{"id":14262,"date":"2025-03-02T17:50:48","date_gmt":"2025-03-02T17:50:48","guid":{"rendered":"https:\/\/topat10.com\/?p=14262"},"modified":"2025-03-02T17:50:48","modified_gmt":"2025-03-02T17:50:48","slug":"honors-new-ai-agent-can-read-and-understand-your-screen","status":"publish","type":"post","link":"https:\/\/topat10.com\/?p=14262","title":{"rendered":"Honor's New AI Agent Can Read and Understand Your Screen"},"content":{"rendered":"


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It chose a restaurant, but then couldn’t complete the process as the spot it chose required a credit card to confirm a reservation, at which point the user had to take over. You can be flexible in your query\u2014in another example, asking it to book a \u201chighly rated\u201d restaurant meant it would look at reviews with high scores, though the agent doesn’t do any more research than that. It’s not cross-referencing OpenTable reviews with data from other parts of the web, especially since all of this data is processed on device and isn’t sent to the cloud.<\/p>\n

This kind of agentic artificial intelligence is the current buzzword in the tech sphere<\/a>. My colleague Will Knight recently tested an AI assistant<\/a> that could browse the web and perform tasks online. Google late last year unveiled its Gemini 2 AI model<\/a> trained to take actions on your behalf. It also renews the idea of a generative user interface for smartphones\u2014at MWC 2024, we saw a few companies working on ways to interact with apps without using apps at all<\/a>, instead leaning on AI assistants to generate a user interface as you issued a command.<\/p>\n

Honor’s approach feels somewhat like what Rabbit\u2014of the infamous Rabbit R1<\/a>\u2014is doing with Teach Mode<\/a>, where you train its assistant manually to complete a task. There’s no need to access an app’s Application Programming Interface (API), which is the traditional way apps or services communicate with each other. The agent memorizes the process, allowing you to then issue the command and have it execute the task.<\/p>\n

But Honor says its self-reliant AI execution model isn’t trained to follow strict steps\u2014it’s capable of multimodal screen context recognition to perform tasks autonomously. Instead of having to train the assistant to learn every single part of the OpenTable app, it is capable of understanding the semantic elements of the user interface and will follow-through with a multi-step process to execute your request. Honor highlighted that this process was more cost effective: \u201cUnlike competitors such as Apple, Samsung, and Google, which rely on external APIs\u2014resulting in higher operational costs\u2014Honor’s AI Agent independently manages a wide range of tasks.”<\/p>\n

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