Family, there is a super big news in AI circle recently, OpenAI officially launched ChatGPT Agent! In the past half year, the Agent concept has been super hot, but not many of them have really been realized into products. The appearance of ChatGPT Agent is definitely a milestone!
It simply doesn't have enough highlights! The 3-in-1 system integrates Operator, Deep Research and ChatGPT ontologies to build a unified intelligence system. There are also built-in tools, such as graphical/textual browser, terminal and API caller, which are very useful and easy to use on cell phones, and the results are automatically pushed when the task is completed, which is very considerate. It connects to third-party apps like Gmail and GitHub, so it's perfect for embedding into our workflows. The performance is also leading, in a number of benchmark tests, performance is superb, comprehensive performance industry-leading. And it's flexible, with quotas for different users and the ability to scale on demand.
From life scenarios like wedding preparations to creative tasks like customizing stickers, it can handle them all with ease. When performing tasks, we can also interrupt at any time, modify commands, and even manually take over browser operations.
It is trained in complex tasks through reinforcement learning and integrates the capabilities of various parties. It's also easy to use: select "Agent Mode" from the "Tools" drop-down menu in the bottom left corner of the chat interface, and the results are automatically pushed. It has been well received by the market, setting new records in benchmark tests.
In the future, the AI Agent availability bar is pulled up and the browser will be the key platform. Let's talk about what you can expect from ChatGPT Agent in the comments section!
#ChatGPTAgent #AI Intelligent Body #OpenAI Novelty #AI Application Breakthrough # Intelligent Body Technology
Baozi people, the official website of the China Securities Regulatory Commission has big news! Yu Shu technology has opened the listing counseling, counseling agency is CITIC Securities ~ counseling filing report also shows that Yu Shu technology's controlling shareholder, the actual controller is Wang Xingxing, he directly holds the company's 23.8216% shares, but also through the Shanghai Yu wing enterprise management consulting partnership (limited partnership) control of the company's 10.9414% shares, and control the company's 34.7630% shares! 34.7630% shares! What do you think of the road to the listing of Yu Shu Technology ah, come together to talk about it!
# Yu Shu Technology # Listing Counseling # Wang Xing Xing # CITIC Securities # Equity Control
ChatGPT's macOS desktop application recording mode is now available worldwide, and it's a great feature that will make your work efficiency take off! 🤩
🌟 Recording mode is super powerful
Just click the Record button at the bottom of the chat window to capture microphone and system audio for up to 120 minutes at a time. The recorded audio is uploaded to the server for processing, and structured notes are generated, such as summaries, key points, action items, and timestamps, and saved in a private canvas. And the original audio is deleted after transcription, so you don't have to worry about data security. Real-time transcription is so sweet that you don't have to manually take notes during meetings or brainstorming sessions, ChatGPT automatically organizes them into clear documents. The generated canvas can also be manually edited or further processed, and can be converted into project plans, email drafts and even code frameworks, making it super flexible! 🎉
💡 Privacy and Compliance to Watch
OpenAI emphasizes that this feature must be used in accordance with local laws and regulations, and with the explicit consent of the person being recorded, and Plus users can disable the "Improve model for everyone" option in the settings to prevent transcribed text and canvas from being used for model training. Different versions also have different privacy settings, so be sure to check them out before you use them to avoid stepping into the privacy minefield! 😜
🌐 Multi-scenario application is super practical
This recording mode comes in handy in so many scenarios:
Meeting minutes: automatically generate time-stamped meeting summaries and action items, reviewing decisions is super easy.
Brainstorming: capturing inspiration and organizing it into structured notes for easy follow up and execution.
Voice annotation: record ideas at any time and turn them into actionable tasks or plans.
