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BestBlogs.dev Weekly Selection Issue #2

Dear Friends, Welcome to this issue of our Newsletter! We have carefully selected 68 articles from over 1600+ on programming technology, artificial intelligence, product design, and business technology, aiming to help you expand your horizons and acquire the most cutting-edge knowledge and insights. In the programming languages section, you will learn about Meituan's practice of domain-driven design (DDD) in complex business systems and explore the performance differences between just-in-time (JIT) compilation and interpretation in JavaScript engines. We also discuss the challenges and solutions for LinkedIn platform expansion, the high-performance design of ByteDance's OneAgent, and the evolution of Ctrip's data platform in a multi-data center architecture. Additionally, you will find insights on Tailwind CSS optimization, examples of using the React Context API, the latest Cloudflare local traffic management extensions, performance optimization for NetEase Cloud Music Desktop 3.0, and a Go engineering development guide for Java programmers. In the field of artificial intelligence, Hugging Face has released Transformers Agent 2.0, enhancing modular design and performance. Tian Yuandong discusses the limitations of Scaling Law and the potential of generative AI, emphasizing the need for major breakthroughs to achieve general artificial intelligence. We also introduce various text generation strategies implemented in the Transformer library and their pros and cons, LlamaIndex's attribute graph indexing capabilities, new features in LangChain v0.2, Jay Alammar's discussion on retrieval-augmented generation (RAG) systems, training and fine-tuning methods for Sentence Transformers v3, and new approaches to synthetic data and privacy protection. In the areas of design, product operations, and marketing, articles explore how to use "cognitive biases" to enhance design effectiveness, analyze nine common user interaction states, emphasize the importance of understanding user needs and task-driven approaches, and unpack Webflow's product-driven SEO success story. We showcase Huawei's core advantages in project management, discuss the importance of user feedback, elaborate on B2B product customer acquisition strategies, and deeply analyze pricing strategies for overseas SaaS products. In the business and technology realm, AI Grant has become the most AI-savvy investment institution, leading market trends. Alibaba Chairman Joe Tsai stated that AI model training is like educating children and will surpass human PhDs in the coming years. Paul Graham shared the paths for ordinary people to achieve great things. The large model price war has drawn attention, but startups remain unphased, with a clear trend towards price reductions. Apple introduced eye-tracking technology in iPadOS 18, hinting at future interaction modes. Tencent launched the AI assistant Yuanbao, focusing on user experience and ecosystem resource integration. Investor Zhang Lu suggested that startups can optimize large models through a "cocktail" approach, and AI is seen as a super tool driving digital transformation across industries. AI pioneers Fei-Fei Li and Geoffrey Hinton discussed AI development, particularly breakthroughs in computer vision. Alright, let's start reading!

Is JIT Really Faster than Interpreted Execution?—Hot Topics about JS Engines

大淘宝技术|mp.weixin.qq.com

AI score: 93 🌟🌟🌟🌟🌟
Is JIT Really Faster than Interpreted Execution?—Hot Topics about JS Engines

With the proliferation of scripting languages and increasing performance demands, interpreted execution and Just-In-Time (JIT) compilation have become two common methods of code execution. This article explores both technologies through detailed examples and in-depth analysis, revealing their working principles, performance differences, and respective advantages and disadvantages.

DDD Practice in B-end Marketing System

美团技术团队|tech.meituan.com

AI score: 95 🌟🌟🌟🌟🌟
DDD Practice in B-end Marketing System

This article systematically introduces the application of Domain-Driven Design (DDD) in complex business systems, with a particular focus on practical cases from Meituan. The article first explains the basic concepts of DDD, including domain models, bounded contexts, aggregates, entities, and value objects. DDD emphasizes a domain-centric approach to solve real business problems through modeling and design. The article details the challenges Meituan faced in building its marketing system, such as business complexity and changing requirements, and how these issues were addressed using DDD methods. From strategic design and tactical design to code architecture, it progressively demonstrates how DDD can be implemented in actual business scenarios. The use of methods like use case diagrams, user stories, and event storming to identify business requirements, and the use of a unified language and conceptual model to ensure consistency between business and technology, are particularly highlighted. Meituan's case shows that DDD can effectively solve problems related to system coupling and changes, improving system flexibility and maintainability. The article also discusses the challenges of implementing DDD, including team collaboration and acquiring domain knowledge, and emphasizes the importance of continuous learning and iterative optimization. Overall, this article provides readers with a comprehensive view and practical guidance on the application of DDD in complex business systems, helping to understand how to solve real business problems and improve system quality through DDD.

The Scaling Journey of LinkedIn

ByteByteGo Newsletter|blog.bytebytego.com

AI score: 93 🌟🌟🌟🌟🌟
The Scaling Journey of LinkedIn

This article provides a detailed look into how LinkedIn handled the challenges of scaling its platform to accommodate exponential growth. It covers the transition from a monolithic architecture to a distributed system, the creation of specialized services like the Member Graph Service and Search Service, and the use of various tools and techniques to manage the increasing demand.

Ctrip Data Foundation Platform 2.0 Construction: Evolution in Multi-datacenter Architecture

携程技术|mp.weixin.qq.com

AI score: 93 🌟🌟🌟🌟🌟

The Ctrip technical team has progressively refined its data foundation platform over the past few years, evolving from the 1.0 architecture to the 2.0 version in 2023. This platform primarily includes the HDFS distributed storage cluster, the YARN computing cluster, and the Spark and Hive computing engines. Faced with the rapid growth of data and computing tasks, the team has taken measures such as multi-data center architecture upgrades, tiered storage strategies, transparent migration technology, priority-based scheduling, NodeManager node mixing, and the integration of offline and online nodes, as well as the introduction of Celeborn as a new Shuffle service. These steps address the pain points in storage, scheduling, and computing engines. Additionally, the team has achieved a smooth upgrade from Spark2 to Spark3, optimized the partition filtering function in Spark3, tackled the issue of data skew, and introduced the Apache Kyuubi project as the Thrift Server for Spark3, providing enhanced multi-tenancy and resource isolation support. Through these improvements, the Ctrip technical team has not only enhanced the scalability, resilience, and performance of the data platform but also ensured the stable operation of the group's data.

Introduction to Go Project Development Workflow for Java Programmers

大淘宝技术|mp.weixin.qq.com

AI score: 92 🌟🌟🌟🌟🌟

For Java programmers without a Go background, the speed of developing a usable program in Go is visibly slow. The main difficulty lies not in the Go language itself but in setting up the entire project pipeline, or 'environment configuration.' This article describes how to configure an environment suitable for Go development to avoid common pitfalls.

2500-Page Document Exposes Google's Search Dark Secrets: User Data Misused, Whitelist Mechanism, and Brands Dominating Search Rankings

智东西|mp.weixin.qq.com

AI score: 91 🌟🌟🌟🌟🌟

Google's largest information leak in 20 years unveils the 'black box' of search ranking mechanisms. The leaked 2500-page document reveals Google search engine's internal algorithms and contradicts Google's public statements and testimonies in the 2023 U.S. Department of Justice antitrust case. Key points include the use of user interaction data, Chrome for data collection, whitelist mechanisms for trusted domains, and human quality evaluators influencing search results. This leak challenges traditional SEO strategies and highlights the dominance of major brands in search rankings.

Uber Migrates 1 Trillion Records from DynamoDB to LedgerStore, Saving $6 Million Annually

InfoQ 中文|mp.weixin.qq.com

AI score: 90 🌟🌟🌟🌟

Uber has migrated all its payment transaction data from DynamoDB and Blob storage to a new long-term solution called LedgerStore. The company aimed to reduce costs and previously minimized DynamoDB usage, only using it for hot data. The new system offers immutable storage with data integrity guarantees, saving Uber around $6 million annually.

