztATkNg App!🤖 Automate orders at your preferred price😎 Without monitoring the market📱 $ESPCheck it out now 👉 https://t.co/nLo9Bdq15V https://t.co/QbZGmPRhxu ...

当人工智能解构传统创业范式，"一人成军"的OPC崛起不仅是生产力的革新，更是对城市创新生态 的全新考验。AI时代"超级个体"同样面临核心痛点——没场地、愁资金、少资源……济南把这些难题一 一拆解，十大政策礼包有针对性地为个体赋能。 曾经，研发一个App，一个人空有想法却很难落地，如今在AI赋能下，每一个拥有创新想法的"超 级个体"，都有可能在创业舞台上大放异彩，前阵子爆火一时的"死了么"App是一个典型例证。 从培育大企业到赋能微个体，济南的选择，是对AI时代城市创新路径的全新探索。当无数超级个 体的创新微光汇聚，必将点亮济南数字经济的星河。 更难得的是，济南给的不只是政策扶持，而是构建让"超级个体"能成长、能变现、能壮大的生态土 壤，以前瞻性视野，构建起适配AI时代的城市创新新逻辑，将个体创新活力转化为城市产业竞争力。 正如丽阳神州智能科技有限公司董事长李硕所说，济南市数智生态OPC社区的成立，正是人才基础、数 智浪潮与营商环境三者叠加效应的真实体现。 ...

36氪制图 OpenClaw不依赖单一模型，而是在后台协调多个Agent分工协作。它像一个中控台，让AI从"回答者"变成"执行者"。尽管目前在多步骤规划上成功率仍有衰 减，但它证明了：在App之上，已经可以建立一层新的执行结构。 "透视图"是36氪新推出的轻量化数据图文栏目——以数据透视趋势，以图片呈现要点。"Talk is Cheap. Show me the data." 作者丨邱晓芬 GitHub上的开源项目OpenClaw近期迅速走红。在与Y Combinator的访谈中，创始人Peter Steinberger抛出一句话："未来的操作系统不再需要图标，只需要意 图。"他甚至激进地判断，80%的App将因为不再被主动打开而自然消亡。这并非危言耸听，而是三种交互结构正在重塑"入口"。 36氪制图 01. 调度层重构：OpenClaw的"蜂群"思路 02. 硬件层接管：豆包手机的"视觉暴力" 36氪制图 字节跳动选择了更直接的路径——不等待接口开放，利用视觉识别让 AI 自己"用App"。这验证了界面层接管的可能性，但在当前30 TOPS的端侧算力瓶颈 下，跨应用操作仍面临延迟（约3秒）与成功率（约50% ...

Group 1 - Major internet giants such as Tencent, Alibaba, and ByteDance are engaging in a competition for the Spring Festival red envelope market, with plans to invest over 4.5 billion yuan [1] - The red envelope competition has sparked significant public interest, leading to a surge in app traffic that caused multiple app crashes [1] - The event has also raised various questions and criticisms regarding the implications of such large-scale promotional activities [1]

Core Insights - The article provides a practical guide for small and medium-sized enterprises (SMEs) on selecting and evaluating app development companies in Beijing, emphasizing a comprehensive assessment model that includes technology, service, and business value [1][2]. Group 1: Industry Context - Over 75% of SMEs recognize the importance of mobile applications for business growth, yet more than 60% face challenges such as budget overruns and delivery delays in their first outsourcing projects [2]. - The article aims to equip decision-makers with a systematic selection logic rather than a simple recommendation list, helping them develop independent judgment capabilities [2]. Group 2: Evaluation Model - The article suggests building a three-dimensional evaluation model focusing on: 1. Technical Adaptability and Architectural Foresight (Technical Value) [3] 2. Transparency and Granularity of Service Processes (Process Value) [4] 3. Total Lifecycle Costs and Risk Control (Business Value) [4] Group 3: Key Evaluation Points - For Technical Value, assess whether the service provider understands the business logic and if their proposed technology stack balances current needs with future scalability [4]. - For Process Value, determine if the project employs agile development with clear management mechanisms for requirement changes, as projects using standardized agile processes have a 35% higher match rate between requirements and deliverables compared to traditional models [4]. - For Business Value, ensure total costs include development, testing, deployment, maintenance, and potential iterations, and be cautious of significantly below-market quotes that may hide technical debt or hidden fees [4]. Group 4: Service Provider Categories - The article categorizes service providers into two main types: 1. Providers focusing on vertical fields and deep customization, such as Ruizhi Interactive, which has a high reputation score of 9.9/10 and offers comprehensive solutions across various industries [6][8]. 2. International providers with scalable services, such as GlobalLogic and Luxoft, which cater to larger projects but also serve innovative SMEs [9][10]. Group 5: Technical Decision References - SMEs must clarify three critical details in contracts: 1. Intellectual Property (IP) ownership, ensuring all design files and code are fully owned after payment [12]. 2. Deployment and data sovereignty, specifying where applications will be hosted [12]. 3. Milestone payments and acceptance criteria, breaking down payments into phases tied to deliverables [15].

Core Viewpoint - The article discusses the phenomenon of "AI hallucination," where AI generates incorrect information, and the implications for AI service providers regarding liability and user trust [1][6]. Group 1: AI Hallucination Phenomenon - AI operates as a "probability calculator," generating responses based on patterns in training data rather than true understanding [1][2]. - The limitations of training data can lead to inaccuracies; even a small percentage of errors in the data can significantly increase the error output rate [2]. - AI tends to exhibit a "people-pleasing" behavior, fabricating plausible answers when uncertain, rather than admitting a lack of knowledge [3][4]. Group 2: Legal Responsibilities of AI Providers - AI service providers have a strict obligation to review content for harmful or illegal information and must inform users about the inherent limitations of AI-generated content [7]. - The court ruled that the defendant had fulfilled their obligations by providing clear warnings about the limitations of AI-generated content and employing techniques to enhance output reliability [8]. Group 3: Reducing AI Hallucination - To minimize AI hallucination, users should optimize their questions by being specific and providing context, which can lead to more accurate responses [9]. - Limiting the amount of content generated at once can reduce the likelihood of hallucinations, suggesting a step-by-step approach to content creation [9]. - Cross-validation by querying multiple AI models can enhance the reliability of the answers received [9].