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Systems that perceive webpages and perform actions like scrolling, typing, and clicking on predicted coordinates.
Distinct from Scroll Access Controllers: Distinct from Scroll Access Controllers: focuses on visual perception-based action prediction, not just scroll toggling.
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FARA is a visual computer-use agent model that controls a browser by predicting screen coordinates for clicking, typing, and scrolling, without relying on DOM or accessibility trees. It is designed to automate multi-step web tasks such as searching, form filling, booking, and shopping by reasoning over visual state and decomposing tasks into sequential actions. The model uses a compact 7-billion-parameter decoder-only transformer that can run on consumer GPUs for low-latency on-device inference, or be deployed as a managed endpoint on Azure Foundry for cloud-based inference without local infr
Perceives webpages and performs scrolling, typing, and clicking on predicted coordinates without accessibility trees.