Manus emerges, ushering in a new era of Chinese technology
Who Exactly is Manus?
Manus, a name that has caused a stir in the AI field, originates from the Latin phrase "Mens et Manus," meaning the combination of mind and hand. It is the world's first general-purpose AI agent product released by the Chinese large model team Monica in the early hours of March 6, 2025. In the history of AI development, many products have shone like stars, but Manus stands out with its unique brilliance, carving out a new path.
Unlike traditional AI, which mostly plays the role of providing suggestions or answers, Manus can directly deliver complete task results, turning users' ideas from conception into reality. It is like a digital assistant with superpowers, running in an independent virtual machine and adopting a Multiple Agent architecture, capable of independent thinking, planning, and executing complex tasks.
In practical applications, Manus's performance is astonishing. When you need to screen resumes, simply send it a Zip file containing multiple resumes, and it will act like an experienced HR professional, automatically decompressing the file, browsing each resume page by page, accurately recording important information, and finally compiling ranking suggestions, candidate profiles, and evaluation criteria. The entire process is seamless, efficient, and accurate, greatly saving manpower and time costs. In travel planning, Manus also demonstrates strong capabilities. It can integrate information on flights, hotels, attractions, and more based on your budget, time, and interests, creating a detailed travel plan and a customized travel guide, making your trip more convenient and enjoyable.
From a technical perspective, Manus's Multiple Agent architecture allows it to break down complex tasks into multiple subtasks, achieving efficient task execution through the collaboration of multiple agents. This architecture is like a precise symphony orchestra, where each agent plays a different role, working together to create a beautiful performance. Additionally, Manus features cloud-based asynchronous execution, a secure isolated virtual machine environment, and multi-modal content generation, ensuring tasks run efficiently and securely in the cloud and can output content in various formats, including PPT, HTML, and audio-visual materials.
In the GAIA benchmark test, Manus performed exceptionally well, achieving new state-of-the-art (SOTA) results across all three difficulty levels, surpassing OpenAI's large models of the same level. This achievement not only proves Manus's powerful performance but also showcases the strength and potential of Chinese AI technology to the world.
The Technological Transformation Brought by Manus
(1) Breakthrough in Multi-Agent Architecture
Manus's multi-agent architecture is key to its powerful functionality. In this architecture, planning agents, execution agents, and verification agents each have their roles but work closely together, like a well-choreographed dance where each dancer knows their position and movements, creating a perfect performance.
The planning agent is like an experienced strategist, capable of breaking down complex tasks into detailed subtasks based on user needs and formulating a reasonable execution plan. For example, in a market research task, the planning agent analyzes the research objectives, determines the types of data to be collected (such as market size, competitor information, and consumer needs), and then plans how to obtain this data, whether through web scraping or by calling professional database interfaces.
The execution agent is the actual executor, carrying out subtasks according to the plan set by the planning agent by calling various tools and resources. It can write code like a skilled programmer to achieve data scraping and analysis functions; it can also browse the web automatically like a professional user, gathering the necessary information; and it can operate various applications to process and integrate data. In market research, the execution agent follows the planning agent's instructions, writing Python code to scrape product sales data from major e-commerce platforms, using data analysis software to clean and analyze the data, and generating preliminary reports.
The verification agent is responsible for quality control, checking and verifying the results of the execution agent to ensure accuracy and reliability. It uses a multi-model voting mechanism to validate the logic of the results. For example, when analyzing sales data, the verification agent checks whether the data trends are reasonable and whether the relationships between various indicators align with common sense. It also adapts the format of the results to ensure the generated report meets user requirements. If issues are found, the verification agent promptly feeds back to the execution agent, requesting corrections.
Compared to traditional AI tools, Manus's multi-agent architecture has significant advantages in task processing. Traditional AI tools often lack the ability to decompose and collaboratively handle complex tasks, making it difficult to complete multi-step, cross-domain tasks. In contrast, Manus's multi-agent architecture can automatically decompose and collaboratively execute tasks, greatly improving task processing efficiency and quality. It is like a well-trained special forces team, where each member has professional skills and can work together in complex environments to complete high-difficulty tasks.
(2) Leap in Performance and Accuracy
In the AI arena, performance and accuracy are crucial metrics for evaluating a product's quality, and Manus excels in these areas. In the GAIA benchmark test, Manus emerged as a dark horse, outperforming OpenAI's similar products with impressive results, showcasing its strong capabilities.