WebGPU Leads the Future of Front-End: How Interactive Rendering Drives Business Growth on Xiaohongshu?

小红书技术REDtech|mp.weixin.qq.com

AI score: 89 🌟🌟🌟🌟

Experts from around the world gather at Xiaohongshu to discuss new trends in web technology. The article delves into the potential of WebGPU as a high-performance API standard for 3D graphics and data parallel computing, its applications in various industries like gaming, VR, and machine learning, and how Xiaohongshu leverages it for business growth. Key points include: 1) The advantages of combining WebCodecs, Streams, and WebGPU for real-time media processing; 2) Use cases of interactive rendering technology in Xiaohongshu; 3) Comparative advantages of WebGL over Lottie and optimization strategies for WebGL; 4) Future prospects of WebGPU in enabling richer and more dynamic web experiences.

Building an Emergency Response System for Handling Failures at Bilibili

dbaplus社群|mp.weixin.qq.com

AI score: 88 🌟🌟🌟🌟

This article, based on a lecture by Bilibili's senior SRE engineer Hong Peng, details the construction of an emergency response system at Bilibili. The system aims to detect issues within 1 minute, respond within 3 minutes, pinpoint and identify within 5 minutes, and recover within 10 minutes. The article covers three main areas: 1. Stability assurance challenges, 2. Emergency Response Center (ERC) construction strategy, and 3. Platform capabilities. Key points include the technical means of monitoring and handling failures, the role of customer feedback, and the automation of the emergency response process.

Why Kubernetes Is a Mistake for My SaaS Business

InfoQ 中文|mp.weixin.qq.com

AI score: 87 🌟🌟🌟🌟

Kubernetes provides a robust solution for managing high-availability large-scale applications, but it may not be suitable for all SaaS businesses, especially for independent developers or smaller projects.

Spring AI 1.0.0 M1 Released

Spring Blog|spring.io

AI score: 90 🌟🌟🌟🌟

The article introduces the 1.0.0 Milestone 1 release of Spring AI, highlighting its new features and improvements. Key points include: 1. ChatClient Fluent API for handling prompts and AI model calls. 2. Usage examples with @RestController, returning AI-generated content. 3. Integration with WebClient for reactive calls. 4. Configuration options for default values in ChatClient. 5. Advisor model for contextual data and conversational history.

Why Enterprises Rely on JavaScript, Python, and Java

InfoWorld|infoworld.com

AI score: 91 🌟🌟🌟🌟🌟

Despite advances in cloud computing, mobile development, and AI, JavaScript, Python, and Java remain the top choices for developers. These languages have been popular for nearly 30 years and are expected to continue to be so. JavaScript powers the front end of applications, Python excels in data analysis and automation, and Java underpins enterprise applications with its robust frameworks and libraries.

13 Frontend Libraries That Have Earned Me Plenty of Leisure Time at Work - Juejin

掘金本周最热|juejin.cn

AI score: 90 🌟🌟🌟🌟

The article's author shared 13 front-end libraries that he frequently uses in his work to help developers improve their efficiency. First, he introduced Ant Design, a React component library that provides a variety of commonly used components, supporting internationalization and custom theme colors. He then discussed Axios, an HTTP request library based on Promises, which supports request and response interceptors as well as the ability to cancel requests. Day.js is a lightweight date processing library with an API design that supports chained calls. Lodash is a JavaScript utility library that offers a range of functionalities including collection processing, functional tools, type checking, deep cloning, string manipulation, and mathematical operations. The XSS library is used to process HTML and prevent XSS attacks, with support for whitelist configuration. Classnames is used for dynamically adding or removing CSS class names. Copy-text-to-clipboard is a lightweight library for copying text to the clipboard. UUID is used for generating globally unique identifiers. Quill is a rich text editor suitable for edit box requirements in mid to back-end products. Crypto-js provides various encryption algorithms and common encryption functions. Viewerjs is an image preview library that supports interactive features such as zooming, dragging, and rotating. Localforage is a library that encapsulates the browser's storage engine, allowing for the selection of appropriate storage engines for data storage. Vconsole enables real-time viewing of debugging information in mobile browsers.

React Context API Explained with Examples

freeCodeCamp.org|freecodecamp.org

AI score: 92 🌟🌟🌟🌟🌟

The article first discusses the complexity of managing state in React applications using prop drilling, which involves passing props down through the component hierarchy. This approach becomes challenging to maintain and understand as the complexity of the application increases. To address this issue, React offers the Context API, which enables state sharing across the component tree without the need for manual prop passing. Next, the article details the creation and use of the Context API through a counter example. It begins by creating a context named CounterContext and defining a CounterProvider component to supply the state and setState function. It then demonstrates how to consume these states within the GrandChildComponent using the useContext hook, instead of via prop passing. The article also outlines several common use cases for the Context API, including global state management, authentication management, theme management, and more. Additionally, it compares the Context API to other state management solutions such as Redux, Zustand, and MobX, highlighting their respective features and appropriate scenarios for use. Finally, the article offers some best practices for using the Context API effectively, which include providing default values, avoiding overuse of Context, minimizing frequently updated states, and utilizing custom hooks and memoization of context values to enhance performance.

Reducing false positives with automated SIEM investigations from Elastic and Tines

Elastic Blog|elastic.co

AI score: 89 🌟🌟🌟🌟

The Elastic InfoSec team faces a major challenge in SIEM management: analysts are overwhelmed by a large number of false positives, leading to fatigue and visibility gaps. To address this issue, the team has implemented the Tines automation tool to reduce the manual investigation workload of SIEM alerts. By integrating Tines with Elastic's SOAR system, the team has established automated investigation workflows that leverage Elasticsearch's _searchAPI and Signals API to automatically close false positive alerts and escalate real threats when necessary. This automation enables Elastic to automatically process over 3,000 alerts daily, equivalent to saving the workload of 94 full-time employees.

Performance Optimization Journey of Yun Music Desktop Version 3.0

奇舞精选|mp.weixin.qq.com

AI score: 92 🌟🌟🌟🌟🌟
Performance Optimization Journey of Yun Music Desktop Version 3.0

The Yun Music desktop version was released in May 2014 and had been using the NEJ + CEF based Hybrid APP architecture until the 3.0 update. Despite trying to adopt React in conjunction with NEJ during 2021-2022, it proved inefficient due to the heavy reliance on NEJ. The 3.0 version brought significant interaction and visual updates, necessitating a complete React-based overhaul. This article discusses the main performance challenges encountered and the optimization strategies implemented, covering areas such as playback initiation time, UI component rendering, handling vast amounts of playlist data, managing diverse events, and complex state subscriptions.

A New Way to Query: Introducing the Atlas Search Playground

MongoDB Blog|mongodb.com

AI score: 91 🌟🌟🌟🌟🌟

The official MongoDB blog has introduced the Atlas Search Playground, a new sandbox environment designed for developers to rapidly experiment with, iterate on, and collaborate on search indexes and queries. The platform is characterized by its ability to allow developers to instantly try creating indexes and formulating data search queries without the need to fully set up Atlas collections or wait for index construction. It offers a seamless user experience, enabling users to complete all operations within a single user-friendly interface without any prior experience or account setup.

Getting Started with Reliability on Azure: Ensuring Cloud Applications Stay Up and Running

Azure Architecture Blog|techcommunity.microsoft.com

AI score: 90 🌟🌟🌟🌟

This article explores the importance of reliability in Azure cloud services, detailing how Azure ensures robust cloud solutions through its architecture. Key aspects include adherence to Service Level Objectives (SLOs) and Service Level Agreements (SLAs), the importance of Recovery Time Objective (RTO) and Recovery Point Objective (RPO), and the shared responsibility model. It also discusses the pillars of cloud reliability, frameworks like Cloud Adoption Framework (CAF) and Well-Architected Framework (WAF), and specific Azure services and tools that enhance reliability.

