Memories.ai models label every clip: Memories-H0 for hand pose, EgoAction for action segments. | Credit: Memories.ai
Memories.ai is building a data pipeline for robotics companies that combines standardized video collection with AI-powered annotation to turn everyday egocentric footage into training data for robots.
The San Francisco-based company is developing software and AI to help robots understand the physical world. It builds video-understanding models and data infrastructure, and it collects and annotates first-person (egocentric) video to provide high-quality training data to robotics companies.
The longer-term aim is to be a data-infrastructure partner for robotics and physical AI, not just a data vendor.
Memories.ai claimed that its video data infrastructure platform is built for physical AI, robotics, world models, vision-language-action (VLA) models, and humanoids. It provides a curated video data lake featuring egocentric video, along with custom annotation services and dataset tools to train robot learning models.
The company obtains egocentric video through data collectors and partners, providing them with standardized capture hardware—described as a modular camera setup—and uniform process to collect footage in a consistent way.
Memories.ai then processes and annotates the data with its models and makes it available through its data infrastructure. The company has published multiple elements of its research on its GitHub repo. It has also published at the ICLR, NeurIPS, and EMNLP events.
ai, recently told The Robot Report . “We really bring robotics into the actual physical world, and I believe that’s our whole team’s vision.
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