UP NEXT! WEBRTC LIVE EPISODE 104

Why Vision Language Models Deserve a Closer Look

Large Language Models (LLMs) have dominated conversations about AI integration in WebRTC, particularly when it comes to voice-based features like transcription, summarization, and intent detection. But there’s an emerging layer that many outside of research circles are missing: Vision Language Models (VLMs). Unlike LLMs, which work with text and speech, VLMs are capable of understanding and generating language based on visual inputs—opening up new possibilities for analyzing what’s happening on camera during a WebRTC session.

In this episode of WebRTC Live, we speak with an AI researcher who’s been exploring exactly this topic. Yahia Salman is a Computer Science and Physics student at George Mason University, who recently won an award at a Stanford hackathon for building ZoneOut, an application that integrates Zoom Real Time Media Streams (RTMS) with both LLMs and VLMs, plus Retrieval Augmented Generation (RAG), to extract meaningful insights from both video and audio in virtual classrooms. He recently presented this work at the Zoom Developer Summit 2025.

Join us as Yahia shares the architecture behind ZoneOut, what it’s like to work with VLMs, and why he thinks they deserve more attention in the development of real-time applications

Wednesday, July 16, 2025 at 12:30 PM Eastern Daylight Time

Register for WebRTC Live Episode 104