Computer Use Explained: How Large Models Can Take Over Your Screen and Mouse
The article introduces Computer Use, a technique that lets large language models directly observe, decide, and act on graphical user interfaces—enabling them to click, type, scroll, and switch windows without relying on APIs, thereby turning AI from mere conversation into executable software actions.
Computer Use can be understood as a capability that allows a model to directly operate a graphical user interface: instead of only producing text, the model observes the current screen, decides where to click, what to type, whether to scroll, or which window to switch to, thereby executing software workflows.
Traditional automation often depends on APIs, scripts, or dedicated integration systems, but many real‑world applications lack standard interfaces, have complex page structures, or incur high integration costs. Computer Use shifts the responsibility for interface manipulation to the model, letting it first learn to "use software" before tackling specific tasks.
The core workflow of Computer Use consists of three steps: observe the interface, judge the state, and execute an action. The model reads the current page or application UI, determines the next step based on the target task, and performs concrete operations such as clicking a button, entering text, opening a link, scrolling, or chaining multiple steps to complete a full process. Typical tasks include searching the web, navigating to a specific page, extracting information, filling out forms, or performing multi‑step operations in backend systems.
Once a model can directly manipulate software, new concerns arise: which pages are permissible, which actions require human confirmation, how permissions are controlled, how failures are rolled back, and whether the entire process can be recorded and audited. These factors directly impact the security and stability of the system.
In summary, Computer Use is not a method for making models "smarter"; it is a way to enable models to directly operate existing software systems, addressing the core challenge of executing tasks in environments without unified interfaces or with highly fragmented workflows.
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Network Intelligence Research Center (NIRC)
NIRC is based on the National Key Laboratory of Network and Switching Technology at Beijing University of Posts and Telecommunications. It has built a technology matrix across four AI domains—intelligent cloud networking, natural language processing, computer vision, and machine learning systems—dedicated to solving real‑world problems, creating top‑tier systems, publishing high‑impact papers, and contributing significantly to the rapid advancement of China's network technology.
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