Code generation: developers voice describe the requirements and turn them directly into a code framework. And the generated canvas can be referenced in subsequent conversations, accumulating knowledge across conversations and making it super easy to look up information! 👏
📈 New breakthroughs in productivity tools
This feature is really a major advancement of AI in productivity, with seamless integration of audio transcription, streamlined meeting recording, intelligent summarization and multi-format output saving a lot of time. Simple to use and powerful, it's a handy tool for professionals, students and creators alike. However, there are some minor shortcomings, the lack of speaker recognition, multi-person scenarios may not be too friendly. But it would be perfect if speaker segmentation and multi-language optimization can be added in the future! 🤗
🎯 The future outlook is super promising
OpenAI says this is just a big step towards becoming a comprehensive productivity assistant. In the future, it will optimize the accuracy of multilingual transcription, may be extended to Windows and mobile devices, and may be integrated with other tools to become a cross-platform intelligent assistant! Isn't it super exciting? 😆
Poeple, go update to the latest version of the ChatGPT macOS app (requires macOS 14 + and Apple Silicon) and get instant access for $20 per month for subscribers. To learn more, go to the official OpenAI website (openai.com) or the Help Center (help.openai.comLook at this.
How does everyone feel about using this feature? Share it with us in the comments section!
Baozi people, following the "AI Sun Yanzi" fire, the AI singer track is lively again! 🎉
Recently, there is a super cool AI singer Yuri, with blue highlights, an Asian face, and a skull microphone, it's awesome! 😎 Last month it released its first AI music MV "Surreal" directly in the whole network burst fire, the play volume of more than 7 million, but also many times on the B station hot list, the North Face (The North Face) are looking for it to cooperate with it, this is no one face! 👏
Yuri & The North Face
Yuri is not the only one, but an AI band "The Velvet Sundown" has also quietly become popular overseas! The Velvet Sundown released five singles in a month, and has amassed more than 1.1 million listeners on Spotify and other streaming platforms. The band's retro jazz sound is so good you can't tell if it's AI or a real band playing it! 🤩
Timbaland, a famous American producer, also came to join in the fun, high-profile launch of the first AI idol TaTa, but also tried to define a new music genre "A-Pop" (AI-Pop), this wave of operation is really 666!👍
Now the AI singer is not simple, from AI covers to AI "original", IP incubation, all the way to the evolution of high-quality works, with fan effect and commercial value of the creators! When the technical barriers are slowly broken down, successful AI IP is established, and TaTa has become the first AI native personality with commercial endorsements! 👏
Moreover, AI's impact on the advertising industry is more than just "using AI to make ad spots", but more importantly, it has changed the entire traffic structure and attention market. In the future, the cost of content production will be low, the supply will grow explosively, the key to advertising will no longer be "production", but "how to be seen", and media channels will become highly fragmented, which is the far-reaching impact on the industry! 😜
What do you think about AI singers and their impact? Let's talk about it in the comments section.
#AI Singer #AI Music #AI Idol # Music Genre # Advertising Industry Change #AI Original # Business Value
Poons, in today's rapidly evolving AI world, an awesome MCP protocol has been born! 🤩
MCP protocol, known as Model Context Protocol (Model Context Protocol), is an open standard protocol proposed by Anthropic and open source. Its appearance is simply too timely, a perfect solution to the problem of connecting AI assistants and various data systems, so that AI systems can more reliably obtain data and give relevant and high-quality responses, which brings a lot of convenience to developers and enterprises! 👏
🔍 Core components are ultra-critical
The MCP protocol core architecture has three important components:
MCP Host: Like the commander, it is the system initiator and contains the MCP client application, which is responsible for sending requests to the MCP server to obtain data and functional support according to user requirements.
MCP Client: As an intermediate bridge, it is responsible for communicating with the MCP server, accurately forwarding the requests from the MCP host, and then sending the results returned by the server back safely to ensure the smooth operation of the system.
MCP Server: A back-end service that provides specific functionality. It is lightweight and can be a local Node.js or Python program, or a remote cloud service, adapting to various application scenarios and deployment needs.
📶 Ultra-flexible communication mechanisms
The MCP protocol communication mechanism is based on JSON-RPC2.0 protocol and supports two communication methods:
Local communication: through the standard input and output and local server interaction, the data security requirements of high scenarios is super suitable, such as internal processing of sensitive data within the enterprise, can ensure that the data in the local security transmission.
Remote communication: HTTP connection based on SSE (Server-Sent Events), with awesome support for cloud services, meeting large-scale data processing and distributed computing needs.
💥 Super wide range of application scenarios
The MCP protocol is used in a huge variety of scenarios, covering almost every area where AI needs to be tightly integrated with data systems. Although it is not mentioned in detail here, you can imagine that it can be very useful in many industries!