From the test data, at Level 1 difficulty, Manus achieved a pass rate of 86.5%, while OpenAI Deep Research only reached 74.3%; at Level 2 difficulty, both had the same pass rate of 69.1%; at Level 3 difficulty, Manus's pass rate was 47.6%, compared to OpenAI Deep Research's 42.3%. These data points clearly reflect Manus's advantages in handling tasks of different difficulty levels, especially in simpler and moderately difficult tasks, where Manus's performance is more prominent.
In practical applications, Manus's high accuracy has also been fully validated. When handling complex financial analysis tasks, Manus can accurately analyze stock trends and predict market movements. For example, when analyzing Tesla stock, it can quickly scrape large amounts of historical data, including stock prices, trading volumes, and market capitalization, and combine this with macroeconomic data and industry trends to conduct in-depth analysis using complex algorithms. Through data mining and analysis, Manus can accurately assess Tesla stock's investment value, providing investors with detailed investment advice, such as optimal buy and sell times and risk assessments. The accuracy and comprehensiveness of its analysis reports even surpass those of some professional financial analysts.
In the scientific research field, Manus also demonstrates strong capabilities. When processing vast amounts of academic literature, it can quickly and accurately extract key information for literature reviews and analysis. For example, in medical research, Manus can help researchers quickly filter out research findings related to specific diseases, analyze the effectiveness and safety of different treatment methods, and provide strong support for new research. It is like an indefatigable research assistant, capable of processing large amounts of information in a short time, saving researchers significant time and effort, allowing them to focus on more creative work.
The Profound Significance of Manus for China's Technological Development
(1) Enhancing Technological Autonomy
In the past, China's AI industry relied on Western core technologies, which limited the autonomous development of China's AI industry. The emergence of Manus has brought new hope to China's AI industry. Its multi-agent architecture and code agent design are important manifestations of China's original AI technology, successfully breaking the West's monopoly in the field of general AI agents.
This "full-chain autonomous execution" capability opens a new track for China in the competition for AI's underlying architecture. From the perspective of technological innovation, Manus's multi-agent architecture is not a simple combination of technologies but a new design philosophy. It breaks the limitations of traditional AI architectures, achieving efficient task execution through the collaboration of multiple agents. This innovative design allows China to explore technological paths that suit its national conditions and development needs without relying on Western technological frameworks.
For example, in the application of AI in the financial sector, Chinese financial institutions previously relied on foreign AI models and technical solutions for risk assessment. While these solutions met some needs, they also posed data security risks and technical adaptation issues. Manus provides financial institutions with a new option. Based on Manus's technical architecture, financial institutions can develop AI risk assessment systems tailored to their needs. Through the multi-agent architecture, the system can monitor and analyze financial data in real-time, quickly and accurately assessing risks. At the same time, being a self-developed technology, it offers better data security and adapts more effectively to the characteristics and needs of China's financial market.
(2) Stimulating Industrial Ecosystem Vitality
Manus's open-source strategy and toolchain integration are like a stone thrown into a calm lake, creating ripples that inject strong momentum into the ecosystem of China's AI developer community. It plans to open its inference module within the year, a move that will undoubtedly attract many developers.
For developers, the open-source technology provided by Manus is like a treasure trove, allowing them to build upon it and create more innovative AI applications. For example, if ByteDance's TikTok collaborates with Manus to test AI service functions, it will greatly promote the popularization of consumer-grade AI services. TikTok has a massive user base, and combining Manus's technology with TikTok's platform can provide users with more personalized and intelligent services. For instance, when users search for travel-related content on TikTok, Manus can recommend personalized travel guides based on their browsing history and preferences, directly generating travel plans that include transportation, accommodation, and attractions, making travel planning more convenient and enjoyable.
This "B-end payment + C-end traffic" dual-driven business model will attract more enterprises and developers to participate in the construction of the AI industry ecosystem. Enterprises can purchase Manus's technical services to enhance their business efficiency and innovation capabilities, while developers can develop applications based on Manus to gain commercial returns. This mutually beneficial model will promote the widespread application of AI technology across various fields, driving the prosperous development of China's AI industry ecosystem, forming an AI agent application ecosystem similar to Android.