Automatically clean up whitespace and duplicate class names - Tailwind CSS

Tailwind CSS Blog|tailwindcss.com

AI score: 92 🌟🌟🌟🌟🌟
Automatically clean up whitespace and duplicate class names - Tailwind CSS

The latest prettier-plugin-tailwindcss release introduces automatic removal of unnecessary whitespace and duplicate classes during sorting, streamlining class management.

ByteDance's Next-Generation Universal High-Performance OneAgent

字节跳动技术团队|mp.weixin.qq.com

AI score: 93 🌟🌟🌟🌟🌟

This article explores the development of OneAgent by ByteDance's Cloud Native Observability team, focusing on its data model, pipeline, orchestration, and build system. It highlights the challenges faced due to the vast scale of ByteDance's infrastructure and the need for a unified observability solution. OneAgent aims to simplify observability system integration and enhance data collection efficiency, resource consumption, and system stability. The article also discusses the collaboration with the iLogtail community and the architectural details of OneAgent, including its core and plugin systems.

Extending local traffic management load balancing to Layer 4 with Spectrum

The Cloudflare Blog|blog.cloudflare.com

AI score: 92 🌟🌟🌟🌟🌟

Cloudflare has extended its Local Traffic Management (LTM) load balancing capabilities to support all TCP and UDP traffic, which previously only supported HTTP(S) traffic. The integration of Cloudflare Spectrum, Tunnels, and load balancers now allows enterprise customers to manage a broader range of network protocols like SSH, FTP, NTP, and SMTP. Key benefits include eliminating the need for on-premise load balancers, increased security through IP concealment, and enhanced scalability via Cloudflare's global Anycast network.

Miss Jia Discusses Scaling Law with Tian Yuandong: A Very Pessimistic Future

甲子光年|mp.weixin.qq.com

AI score: 94 🌟🌟🌟🌟🌟
Miss Jia Discusses Scaling Law with Tian Yuandong: A Very Pessimistic Future

In this article, Tian Yuandong provides profound insights into several key issues in current AI research, particularly his skepticism towards the Scaling Law and his advocacy for generative AI. Tian first discusses the limitations of the Scaling Law. Proposed by OpenAI in 2020, the Scaling Law suggests that the ultimate performance of large models is primarily determined by computational power, model parameter size, and the amount of training data, rather than the specific structure of the models. However, Tian points out that as model performance approaches human levels, acquiring new data becomes increasingly difficult, and further improvements become harder to achieve. Additionally, he highlights that many real-world long-tail needs involve scenarios with very little data, which cannot be addressed by relying on the Scaling Law alone. This could eventually lead to a situation where everyone is isolated on their own "data islands," unable to share and utilize each other's data. Tian then emphasizes the advantages of generative AI. He believes that generative AI can generate large amounts of content from minimal prompts, reducing the need for manual input and repetitive labor. Generative AI can work similarly to teaching a child, where minimal guidance allows it to extrapolate and create more, significantly boosting productivity. This is because generative AI can work around the clock, has low replication costs, and replicating engineers is very difficult. Furthermore, Tian presents his views on breakthroughs in data efficiency. He argues that achieving truly data-efficient artificial general intelligence (AGI) requires 2-3 major breakthroughs. While the Scaling Law may be effective in some aspects, it is not the complete solution, as it represents a very pessimistic future. Regarding the interpretability of AI, Tian believes that AI models based on neural networks are interpretable, and eventually, humans will understand how these models are trained. Despite many currently inexplicable aspects, he argues that this should not be a reason to abandon exploration. Lastly, Tian discusses the diversity of technology in Silicon Valley, noting that everyone has their own methods, and technological progress does not necessarily rely on current mainstream approaches. Non-mainstream explorations could potentially drive the next technological revolution. He also suggests abandoning the notion that "the brain is the controller of humans," asserting that every part of the body has a vote in behavioral expressions, and future integrated AI will have a vote as well. Through Tian Yuandong's perspective, this article offers readers unique insights into the development of AI, the limitations of data-driven models, and the prospects of generative AI, making it a valuable read for deeper understanding and contemplation.

Developers get by with a little help from AI: Stack Overflow Knows code assistant pulse survey results

Stack Overflow Blog|stackoverflow.blog

AI score: 89 🌟🌟🌟🌟

This article explores the use of generative AI tools among professional developers and their impact on productivity. Based on a survey of over 1,700 Stack Overflow community members, it reveals varying usage rates and experiences among different roles. Academic researchers and AI developers have higher usage rates, while data analysts and desktop developers use these tools less, reflecting differences in training data and application contexts. Despite challenges in accuracy and handling complex problems, AI tools are found to improve work quality and developer satisfaction. ChatGPT and GitHub Copilot are the most popular tools, with distinct preferences among professional developers and learners. While productivity gains are hard to quantify, most users report improved productivity thanks to these tools. However, low trust and adoption rates within teams hinder broader utilization.

Dify Workflow Major Update: Workflow Released as Tool, Iteration Node, Parameter Extraction, Flexibly Building Production-Level AI Applications

Dify|mp.weixin.qq.com

AI score: 91 🌟🌟🌟🌟🌟

Dify Workflow has been updated with new capabilities to enhance the flexibility of building production-level AI applications. The update includes the ability to publish Workflow as a tool, add iteration nodes for multi-step generation, extract structured parameters from unstructured information, and optimize node capabilities. The article provides examples of how these features can be applied in real business scenarios.

Baidu Comate Enhances Developer Efficiency, Completing 3 Weeks of Work in Just 2 Days

百度AI|mp.weixin.qq.com

AI score: 91 🌟🌟🌟🌟🌟

Baidu Comate is an intelligent coding assistant based on the Wenxin large model, which supports multiple programming languages and can be deeply integrated into mainstream IDEs. It provides features such as real-time code continuation and comment-based code generation, significantly enhancing the efficiency of code writing. Wang Rongsheng, a postgraduate student at the Macau University of Science and Technology, along with his laboratory colleagues, used Baidu Comate to process 150GB of medical imaging data, reducing the work that originally required three people for a week to just one person in two days, increasing efficiency by more than ninefold. Baidu Comate is capable of intelligently generating code blocks by analyzing contextual logical relationships and supports outputting code through natural language commands, thus improving the response speed to new requirements. Additionally, Baidu Comate's "code generation comments" and "private domain knowledge enhancement" functions, as well as the recently released "Comate Open Platform" feature, have further facilitated team collaboration and efficiency. Wang Rongsheng believes that Baidu Comate has not only improved the quality and speed of code generation but also helped their team achieve their own customized capabilities, enhancing the efficiency of research and development.

ControlNet Author Engages in Large Model Projects: Simplifying Image Prompts to a Sentence

量子位|qbitai.com

AI score: 91 🌟🌟🌟🌟🌟

The author of ControlNet, Lvmin Zhang, has launched a new project named Omost, which aims to simplify the process of writing prompts for AI-generated images. Users can now generate detailed compositions with just a simple sentence prompt. Key features include breaking down prompts into sub-prompts, defining numerous positions and offsets for elements in an image, and using a baseline renderer based on attention manipulation. The project is designed to make image generation intuitive and user-friendly, with tools for modifying images with minimal effort.