What do you think about the MCP protocol? Let's talk about it in the comments section!
#MCP Protocol #ModelContextProtocol #AI Protocol # Data Connection # Core Components # Communication Mechanisms
Gemini Live, Google's intelligent voice assistant, is getting a big upgrade! 👏
Gemini Live Extends Application Connectivity with Upgraded Functionality
It will soon be deeply integrated with so many Google apps, practicality and intelligence directly pull full, properly to become a super powerful productivity tool! 🤩
This time, we've expanded our app connectivity to include popular apps like Google Maps and Google Calendar, as well as third-party apps like Spotify and YouTube Music. With natural voice interaction, you can easily control them, such as creating events in Google Calendar and playing your favorite songs on Spotify! 🎉
What's more, it's added camera-based input. Show a concert poster or a handwritten list, and it recognizes the information and acts on it in the corresponding app, like adding an event to Google Calendar or jotting down a list in Google Keep... so cool! 😎
Smarter Interaction: Real-time Information and Card-based Interface
Interaction is also smarter, the new card-based interface will show real-time information from Google apps in the dialog, such as asking for location information, and extracting data directly from Google Maps to present navigation options in the form of cards, so you don't have to switch back and forth between different apps. And there are also plans to introduce a feature similar to Circle-to-Search, making search and operation more flexible and handling complex tasks more powerful! 💪
Privacy is also guaranteed, as users can turn off the connection at any time, and chat data will not be used to train AI models after specific settings are turned off.
Google wants to make it a unified AI control center that may support more services and apps in the future, and maybe control smart home devices! 🤗
Progressive push, some users can already experience
The new features are currently being pushed out in phases, and some users have been able to experience some of the features, so you can try voice commands to see if your device has the new features enabled! 🤔
Pozi, are you looking forward to this upgrade of Gemini Live? Let's talk about it in the comments section!
Baozi people, millet car this time really zoomed in! June 26 millet car's first SUV model -- millet YU7 officially listed, a large set of channels to open the direct detonation of the market, the booking of an hour large set of orders exceeded 289,000 units, this achievement is simply absolute! 👏
🌟 Super eye-catching appearance The exterior design of Xiaomi YU7 is so attractive! The front has the same family design as the SU7, with a closed grille and a decorative panel of the same color in the center of the front surround, which is exquisite and harmonious. The headlights are similar to SU7 in outline, but full of details: the upper part is hollowed out and embedded in the air ducts, which opens up to the front hatch to optimize aerodynamic performance, and it is also upgraded to 180-degree super wide-angle lighting for a better and safer night-time driving view. The rear of the car has a symmetrical C-shaped taillight cluster with transparent lampshades, giving it a superb sense of technology. The hollowed-out spoiler and "ducktail" rear spoiler on the rear roof and along the lower edge of the rear windshield not only look good, but also optimize airflow and improve driving stability. It also has 9 exterior paint colors to choose from, like Jewel Green and Titanium Metallic, and four color schemes for the interior, including Pine Grey, to meet the personalized needs of different po-po-po's~🥰
🚗 Super spacious Xiaomi YU7 is positioned as a medium-large pure electric SUV, with dimensions of 4999 mm (length), 1996 mm (width) and 1600 mm (height), a wheelbase of 3000 mm, and a spacious 5-seat layout. Compared with the Zhijie R7 Pure Electric Edition and Avita 11 Pure Electric Edition, the length, width and wheelbase of the body have an advantage, and even compared with the Tesla Model Y, except for a slightly lower height, the length, width and wheelbase are comprehensively beyond the spatial performance of the bar! 👍
🧠 Intelligence is super awesome Intelligence is the core competitiveness of Xiaomi YU7. In terms of intelligent driving, the whole series is equipped with NVIDIA Thor assisted driving chip as standard, as well as luxury perception hardware, 1 high-performance LIDAR, 1 4D millimeter-wave radar, 11 high-definition cameras and 12 ultrasonic radars, which form an all-around high redundancy perception system.Thor chip 700 TOPS arithmetic power, providing strong support for decision-making for complex scenarios. Moreover, the entire system comes standard with the Xiaomi End-to-End Assisted Driving System, which supports 10 million Clips, and Xiaomi's full-stack self-research strength is superb! The interior is a wrap-around cabin layout, consistent with the style of Xiaomi SU7, and the large-size floating center control screen is super cool. Also canceled SU7 flip full LCD dashboard, replaced with "millet sky screen panoramic display system", three Mini LED screen with panoramic surface projection technology, the key driving information projected on the lower edge of the front windshield, the display effect is superb! 🤩
The Xiaomi YU7 has had such a shocking start with orders, outstanding product power and an attractive price. Will it be able to turn orders into deliveries in a competitive market, hit the sales charts, and challenge the status of the Model Y? I'm really looking forward to it! What do you think about the Xiaomi YU7? Let's talk about it in the comments section 😜😜😜😜😜!
