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As large language and vision-language models continue to evolve rapidly in 2025, a new frontier is emerging at the application layer of generative AI: intelligent agents. These AI agents are more than just fancy wrappers around models—they represent a shift toward building autonomous, goal-directed systems that can perceive their environment, take actions, and deliver robust, grounded outputs in real-world scenarios.
🔍 What are AI Agents?
In simple terms, AI agents are like digital workers. They combine large models (LLMs, VLMs, MLLMs, etc.) with tools (functions, databases, APIs) to perceive, plan, and act. Unlike standalone models that only generate text or images, agents operate in iterative loops, continually sensing and adjusting to their environment to achieve specific tasks.
This talk broke down key distinctions:
🛠 Live Demo: The UI Agent
One of the highlights was a live demo of a UI Agent—a system that can control a user’s browser entirely on its own. It could navigate websites, execute searches, and return results without any manual clicks. This is a glimpse into what future autonomous systems might look like for everyday tasks.
🌍 Real-World Use Cases
The presentation also explored how AI agents can drive value across industries such as:
This is the first public demonstration of BKOAI’s internal protocol experimentation, with an eye toward open collaboration and feedback from the broader AI builder community.
For those interested, here’s the original presentation PDF for a closer look:
🔗 Download the PDF
If you’re curious about more talks like this, or want to join a community passionate about data, AI, and real-world applications, check out and join our Meetup group:
👉 Data & AI Meetup
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