Suno V3.5 Hands-on Experience: AI Lowers the Barrier to Music Creation Again

Founder Park|mp.weixin.qq.com

AI score: 90 🌟🌟🌟🌟

Suno V3.5 has expanded the minimum segment length to 4 minutes, allowing creators to generate complete songs more easily. The new version also analyzes and constructs music structures more effectively, resulting in smoother and more natural music. The article discusses the practical experience of using Suno V3.5 and its impact on the music industry.

What We Learned from a Year of Building with Large Language Models (Part 1)

宝玉的分享|baoyu.io

AI score: 90 🌟🌟🌟🌟

This article summarizes the experiences gained from a year of building products with Large Language Models (LLMs). It highlights the advancements in LLMs, their application in real-world scenarios, and the challenges in creating robust AI products. The article also discusses the importance of prompt design, retrieval-augmented generation, and structured input/output in developing effective LLM applications.

Perplexity Introduces New Feature, Taking the First Step from Search to Browser

Z Potentials|mp.weixin.qq.com

AI score: 89 🌟🌟🌟🌟

Perplexity AI has recently introduced Perplexity Pages, a tool designed to assist users in creating visually appealing reports, articles, or guides. Users simply input a prompt, such as "information about the Sahara Desert," and the system generates customized content based on their input. Users can select different audience types to adjust the tone of the generated text. Perplexity's algorithm is capable of creating detailed articles with various sections and allows users to rewrite, reformat, or delete parts of the text. Additionally, users can draft sections about specific subtopics through prompts and assist in finding and inserting relevant media items, such as images and videos. The pages created can be published and searched through Google, and users can share the page links, enabling others to ask follow-up questions on the topic. Henry Modisett, the design lead for Perplexity, stated that the company aims to leverage its core technology to use Perplexity as a research tool but in a more shareable format. He emphasized that although the AI engine can quickly answer questions and form pages, completing a page takes a few minutes. Perplexity views this tool as a means of information filtering rather than complete content generation by AI, as users have decision-making power over the content and organization of the pages. The Perplexity Pages feature will initially be rolled out to a limited number of users, with plans to eventually offer it to all users.

After Experiencing Tencent's Latest AI Application 'Yuanbao', I Discovered a Surprising Feature That Other AI Assistants Lack

爱范儿|ifanr.com

AI score: 89 🌟🌟🌟🌟

Tencent has launched its new AI application 'Yuanbao', which integrates AI search, AI summary, and AI writing features. Unlike other AI assistants, Yuanbao combines multiple functionalities, such as real-time news push, and uniquely leverages Tencent's vast content resources from platforms like WeChat. Yuanbao aims to enhance user experience in content creation, multilingual translation, and even creative tasks like generating AI images. The app benefits from Tencent's advanced Hunyuan AI model, positioning it at the forefront of AI applications.

Become a 'My Neighbor Totoro' Character in Half an Hour

机器之心|jiqizhixin.com

AI score: 88 🌟🌟🌟🌟

The article details a case study on how to transform oneself into an anime character from "My Neighbor Totoro" using AI tools within half an hour. It begins with generating background and bus images using AI tools like Midjourney, followed by adjustments with an AI image editor. Next, the article guides on recording one's own motion video and processing the background using an AI green screen removal tool. Then, it describes using tools like DomoAI to convert the video into an anime style and compositing all materials, including the background image, processed video, and bus image, in a video editing software. Finally, the article concludes with adding green screen elements and sound effects to complete the video production.

Now Everyone Can Use GPT-4o for Free!

新智元|mp.weixin.qq.com

AI score: 88 🌟🌟🌟🌟

OpenAI has announced that ChatGPT is now free for all users, allowing access to customized GPTs, chart analysis, photo-related questions, and other features added to GPT-4o in early May. Free users can browse, use visual and data analysis tools, upload files, and access GPTs, but they cannot create their own GPTs, which is reserved for paid users. Paid users have higher message limits and access to the 'income sharing program' for creators of custom GPTs. The article also introduces four recommended GPTs available in the GPT Store.

Introducing Transformers Intelligent Agent 2.0

Hugging Face|mp.weixin.qq.com

AI score: 95 🌟🌟🌟🌟🌟
Introducing Transformers Intelligent Agent 2.0

Hugging Face has launched the new Transformers Agents 2.0, introducing two new types of agents capable of solving complex tasks based on historical observations, enhancing code clarity and modular design. Additionally, the new sharing feature fosters the development of agents within the community. The Llama-3-70B-Instruct agent surpasses GPT-4-based agents in the GAIA rankings, demonstrating exceptional performance. Agents are programs driven by large language models (LLMs) that execute specific tasks using tools. The framework design emphasizes simplicity and modularity, providing building blocks rather than a complex feature set, allowing users to freely choose the modules that best suit their projects. The main components include Tools, Toolboxes, CodeAgents, and ReactAgents. The article explains in detail the working mechanism of agents, particularly how the agent.run() method prompts the LLM to use tools, parse outputs, and execute calls. Moreover, it demonstrates through examples how to use agents for Retrieval-Augmented Generation (RAG), providing complete steps and code examples from installing dependencies to building and running agents.

Text Generation with Different Sampling Methods using Transformers

大淘宝技术|mp.weixin.qq.com

AI score: 94 🌟🌟🌟🌟🌟

In recent years, with the rise of large Transformer language models such as OpenAI's ChatGPT and Meta's LLaMA, the field of open-domain language generation has attracted increasing attention. This article provides a detailed introduction to several major sampling strategies and their implementation methods in the Transformer library, including greedy search, beam search, top-K sampling, top-P sampling, and temperature adjustment. Greedy search generates text by selecting the word with the highest probability at each step, which is simple but prone to repetition. Beam search retains multiple candidate sequences, reducing the risk of missing high-probability words, but it does not guarantee finding the optimal solution. Top-K sampling chooses from the top K words, increasing the diversity of generated text, but the fixed K value may not be suitable for all situations. Top-P sampling dynamically adjusts the sampling pool through cumulative probability, making it more flexible and effective. The temperature parameter affects the output of the softmax function, controlling the randomness and creativity of the generated text. Each of these strategies has its own advantages and disadvantages. Understanding and selecting the appropriate strategy can significantly improve the text generation quality of language models.

A Guide to AI Agents - Intelligent Agents

腾讯技术工程|mp.weixin.qq.com

AI score: 92 🌟🌟🌟🌟🌟
A Guide to AI Agents - Intelligent Agents

The article provides a detailed exposition of the concept of intelligent agents and their differences and similarities to the human brain. An intelligent agent is a universal problem solver based on large language models, capable of planning, memory, and tool utilization. The article illustrates through the example of a "researcher" agent how such agents can retrieve information from search engines and generate research reports. The key components of an intelligent agent include planning, memory, and tool use. Planning encompasses task decomposition, chains of thought (CoT), reflection and refinement, as well as the ReAct model, which integrates reasoning and acting strategies. Memory is divided into short-term and long-term memory, mimicking the human memory mechanism. Tool use is facilitated by the Function Calling mechanism, which allows large models to connect with external tools and execute function calls. Finally, the article introduces frameworks for developing intelligent agents and discusses how, with the enhancement of large model capabilities, intelligent agent technology will reshape software forms and interaction methods.

Benchmarking Text Generation Inference

Hugging Face Blog|huggingface.co

AI score: 88 🌟🌟🌟🌟

The article explores the Hugging Face Text Generation Inference (TGI) Benchmarking tool, designed to profile LLM deployments more effectively. It discusses the inefficiencies of LLMs, advancements in optimization techniques, and the importance of configuration based on use cases. Key concepts like latency and throughput are explained to help users optimize their deployments.