# Xiaomi YU7 # Xiaomi car # new energy vehicles #SUV models # intelligent driving # car listing # car review
Hey guys, when I was browsing GitHub last night, an open source project called WeClone went straight to #1 on the Hotlist, and it really surprised me! 😱
This project claims to be able to clone anyone's "digital doppelganger" through WeChat chat logs, speaking in exactly the same style not to mention that the voice can actually 95% be restored! 🤯
My first thought at the time was: this is too scary, isn't it? Imagine that dialog box that you haven't heard from in a while, and suddenly a voice pops up, with a voice, tone, and mantra that's nothing like the TA you remember, it's almost scary to think about! 🧐
🌟 Powerful and scary features
It's pretty simple to operate, exporting WeChat chat records and training AI models with the data to generate a digital doppelganger with the same chat style. What's even more exaggerated is the voice cloning, the official said that as long as 5 seconds of voice samples, you can clone a super similar voice. I immediately thought of my grandmother, who passed away last year, if I used this technology ...... I can't imagine what my reaction would be. 😟
And this technology threshold is not high, 16GB video memory game computer can run, the project is also open source, anyone can download and use for free. What does this mean? Someone could be building a "digital version of you" out of your chat logs without you even knowing it! 😰
💥 The netizens are up in arms!
Once the project was released, the online discussion exploded. Those who support it feel that they can "resurrect" loved ones who have passed away, so that love can continue, and those who do self-media can also use it to automate the operation of their accounts. 🥺
But the opposition was even stronger! People are worried about being used by bad people to scam, worried that the dead can not rest in peace, and even feel that this is the desecration of the dead. Indeed, if the scammers use this to impersonate family members for fraud, even the voice is the same, how can we tell the real from the fake? 😫
🤔 A fine-tuned application scenario
The official application scenarios such as personal assistant, content creation and digital immortality sound good, but the risk behind them is huge. In the future to take "acquaintances" phone, do not know whether the opposite is a real person or AI; chat records may be quietly taken to train AI, privacy leaks; there may be a deceased "digital doppelganger" manipulation of family members emotions, the law has not been standardized, do not know what to do in case of trouble. The right to defense. When my friend heard about it, she hurriedly deleted her chat records with her ex, in case she was cloned to cheat her current boyfriend, it's not impossible! 😂
😕 Are we really ready?
Needless to say, this is indeed a technological breakthrough that can help some people ease the pain of losing a loved one. But it is hard to imagine the consequences of the spread of technology, when it is not clear whether the opposite side is a real person or AI, the dead can "come back to life" to talk, what will the world become? As in the episode "Black Mirror," technology is advancing faster than human morality can prepare for. The key is not in the technology itself, but how to use it, powerful technology is a double-edged sword, depending on the user's motivation. 😖
The emergence of WeClone allows us to see how terrifying the speed of AI development is, and also makes us think about the boundaries between people and technology. Maybe in the future, we can let the people we love be with each other forever, but before that, we have to be prepared. 2025, the development of AI is beyond imagination, as an ordinary person, we have to embrace the convenience, but also to keep vigilant.
What do you think of this "microsoft clone" technology? Are you looking forward to it or are you afraid of it? Leave a quick comment with your thoughts! 😘
In technical exchange groups and community forums, I found that many front-end developers have difficulties when using AI: either asking vague questions and getting answers that can't be put into practice; or only using AI to do simple code completion, far from realizing its potential. This is like "begging for food with a golden bowl", obviously AI is a powerful tool in your hand, but you have only tapped into its value. In order to help you break these bottlenecks, I will share my practical experience and methodology for collaborating with AI in front-end development, which will help you efficiently master AI technology.
