Video Discovery for Agentic World-Model Training

Official Schedule Context

Official Description

Physical AI had its “Attention Is All You Need” moment with the rise of Vision-Language-Action

models. The next bottleneck is data: not just more video, but the ability to find the exact real-

world moments that teach models how the world works: gravity, motion, causality, human behavior, and

object interactions. This session explores a new approach: discovering specific scenes from the

vastness of the web. We’ll show how teams can search for moments like objects falling, people

interacting with environments, or actions unfolding over time, then collect and structure only the

relevant clips for training and evaluation. Attendees will learn how scene-level discovery changes

multimodal data pipelines, reducing wasted collection, processing, storage, and review, while making

it easier to build targeted datasets for VLA systems, robotics, physical AI, and agentic world

models.

Related YouTube Video

From MCP to Scale: Pipelines That Build Themselves — Rafael Levi, Bright Data (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions).

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Related video transcript availability: English auto-captions. Treat this as supporting context, not a recording of this exact scheduled session unless later confirmed. Not fetched yet.

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