JLama: The First Pure Java Model Inference Engine Implemented With Vector API and Project Panama

InfoQ|infoq.com

AI score: 90 🌟🌟🌟🌟

JLama emerges as the first pure Java inference engine available in Maven Central, following the widespread adoption of Andrej Karpathy's open-source llama.c inference interface. This library leverages the Vector API and PanamaTensorOperations class with native fallback, promising faster inference using Java 21. JLama supports various models including Gemma, Llama, Mistral, GPT-2, BERT, and offers features like distributed inference, flash attention, and Hugging Face SafeTensors model compatibility. Developers can easily download models, interact with them through prompts or chat functionalities, and even utilize a simple web UI provided by JLama. The emergence of such tools signifies a growing trend towards smaller, more accessible LLMs, making their integration into Java applications increasingly feasible.

Using Cloud Run for AI applications

Google Cloud Blog|cloud.google.com

AI score: 89 🌟🌟🌟🌟

Google Cloud Run is a container platform that accelerates the development and deployment process of AI applications by providing a set of key features. These features include a quick transition from prototyping in Vertex AI Studio to containerized deployment; built-in Service Level Objective (SLO) monitoring and observability solutions; parallel version testing through traffic splitting; ensuring relevance and factuality by securely connecting to cloud databases; and achieving multi-regional deployment and high availability through global load balancers. The article details how to migrate from prototype creation in Vertex AI Studio to containerized deployment on Cloud Run, as well as how to use Cloud Run's code generation feature to transform experiments into deployable code. Additionally, the article explains how to monitor application performance using Cloud Run's SLO monitoring and Google Cloud's observability tools, and how to accelerate innovation with parallel versions and Cloud Deploy.

Training and Finetuning Embedding Models with Sentence Transformers v3

Hugging Face Blog|huggingface.co

AI score: 93 🌟🌟🌟🌟🌟

This article provides a detailed guide on how to train and finetune embedding models using Sentence Transformers v3. It explains the importance of finetuning for specific tasks, the components involved in the training process such as datasets, loss functions, and the new trainer, and how to use them effectively. It also discusses the significance of dataset format matching the chosen loss function.

Improving synthetic data without compromising privacy protection

Microsoft Research Blog|microsoft.com

AI score: 92 🌟🌟🌟🌟🌟
Improving synthetic data without compromising privacy protection

This article explores how synthetic data technology can balance the need for innovation and privacy protection in a data-driven world. It highlights that synthetic data allows AI models to be trained and adapted without using real user data, thus reducing privacy risks and complying with data privacy regulations. Differential Privacy (DP) is introduced as a key technique to generate statistically representative synthetic data while protecting the privacy of data contributors. The research showcases recent advancements, including the application of DP in fine-tuning generative language models (LLMs) to ensure the generated text is both representative and privacy-preserving. Additionally, methods for generating synthetic data via APIs and privacy-preserving techniques in few-shot learning are discussed. These findings provide organizations with new ways to generate useful and privacy-safe data, fostering responsible AI development. By leveraging these technologies and methods, synthetic data and differential privacy effectively support AI model training and application while ensuring data privacy, laying a solid foundation for innovation across various fields.

Practical Prompt Engineering for Smaller Language Models

Web Dev Articles|web.dev

AI score: 91 🌟🌟🌟🌟🌟

Learn techniques to optimize prompts for smaller language models to achieve desired outputs, including context provision and precise format instructions.

SiliconCloud Public Beta Launch, Free 3 Billion Tokens for Everyone

OneFlow|mp.weixin.qq.com

AI score: 89 🌟🌟🌟🌟
SiliconCloud Public Beta Launch, Free 3 Billion Tokens for Everyone

SiliconCloud is a comprehensive cloud service platform released by SiliconFlow, integrating APIs from a variety of mainstream open-source large language models and image generation models, including DeepSeek V2, Mistral, LLaMA 3, Qwen, SDXL, InstantID, among others. The platform aims to offer developers more comprehensive, faster, and more cost-effective model API access services, optimizing the inference process of large models through an inference acceleration engine to achieve efficient development of generative AI applications. The inference acceleration service provided by SiliconCloud significantly enhances the token output speed of DeepSeek V2 and enables the Stable Diffusion XL model to achieve millisecond-level instant image output. During the upcoming "6.18 Shopping Festival," SiliconFlow is offering a benefit to developers, providing each with 300 million Tokens to promote the popularization of large model applications and the development of the developer ecosystem. Additionally, SiliconCloud's acceleration technology can achieve algorithm optimization across various application scenarios, with up to a 10-fold acceleration effect, thereby reducing the cost of large model inference and improving inference efficiency. The SiliconFlow team is dedicated to addressing the supply and demand issues of computing power through software means and is promoting the ecological development of large model applications through comprehensive support.

Retrieval-Augmented Generation (RAG) Patterns and Best Practices

InfoQ|infoq.com

AI score: 93 🌟🌟🌟🌟🌟

Jay Alammar discusses the burgeoning field of Retrieval-Augmented Generation (RAG) systems and their impact within the broader scope of AI and language models. Highlighting both historical context and practical insights from industry experiences, he offers key perspectives on the capabilities of language AI. Key points include: 1. The historical evolution of generative AI and its comparison to past technological shifts. 2. The conceptual foundation and utility of RAG systems. 3. Practical insights from industry experience, particularly from Cohere. 4. Useful recommendations on viewing language models beyond mere black boxes. 5. Future directions and potential impact of language AI technologies.

Introducing the Property Graph Index: A Powerful New Way to Build Knowledge Graphs with LLMs

LlamaIndex Blog|llamaindex.ai

AI score: 94 🌟🌟🌟🌟🌟

This article introduces a new feature of LlamaIndex—the Property Graph Index. Traditional knowledge graph representations, such as knowledge triples, have limitations in expressiveness, including the inability to assign labels and properties to nodes and relationships, represent text nodes as vector embeddings, and perform both vector and symbolic retrieval. The Property Graph Index addresses these issues by using a labeled property graph representation, enabling richer modeling, storage, and querying capabilities. The article describes three methods for extracting knowledge graphs from data: Schema-Guided Extraction, Implicit Extraction, and Free-Form Extraction. Users can mix and match these methods for fine-grained control over the graph structure. By default, all graph nodes are embedded, and users can also specify and use any vector store from LlamaIndex. For querying, the Property Graph Index supports various techniques, including keyword/synonym-based retrieval, vector similarity, Cypher queries, and custom graph traversal. These techniques can be combined, offering flexible and powerful retrieval capabilities. Finally, the article notes that the Property Graph Index uses the PropertyGraphStore abstraction to store and retrieve graph data, providing extensive resources for users to learn more. Overall, the Property Graph Index significantly enhances existing knowledge graph functionalities, supporting more complex application scenarios with greater flexibility and efficiency.

Using Vertex AI Grounding with Google Search

Google Cloud Blog|cloud.google.com

AI score: 91 🌟🌟🌟🌟🌟

The article introduces how to utilize the grounding feature with Google Search in Vertex AI to enhance the accuracy and reliability of large language models (LLMs). The article first highlights the issues LLMs may face, such as generating incorrect, outdated information, lacking citations, and not being able to access private data. By enabling grounding with Google Search, the model can generate more reliable responses based on the latest public knowledge and provide sources for the information. The article demonstrates the practical effects of this feature by comparing the model's responses before and after enabling grounding. For example, when asked about Arsenal FC's game results and the weather in London, the model with grounding enabled can provide accurate and cited answers. The process to enable this feature is straightforward, requiring just a few settings in the Vertex AI console. Additionally, the article provides code examples in Python and C#, showing how to integrate Google Search grounding into applications. These examples allow readers to easily implement this feature in their projects.