(3) Enhancing Global Discourse Power
On the global AI competition stage, the emergence of Manus is like a shining star, once again proving the innovative capabilities of Chinese teams in the AI application layer. Its "asynchronous task processing + memory optimization" technical path provides a valuable practical sample for China's participation in global AI governance standard setting.
As AI technology becomes more widely applied, data privacy and ethical issues are increasingly gaining attention. Manus emphasizes data privacy protection and ethical norms during data processing and task execution. It uses a secure isolated virtual machine environment to ensure user data security and follows certain ethical guidelines during task execution to avoid unreasonable decisions. These practical experiences provide strong support for China in global AI governance standard setting, enabling China to play a greater role in global AI governance and enhancing China's discourse power in the global AI field.
For example, in the formulation of global AI data privacy protection standards, China can draw on Manus's data security processing experience to propose standards that align with China's national conditions and international trends. By actively participating in global AI governance standard setting, China can better safeguard its interests, promote the healthy development of global AI technology, and gain broader recognition and application for China's AI technology worldwide.
Manus's Impressive Performance in Practical Applications
Manus's powerful functionality is not just theoretical or limited to tests; its performance in practical applications is equally remarkable, demonstrating significant value across multiple fields.
In the human resources field, Manus is like an indefatigable recruitment expert, efficiently handling large volumes of resume screening. In the past, HR professionals faced mountains of resumes, spending significant time and effort browsing and screening them, often inefficiently and prone to errors. Manus has completely changed this scenario. For example, in the recruitment of software development engineers at an internet company, Manus received hundreds of resumes. After receiving the task, Manus quickly got to work, automatically decompressing the resume files, browsing each resume page by page, extracting key information such as education, work experience, project experience, and skill certifications. It then ranked the candidates based on preset job requirements and evaluation criteria. The entire process took only a few hours, completing work that would have taken HR professionals days, with more accurate screening results, saving HR significant time and effort, allowing them to focus more on subsequent interview processes.
In travel planning, Manus is a thoughtful travel butler, providing users with personalized, comprehensive travel services. A user planning a trip to Japan provided Manus with travel requirements, including travel time, budget, and interests. Manus quickly integrated information on flights, hotels, and attractions based on this information. It recommended suitable flights, considering factors such as distance between departure and destination, flight times, and prices; it filtered hotels that met the budget and location requirements, providing detailed information and user reviews; it planned a detailed travel itinerary, including daily attraction arrangements, transportation methods, and food recommendations. Finally, Manus created a customized travel guide for the user, allowing them to view the travel plan anytime, anywhere, making the trip more relaxed and enjoyable.
In the financial analysis field, Manus demonstrates professional strength, becoming a valuable assistant for investors. When analyzing Tesla stock, Manus connected to authoritative financial data sources via API, obtaining Tesla's historical stock data, including price trends, trading volumes, and market capitalization. It then used Python to write code for data analysis and visualization, generating a detailed stock analysis dashboard. The dashboard not only displayed key stock data and trends but also provided buy/sell recommendations and risk assessments. Through this dashboard, investors could intuitively understand Tesla's stock situation, making more informed investment decisions.
These practical application cases are just the tip of the iceberg for Manus's many application scenarios. From user feedback, we can also sense the immense convenience and value Manus brings. An HR professional using Manus for resume screening said, "Manus is a lifesaver for us HR professionals. It has greatly improved our recruitment efficiency, allowing us to find suitable talent faster. Moreover, its screening results are very accurate, reducing a lot of our workload." A user who experienced Manus's travel planning service said, "Planning trips used to be a headache, requiring a lot of time to research and arrange. But with Manus, everything has become simple. The travel plan it created for me was perfect, making my trip more relaxed and enjoyable." These user evaluations fully demonstrate Manus's strong capabilities and significant value in practical applications.
Challenges and Reflections on Manus
(1) Ethical and Social Risks
With the continuous development of AI agent technologies like Manus, their efficient execution capabilities bring convenience but also raise a series of ethical and social risks. Among these, the most concerning is the replacement of white-collar jobs. Manus can quickly and accurately complete repetitive, rule-based tasks such as resume screening and data analysis, putting some white-collar jobs at risk of being replaced.
For example, in the human resources field, Manus can process large volumes of resumes in a short time, screening and evaluating them based on preset standards, generating candidate rankings and analysis reports. This process greatly improves recruitment efficiency and reduces HR workload. However, it also means some basic HR positions may be replaced by Manus. Similarly, in the financial analysis field, Manus can quickly analyze market data and predict trends, performing tasks typically done by junior financial analysts. According to related research, a significant proportion of basic white-collar jobs may be impacted by AI agents in the coming years.