I. Redefining the relationship between front-end and AI
In the rapidly changing technology iteration, AI is no longer a bystander in the field of front-end development, but an important participant deeply integrated into the development process. As a developer who has been exploring the wave of front-end and AI convergence, I deeply realize that mastering the skills of using AI tools is only the foundation, and building a systematic AI thinking architecture is the key to stand out in the current competitive environment.
In the past, we viewed AI as a tool to assist in writing code and finding bugs, a perception that greatly limited its value. Today, AI has become a partner that can deeply collaborate with developers. In actual projects, I have faced complex performance optimization problems, and the traditional way requires a lot of time for code analysis and solution verification. With AI, through reasonable questions and interactions, it can not only quickly provide a variety of optimization ideas, but also evaluate solutions in the context of the actual project, significantly reducing the development cycle. This collaboration model shows that AI is no longer a "machine" that passively executes instructions, but an "intelligent body" that can think and solve problems together with developers.
II. Four-quadrant framework for AI dialogues: building a mindset model for efficient collaboration
Quadrant 1: Open (AI knows, people know)
When both the developer and AI have a clear understanding of the problem, this is the most direct and efficient collaboration scenario. For example, when developing React components, if the clear requirement is to realize anti-shake function with React Hook, you can directly give AI the instruction of "realize an anti-shake component with React Hook, require concise code with comments", and then you can get the result quickly. However, it should be noted that the more structured the instruction is (e.g. "step-by-step instructions + code examples + notes"), the lower the communication cost.
Quadrant 2: Blind (AI knows, people don't)
When facing unfamiliar technical issues, such as optimizing front-end page load speed, direct questions often get general answers. At this point, we should adopt a layered questioning strategy: first understand the common dimensions of performance optimization, then explore the priority of network request and rendering optimization, then ask about the specific optimization means of the React project, and finally ask for actual cases. Through the progressive questioning of "what→why→how→case", AI can avoid outputting invalid information.
Quadrant III: Unknown (AI does not know, people do not know)
When exploring the integration of new technologies, such as the combination of 3D models generated by AIGC and WebGL to realize interactive virtual exhibition halls, there is no ready answer for both humans and machines. In this case, AI should be regarded as a creative stimulation partner, obtaining ideas through cross-border questioning, and then combining with its own technical capabilities to make feasibility judgments and program iterations.AI's answers are creative materials, and developers need to sift, combine and verify them.
Quadrant 4: Hidden (AI doesn't know, people know)
Involving project-specific knowledge, such as the company's own research component library development specifications, you need to take the initiative to "feed" information to the AI. Uploading relevant documents and code snippets and then giving instructions will enable the AI to generate content that better fits the actual needs. Enterprises can establish a technical knowledge base and use RAG technology to realize the rapid invocation of internal data by AI; individual developers should also be clearly informed of the project constraints before collaboration to avoid AI generating unrealistic solutions.
From Tool Use to Thinking Architecture: The AI Advancement Path for Front-End Developers
1. Create a sense of positioning for AI collaboration
Before every interaction with AI, think about three questions: what is the nature of the problem, and what is the AI's mastery of the relevant technology stack? What proprietary information should be added? Take debugging a React component as an example, if the type of error is clear, it belongs to the Open quadrant, and you can directly seek a solution; if the cause of the error is vague, you need to enter the Blind quadrant, and adopt a layered questioning strategy.
2. Developing structured questioning skills
Especially in the Blind Quadrant, the "onion peeling" method of questioning can effectively improve the quality of information acquisition. Take learning WebAssembly as an example, from the core principle (what), to the reasons for solving the performance bottleneck of JavaScript (why), to the integration method in the React project (how), and finally to the actual application cases (scenario-based validation), we will go deeper and deeper. At the same time, the use of "if... then..." sentences to test the depth of understanding and strengthen the learning effect.
3. Building a Personal AI Collaboration Intelligence Repository
Organize commonly used tech stack documents, team code specifications, and historical project pitfall records into a Markdown format "AI Collaboration Manual". Asking questions with links to key chapters or explicitly referencing specifications in instructions enables AI to quickly understand the technical context and generate content that is more in line with expectations.