[Week of 5/27] LangChain Release Notes

LangChain Blog|blog.langchain.dev

AI score: 93 🌟🌟🌟🌟🌟

LangChain v0.2 has introduced versioned docs, and LangSmith has added off-the-shelf evaluator prompts, plus dataset splits and repetitions. The article also highlights a new contest with NVIDIA and upcoming meetups in New York City and San Francisco.

Anthropic’s Claude 3 Opus and tool use go GA on Vertex AI | Google Cloud Blog

Google Cloud Blog|cloud.google.com

AI score: 91 🌟🌟🌟🌟🌟

Anthropic’s Claude 3 Opus, tool use, and provisioned throughput are now available on Google Cloud's Vertex AI. The announcement marks a significant milestone as the Claude 3 model family becomes generally available, offering capabilities ideal for complex tasks across various industries. Key features include assured performance with provisioned throughput, and enhanced flexibility and control with tool use, enabling models like Claude 3 to interact autonomously with external tools and data sources.

Design Review: Application of "Cognitive Bias" in Design

Clip设计夹|mp.weixin.qq.com

AI score: 93 🌟🌟🌟🌟🌟
Design Review: Application of "Cognitive Bias" in Design

The article discusses the concept of "cognitive bias" and its application in design to drive business results. It explains what constitutes "good design" from both aesthetic and functional perspectives and provides a detailed analysis of how cognitive biases can be utilized to enhance design effectiveness. Specific design cases and their psychological underpinnings are explored in depth. - Defines "good design" and its business impact - Describes cognitive bias and its role in perception and decision-making - Case studies of design applications using cognitive bias - Analysis of design strategies and optimization methods

Finding Customers in Specific Scenarios

人人都是产品经理|woshipm.com

AI score: 91 🌟🌟🌟🌟🌟
Finding Customers in Specific Scenarios

This article delves into key issues in marketing strategies, emphasizing the correct approach to understanding user needs. It points out that marketers often mistakenly believe they can understand customer needs from an office setting, whereas true understanding and satisfaction of user needs come from immersing oneself in the customer's actual environment and observing consumer behavior. This is the foundation of all marketing promotions and brand building. The article outlines the five stages of the user purchase journey: tasks, information gathering, comparison and evaluation, purchase, and sharing. It emphasizes that task-driven marketing is crucial because tasks stem from users' specific needs, desires, and self-awareness. In the marketing process, brands need to find touchpoints at each stage of the user's purchase journey. Furthermore, the article stresses the importance of avoiding market noise and focusing on specific user scenarios. Only in specific scenarios can marketers accurately identify users' concrete needs and propose suitable solutions rather than striving for perfection. The article also elaborates on the distinctions between needs, pain points, itching points, and pleasure points. Needs are the problems and goals users have in specific contexts; pain points are needs that current solutions cannot fully satisfy; itching and pleasure points fulfill deep-seated user needs and provide immediate gratification. Finally, the article highlights the importance of focusing on specific individuals, including direct and indirect beneficiaries, and analyzes the needs and decision-making processes of different types of users. In summary, the article underscores the significance of tasks, scenarios, pain points, and specific individuals in marketing strategies, proposing a method that bases effective marketing strategies on tasks and scenarios, combined with the needs of specific groups.

In-depth | From Low to $4 Billion Valuation: Deconstructing Webflow's Product-Driven SEO Strategy

人人都是产品经理|woshipm.com

AI score: 91 🌟🌟🌟🌟🌟
In-depth | From Low to $4 Billion Valuation: Deconstructing Webflow's Product-Driven SEO Strategy

This article analyzes Webflow's success through its product-driven SEO strategy. Key takeaways include: - Understanding User Intent: Webflow aligns its content with the four types of user search intent: informational, commercial investigational, navigational, and transactional. - Value-Driven Content: Webflow's blog content, particularly articles like "8 best cheap domain registrars compared and reviewed," targets long-tail keywords related to user needs and subtly promotes its product as a solution. - Strategic CTAs: Webflow utilizes clear CTAs, tailored to different user personas, to drive product trials and highlight the value proposition of a freemium model. - Templates for Faster Sales: By offering free, customizable templates, Webflow shortens the traditional B2B SaaS sales cycle by allowing users to experience the product's value before committing. - Freemium Model for Acquisition: Webflow's freemium model, with no credit card required and no trial period, encourages widespread adoption, turning free users into paying customers over time.

Huawei Project Management: Why Is It So Strong?

笔记侠|mp.weixin.qq.com

AI score: 90 🌟🌟🌟🌟

"Projects are the foundation and cells of company management. If you understand project management, you are qualified to be a 'commander'." This article deeply analyzes the strengths of Huawei's project management, systematically showcasing its core advantages and successful experiences. The main points are as follows: 1. Practical Foundation: Huawei systematically summarizes and refines successful experiences through project practices across multiple clients and industries. This practical knowledge base makes project management methods more practical and operable. 2. Systematic Development: Huawei's project management has gone through four modernization stages: specialization, systematization, digitalization, and value orientation. Each stage is optimized for different challenges, ensuring continuous evolution and improvement of the project management system. 3. Customer-Centric Approach: From individual projects to project groups and portfolios, Huawei gradually shifts the focus of project management from contractual delivery to value delivery centered on the customer, enhancing customer satisfaction and the ultimate value of projects. 4. Talent Development: Huawei cultivates and selects project management talent through practical experience, using the HEROS and BEST models to ensure that project managers possess professional skills and practical experience. This talent development mechanism is key to project success. 5. Intelligent Digital Platform: Huawei has built the ISDP digital platform, achieving visualization and efficiency in project management, thereby enhancing management efficiency and project transparency. 6. Project Management Culture: Emphasizing teamwork, open innovation, and contractual spirit, Huawei forms a "project-centered" corporate culture. This culture is an important support for project success. 7. Forward-Looking Thinking: Huawei continuously observes the latest changes in project management, proposing "seven development trends" and "eight responses," making its project management system forward-looking and flexible enough to handle future challenges. Through systematic practice summarization, customer-centric value delivery, talent development mechanisms, digital platforms, and project management culture, Huawei's project management system provides a solid foundation for enterprises to tackle complex and changing challenges. The article not only reveals Huawei's successful experiences in project management but also offers valuable insights for other companies.

The Secret of User Feedback: 4 Dimensions to Enhance Your Product

人人都是产品经理|woshipm.com

AI score: 90 🌟🌟🌟🌟

User feedback is an essential way to gather product requirements. However, not all feedback is valid and the quality of feedback directly impacts product improvement and strategy formulation. The article outlines four dimensions for evaluating the quality of user feedback: dimensions of feedback, breadth of feedback, speed of feedback, and accuracy of feedback. These dimensions ensure that feedback is multidimensional, diverse, quickly obtainable, and accurate, allowing businesses to optimize and iterate their products effectively. Key Points: 1. Dimensions of Feedback: Incorporate all user behaviors and judgments, both active and passive. 2. Breadth of Feedback: Diverse feedback covering different user demographics and product usage scenarios. 3. Speed of Feedback: Fast feedback loops from user perception to company response. 4. Accuracy of Feedback: Ensuring feedback is genuine, clear, and verifiable. 5. Two-Way Feedback: Companies should also provide feedback to users to improve the experience.

Multi-Channel Customer Acquisition Strategies for B-End Internet Products

人人都是产品经理|woshipm.com

AI score: 90 🌟🌟🌟🌟

This article comprehensively discusses the challenges and strategies for customer acquisition in B-end internet products. It emphasizes the differences between B-end and C-end customer acquisition methods and provides a detailed analysis of various online and offline channels, including SEO/SEM and social media. The article also highlights the importance of understanding where the customers are and the need for a diversified and sustainable approach to customer acquisition.

