The Team
The Learning From Videos (LFV) team in the Robotics division focuses on the development of foundation models capable of leveraging large-scale multi-modal (RGB, depth, flow, semantics, bounding boxes, tactile, audio, etc) data from multiple domains (driving, robotics, indoors, outdoors, etc) to improve downstream task performance.
Our approach emphasizes training scalability: by learning from multiple modalities, models can develop useful data-driven priors about 3D geometry, physics, and dynamics for world understanding.
Our research interests include, but are not limited to:
The AI Resident
This year-long AI Residency is a research-focused position designed for early-career researchers and engineers who are excited to work on ambitious problems in embodied AI. The resident will be deeply integrated into the LFV team, contributing to both ongoing and new research efforts in areas including:
As an AI Resident, you will collaborate closely with researchers and engineers at TRI on high-risk, pushing forward our understanding of spatio-temporal reasoning and zero-shot generalization. This is a research-focused position, targeting the development of methods and techniques that can solve real-world problems.
We welcome you to join a positive, friendly, and enthusiastic team of researchers, where you will contribute to helping people gain and maintain independence, access, and mobility. We work closely with other Toyota affiliates, and actively collaborate towards research publications and the productization of our developed technologies.