4. Stimulating innovative thinking and exploring uncharted territories
Use a "technical domain + non-technical domain + target scenario" questioning formula, e.g., "When ChatGPT learns front-end engineering, can it automatically generate scaffolding that meets the team's specifications? What data training is needed?" Encourage AI to think out of the box and explore the new boundaries of technology together. At the same time, we screen the solutions through technical feasibility analysis and carry out iterative optimization.
5. Dynamic adaptation of collaboration strategies
Regularly follow the updates of front-end AI tools and test the adaptability of new features in real projects. Record the types of problems encountered during AI collaboration and the quadrants they belong to, and analyze the distribution of your collaboration ability in different quadrants. If the Hidden quadrant has frequent problems, improve the internal knowledge base; if the Blind quadrant has more problems, strengthen the training on question disassembly.
Practical tool recommendation: covering the whole quadrant of the front-end AI collaboration matrix
Open Quadrant (AI is known to all)
Tools / Methods
Core competencies and scenarios
Cursor
- Natural language generation of complete code for React/Vue components (including Hook logic) - Support for real-time code debugging and bug fixing (e.g., automatic handling of Promise exceptions)
Codeium
- Context-based code completion (e.g., enteruseEffect(Automatically prompts for dependency array writes) - Generate test cases (Jest/React Testing Library)
Tabnine
- Smart function name recommendation (e.g. enterfetchDataFromauto-completeAPI) - Generate TypeScript type definitions (inferring return value types from function arguments)
Blind Quadrant (AI knows but no one knows)
Tools / Methods
Core competencies and scenarios
Raycast AI
- Breaking down complex problems (e.g. generating a layered solution for "React Performance Optimization": Network Optimization → Rendering Optimization → Component Optimization) - Querying framework source code in real-time (e.g. automatically parsing the implementation logic of React Router v6 Hooks)
WizNote AI Assistant
- Structured questioning of technical documentation (e.g. "How to integrate WASM in React" after uploading official WebAssembly docs) - Generation of knowledge brain maps (automated sorting of CSS-in-JS scenarios with comparative strengths and weaknesses)
DevDocs AI
- Cross-document retrieval (e.g., query MDN + React official website + community blogs at the same time, integrate "useContext best practices") - Code sample adaptation (automatically convert Vue3 examples to React writing style)
Hidden quadrant (known but not known to AI)
Tools / Methods
Core competencies and scenarios
PrivateGPT (Enterprise Edition)
- Uploading the team's component library specification and generating code that conforms to the specification (e.g., generating a Button component based on the Ant Design specification). - Parsing internal business documents (e.g., generating form validation logic based on e-commerce order system documents)
RAG-Stack (self-built knowledge base)
- Access to enterprise Git repositories, AI automatically learns historical project architecture (e.g., identifying a project's micro-front-end splitting strategy) - Generates problem troubleshooting processes based on internal failure documentation (e.g., diagnostic steps for "white screen problems")
LocalAI + Vector Database
- Secure handling of sensitive code (e.g., cryptographic algorithm modules for financial projects) - Generation of code styles that conform to team conventions (e.g., automatically formatting code according to team ESLint configurations)
Unknown quadrant.
Tools / Methods
Core competencies and scenarios
GitHub Copilot X
- Collaborative exploration of new architectures (e.g. AI to generate technical solution sketches for "React+WebAssembly for 3D editor") - Automated generation of technical feasibility reports (with performance estimates and risk point analysis)
- Generate cross-domain technology combinations (e.g. "LLM + Front-End Route Guard" for dynamic privilege control) - Provide technology roadmaps (e.g. migration steps from "Legacy SPA" to "PWA Provide a technology roadmap (e.g. migration steps from "Traditional SPA" to "PWA + Server Components").
V. Conclusion: Embracing AI, Reconstructing Front-End Development Thinking
The application of AI in the front-end field is not only an upgrade of tools, but also a change in the way of thinking. Mastering the four-quadrant framework of AI dialogue and building a systematic AI thinking architecture will enable us to transform from "AI tool users" to "intelligent collaboration leaders". In the future of front-end development, those developers who can master AI and collaborate with it in depth will surely have a head start in the wave of technology. We look forward to exploring more possibilities for the integration of AI and front-end development with your peers, and welcome you to share your practical experience and thoughts.
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