MEUX 'May' AI Design Insights

百度MEUX|mp.weixin.qq.com

AI score: 88 🌟🌟🌟🌟

MEUX's AI Design Insights series provides a regular summary of domestic and international design trends, offering the latest industry news. This issue covers advancements in AI models like GPT-4o, Microsoft's GroupMe update, Flowith's innovative chat interface, and the emergence of Vidu as a competitor to Sora in video generation.

Pricing Strategies for Overseas SAAS Products

人人都是产品经理|woshipm.com

AI score: 86 🌟🌟🌟🌟

The author discusses their experience pricing a design tool SAAS product, considering factors like competition, user base, and subscription models.

In-Depth Analysis|Self-Check and Design of Nine Interactive States

人人都是产品经理|woshipm.com

AI score: 92 🌟🌟🌟🌟🌟
In-Depth Analysis|Self-Check and Design of Nine Interactive States

Understanding the various interactive states users may face in different scenarios is an important task for UX designers. A comprehensive and clear anticipation of these states benefits designers, particularly newcomers, in two ways. It ensures the completeness of the solution delivery, making the product more usable and easy to use, and helps quickly identify and fix potential issues during the walk-through phase after product development. The article explores nine categories of interactive states subdivided into 38 detailed states, with design considerations provided for each.

Deep Dive: What is the Hottest AI Incubator Doing in the AI Era?

深思SenseAI|mp.weixin.qq.com

AI score: 94 🌟🌟🌟🌟🌟

AI Grant, known as the AI version of YC, is an early-stage investment firm specializing in AI technologies. With a focus on practical technical products, AI Grant has invested in several successful projects, including AI search engines, AI-driven image products, and AI-powered video editing tools. The founders, Nat Friedman and Daniel Gross, are recognized for their deep understanding of both technology and investment, making AI Grant a significant trendsetter in the AI investment landscape.

Alibaba Chairman Tsai Compares AI Training to Raising Children, Forecasts Rapid Progress

腾讯科技|mp.weixin.qq.com

AI score: 93 🌟🌟🌟🌟🌟
Alibaba Chairman Tsai Compares AI Training to Raising Children, Forecasts Rapid Progress

At the 20th Global China Summit held in Shanghai, Alibaba Group Chairman Daniel Zhang discussed with Morgan Stanley's North Asia Chairman and Vice Chairman of Investment Banking for Greater China, Kam Shing Kwang. Zhang shared his insights on artificial intelligence, likening the training of AI models to the education of children, and suggested that AI could potentially surpass the academic level of a human PhD in just three to four years. He emphasized the importance of the deep integration of cloud computing and AI for Alibaba, and mentioned the company's two core business areas: e-commerce and cloud computing. Zhang also talked about Alibaba's reorganization, which empowered business unit managers with greater autonomy, and introduced the new CEO, Wu Yongming. In the field of AI, Zhang believes that machine intelligence will continue to advance and highlighted Alibaba's large language model "Tongyi Qianwen," as well as the company's contributions to the open-source AI community through ModelScope. He also discussed examples of AI applications in vertical domains, Alibaba's growth targets over the next decade, aiming to achieve double-digit growth by March 2027, and addressed challenges such as regulatory environment, competitive pressure, and geopolitics, as well as how the company is tackling these issues. Finally, Zhang shared his leadership style and the importance of self-discipline and adequate sleep for maintaining health and peak performance.

Paul Graham, the Startup Guru of Silicon Valley, Writes a 20,000-Character Long Article: How Can Ordinary People Achieve Great Things?

Founder Park|mp.weixin.qq.com

AI score: 93 🌟🌟🌟🌟🌟

Paul Graham, the founder of Y Combinator, the godfather of Silicon Valley startups, and the author of "Hackers & Painters," published an article discussing how to achieve outstanding achievements. The article outlines practical steps to achieve great success, including choosing work that ignites personal interest and leverages one's talents, continuous learning and identifying gaps in knowledge, maintaining curiosity and resilience, balancing work without causing fatigue, and pursuing ambitious goals in different industries. The article emphasizes the importance of selecting suitable work, learning enough knowledge to reach the forefront of a field, noticing gaps in the field, and exploring promising opportunities within those gaps. Graham also points out that individuals who achieve outstanding success typically spend a significant amount of time on a problem and require effort, sincerity, and intellectual honesty in their work. He mentions that originality, unconventional ideas, breaking the rules, maintaining broad curiosity, focusing on important matters rather than irrelevant ones, and staying genuine while doing significant work are all key to achieving great success. Additionally, he discusses topics such as choosing problems, generating new ideas, dealing with project procrastination, balancing work and relaxation, and cultivating and protecting one's morale. The article ultimately encourages readers to consciously decide whether to attempt great achievements and highlights the role of curiosity throughout the process.

Interpreting the Large Model Price War: The Urgent Giants, the Calm Model Manufacturers, and Entrepreneurs

Founder Park|mp.weixin.qq.com

AI score: 92 🌟🌟🌟🌟🌟

This article provides an in-depth analysis of the background, impact, and future trends of the current large model price war. Since DeepSeek’s price cut, major companies such as ByteDance, Zhipu, Alibaba, and others have followed suit, triggering a wave of price reductions, even offering models for free under certain conditions. The primary goal of these price cuts is to attract developers by lowering trial costs and promoting cloud and other product sales. The article points out that despite the widespread attention from the big companies' price cuts, model startups are not panicking because these cuts have many conditions, and the actual usage costs have not significantly decreased. Performance remains a key factor for developers, and the price war has limited actual impact on them. What really matters is the model's performance and business risk. The article also mentions, "Regardless of whether it’s for large companies or model startups, reducing Token costs is an inevitable trend," indicating that future Token prices may become negligible, fostering the prosperity of the large model ecosystem and benefiting companies along the industry chain. Future business models may evolve in two paths: serving customers for free to achieve large scale or charging users directly to achieve high profitability. As the article states, "The aggressive cloud vendors' intentions are obvious: to attract a large number of trial developers by lowering trial costs; to enhance cloud and other product sales by reducing model costs." In summary, while the price war brings challenges, it also offers more opportunities and market education for the industry. Model vendors need to continuously innovate in technology and business models, reduce costs, and improve performance to remain competitive.

Apple's 'Assistive Feature' Predicts the Future of iPad Interaction

爱范儿|ifanr.com

AI score: 91 🌟🌟🌟🌟🌟

Apple's latest update to iPadOS 18 introduces eye-tracking technology, suggesting a new direction for iPad interaction. This feature, initially seen in the Vision Pro, allows users to control applications and navigate menus through eye movements, enhancing convenience and efficiency. The technology leverages machine learning and existing hardware to provide a seamless experience across all devices running iPadOS 18. This advancement not only expands the iPad's capabilities but also raises questions about privacy and the future integration of AI in user interfaces.

Exploring the Launch of Tencent's AI Assistant Yuanbao: Insights from Tencent's Hybrid Large Model Leader

腾讯科技|mp.weixin.qq.com

AI score: 91 🌟🌟🌟🌟🌟

This article discusses the launch of Tencent's AI assistant, Yuanbao, and the strategic thinking behind its development. 1. The AI product market is still in its early stages: Despite the high enthusiasm in the AI industry, the penetration rate of AI products is less than 1%, indicating a vast potential for market growth. 2. The design philosophy of Tencent Yuanbao emphasizes a simple interface with powerful functions, focusing on efficiency and entertainment scenarios, offering capabilities such as AI search, AI summarization, and AI writing. 3. Technical advantage: Tencent's self-developed Angel machine learning platform has significantly improved training and inference speeds, supporting the efficient operation of large models. 4. Ecosystem integration: Tencent Yuanbao integrates various internal ecosystem resources, such as WeChat Official Accounts content, as well as external search engine resources. 5. Open platform and resource sharing: Tencent's intelligent agent open platform "Yuanqi" provides developers with free model resources and distribution channels. 6. Commercialization and promotion strategy: Tencent Yuanbao is currently not considering charging users, with a focus on enhancing user experience and empowering other mature products. 7. Combating homogenization: Tencent leverages its advantages in product capabilities, engineering capabilities, and technological innovation, as well as deep integration with its ecosystem, to address the issue of homogenization among AI assistant products. 8. Content visibility and copyright protection: Tencent Yuanbao considers the copyright of content creators when integrating content and uses intelligent agents to enhance content visibility and the ability to discern authenticity.