To address this issue, establishing career transition training mechanisms is crucial. Governments and enterprises can collaborate to provide targeted training for those in potentially replaceable positions. Training content can include emerging technologies like data analysis and AI algorithm understanding, helping them acquire new skills for transitioning to other roles. Additionally, training in soft skills such as innovation, communication, and leadership, which are difficult for AI to replace, can help individuals add more value in new roles.
Moreover, Manus's data access permissions have sparked privacy protection debates. During task execution, Manus needs to access large amounts of data, including sensitive information like personal financial and property data. If this data is not used and protected properly, it could pose serious threats to user privacy. Some users worry whether Manus can ensure data security during processing, preventing leaks and misuse. Therefore, establishing robust data privacy protection mechanisms and cross-border data governance agreements is urgent. Enterprises need to increase technical investments, adopting advanced data encryption technologies to ensure data security during transmission and storage. They also need to set strict data usage norms, clarify data usage scopes and permissions, and strengthen data usage oversight to protect user privacy rights.
(2) Risks of Technological Dependency
While enjoying the efficiency and convenience brought by Manus, we must also be wary of the potential risks of over-reliance on technology. When people rely too heavily on Manus to complete various tasks, their decision-making and thinking abilities may gradually deteriorate.
From a psychological perspective, human cognitive abilities develop and improve through continuous practice and thinking. When we delegate a large number of decision-making tasks to Manus, our opportunities to participate in decision-making decrease, and over time, our decision-making abilities may decline. For example, in investment decisions, investors traditionally needed to collect information, analyze market trends, and assess risks before making decisions. Now, if investors overly rely on Manus's investment advice, they may no longer deeply consider the logic and risks of investments, blindly following Manus's recommendations. If Manus makes errors or encounters complex situations it cannot handle, investors may find themselves in trouble.
Manus's "memory function" can optimize user experience by providing personalized services based on historical operations and preferences, but it may also solidify users' thinking paths. It recommends solutions based on users' historical behavior patterns, potentially limiting exposure to new ideas and methods, stifling innovation diversity. For example, in copywriting, Manus may generate similar copy based on users' past writing styles, and users may accept it for convenience, missing opportunities to try new creative expressions.
To balance efficiency improvement and cognitive autonomy, we need to maintain independent thinking while using Manus. When accepting Manus's advice and assistance, we should critically analyze its results, not blindly follow them. At the same time, we should actively learn and explore new knowledge and skills, continuously improving our cognitive levels to avoid ability degradation due to over-reliance on technology. For example, when using Manus for market research, we can refer to its reports but also conduct additional investigations and analyses to form our own insights, maintaining competitiveness while enjoying technological convenience.
(3) Challenges in Commercial Implementation
Despite Manus's strong technical capabilities and potential, its path to commercial implementation is not smooth, facing many challenges. Currently, Manus's demonstrations mostly remain in the "showroom-style demo" stage of preset scenario tasks. While Manus can perfectly complete tasks in these demos, showcasing its powerful functions, real-world applications are often more complex and variable, and its actual generalization ability still needs verification.
In the real world, task requirements and scenarios are diverse, with various unexpected situations and uncertainties. For example, in travel planning, flight delays or hotel booking issues may arise. Whether Manus can effectively handle these situations and adjust travel plans is a key test of its generalization ability. Currently, Manus still has limitations in handling such complex and variable real-world situations, requiring further optimization and improvement.
Additionally, giants like OpenAI, with their first-mover advantage and strong technical capabilities, have built vast ecosystems, such as the ChatGPT plugin system. These ecosystems have accumulated large user and developer bases, creating strong network effects. As a latecomer, Manus faces market space limitations in such a competitive environment. To break through, Manus needs to find differentiated development paths, such as focusing on enterprise-level customized services. By deeply understanding enterprises' specific needs and providing tailored solutions for different business scenarios, Manus can avoid direct competition with giants in the general market and win enterprise clients with personalized services, gradually expanding its market share.
Summary and Outlook
The emergence of Manus has undoubtedly injected strong momentum into China's technological development, demonstrating immense potential and value in technological innovation, industrial ecosystem