Silicon Valley VC Zhang Lu: Silicon Valley's Large Model Market is Divided into Three Categories, with Rapid Iteration in Three Major Application Areas

量子位|qbitai.com

AI score: 91 🌟🌟🌟🌟🌟
Silicon Valley VC Zhang Lu: Silicon Valley's Large Model Market is Divided into Three Categories, with Rapid Iteration in Three Major Application Areas

This article delves into the current state and future development of the large model market in Silicon Valley. At the China AIGC Industry Summit, Silicon Valley investor Lu Zhang highlighted that startups can optimize industry-specific models by combining large model APIs with open-source models in a "cocktail" approach. She emphasized that AI is a super tool driving the digital transformation of entire industries, though only one-third of the opportunities are available to startups despite the enormous potential. The article outlines several challenges AI faces at the infrastructure level, including high computing costs, high energy consumption, data privacy, and latency issues. Lu Zhang pointed out, "In Silicon Valley, the theme of AI is empowerment rather than disruption or transformation," and stressed that data quality is more important than quantity. She also mentioned that healthcare, financial insurance, and robotics are the fastest-evolving application fields. Key quotes: 1. "AI is an efficient super tool representing the trend of digital transformation across entire industries." 2. "Empowerment means not only startups but also large tech companies can be empowered." 3. "In specific application scenarios and industries, training small models specific to the industry can perform as well as general large models." In summary, the article emphasizes the critical role of infrastructure and the importance of high-quality data, offering valuable advice for startups in AI applications.

Li Feifei's Classic Dialogue with AI Pioneer Hinton: A 25,000-Word Record (Full Text + Video)

Web3天空之城|mp.weixin.qq.com

AI score: 91 🌟🌟🌟🌟🌟

This article documents a historic dialogue between AI pioneers Li Feifei and Geoffrey Hinton, discussing the development of AI, particularly in the field of computer vision. The conversation, spanning 110 minutes, covers the creation of ImageNet, a pivotal dataset in the advancement of deep learning, and its impact on the AI community. The article also highlights the challenges faced by both researchers in their pursuit to revolutionize the field of AI.

Do These 5 Things for More Powerful Thinking

笔记侠|mp.weixin.qq.com

AI score: 90 🌟🌟🌟🌟

This article provides a detailed introduction to five simple and effective methods to enhance thinking abilities. Here are the specific methods: 1. Sequence Recall Method: This method involves recalling the content you have read or watched after a certain interval to train memory and information retention. For example, after reading several articles or watching several videos, take a break and then try to recall the order and key points of these contents. The key points of this method are to recall after a certain interval, avoid looking at the answers, and try to recall in order. 2. Feynman Learning Technique: This technique involves deepening understanding by simulating explaining new knowledge to others. The specific steps include explaining the core content of the knowledge point (what it is), describing its background and purpose (why it is), and summarizing its application (how to do it). This method helps to reinforce understanding of the knowledge, making it better absorbed and internalized. 3. Structured Thinking Method: This method helps in organizing thoughts and expressing viewpoints more clearly by clarifying points, reasons, and evidence. Specific training methods include briefly summarizing the viewpoint, listing the reasons supporting the viewpoint, finding evidence for each reason, and integrating them into a complete argument. This can make expressions clearer and logic more rigorous. 4. Sensory Immersion Method: This method involves focusing attention on sensory experiences to enhance concentration. It is suggested to choose a quiet outdoor environment and concentrate on sensory experiences such as sight, hearing, and smell, avoiding analysis or thinking. This can effectively improve perception of the current environment and enhance the focus of attention. 5. Pre-Sleep Guidance Method: This method suggests reviewing interesting and valuable experiences of the day before sleep, avoiding the repeated recall of negative information to optimize memory. The specific approach is to review and record positive and meaningful events that happened during the day before going to bed every night, strengthening the brain’s memory of these positive information while avoiding recalling negative events to maintain a positive mindset. The article not only provides detailed steps and usage tips for each method but also encourages readers to integrate these methods into their daily lives gradually forming habits, thereby achieving comprehensive enhancement of thinking abilities.

The Life Algorithm of the 'King of Quant': Five Key Principles

华尔街见闻|mp.weixin.qq.com

AI score: 89 🌟🌟🌟🌟
The Life Algorithm of the 'King of Quant': Five Key Principles

Jim Simons, through the establishment of Renaissance Technologies, has demonstrated his extraordinary achievements in the financial sector. This article delves into the five key principles behind Simons' success and reveals how he turned complex market challenges into opportunities through these principles. First, Simons emphasizes the importance of pursuing beauty, which means finding elegant solutions to difficult problems. This is evident not only in his financial strategies but also in his approach to teamwork. By creating an environment that encourages innovation and open communication, he successfully coordinated a group of highly intelligent and confident individuals to work together. Second, Simons understands the significance of surrounding himself with smart people. His success lies in finding individuals smarter than himself and attracting them to join his team. He provides these talents with great freedom and the best infrastructure, encouraging them to collaborate and exchange ideas. This approach not only sparks creativity within the team but also drives continuous innovation. Third, Simons values the principle of not following the crowd. When faced with market problems, he encourages his team to avoid conformity and seek unique solutions. If everyone comes up with the same approach, they should look for new, original paths. This commitment to originality has allowed Renaissance Technologies to stand out in a competitive market. Fourth, Simons' success is rooted in his persistence. From establishing the fund to finding the right combination of strategy, talent, and technology, he spent ten years in the process. This journey was filled with learning, experimentation, and continuous improvement, ultimately creating an efficient system that connects talent, strategy, and capital. Finally, Simons maintains an optimistic attitude. He acknowledges the significant role luck plays in success. Whether in good times or bad, he remains humble about luck, being both grateful and cautious. Simons believes in the importance of expecting good fortune and sees this optimism as an integral part of his work.

The Three Transitions from Employee to Boss

刘润|mp.weixin.qq.com

AI score: 88 🌟🌟🌟🌟

1. The key to becoming a good employee lies in proactively taking on responsibilities and accumulating scarce skills to enhance one's value. 2. To become a good manager, one must govern the organization through system design, achieving self-management and efficient operation. 3. Becoming a good boss requires adhering to core values, centering on the user, and providing genuine products and services without resorting to deceptive practices.

Multi-tasking with Minimized Custom Tabs

Chromium Blog|blog.chromium.org

AI score: 88 🌟🌟🌟🌟

In the latest Chrome update, the Minimized Custom Tabs feature has been introduced, allowing users to minimize custom tabs into a compact floating image in picture-in-picture (PiP) mode by clicking the minimize button on the toolbar. This enables users to switch more seamlessly between native apps and web content, enhancing their multitasking capabilities. Starting with Chrome version M124, developers can automatically provide users with this new feature without any additional action. Users can easily restore the minimized tab to its original size by clicking on the floating window. Additionally, the Chromium team hopes that other browsers will also adopt similar functionality.