Figure Announces "Project Go Big" for Internet-Scale Humanoid Pretraining

San Francisco, CA – Figure, a developer of humanoid robots, has announced "Project Go Big," a new initiative focused on internet-scale pretraining for humanoid robots. The project aims to enable robots to learn and perform a wide range of tasks by leveraging a massive dataset and a novel human-to-robot transfer learning approach.

Internet-Scale Pretraining

Project Go Big will utilize a substantial dataset to pretrain humanoid robots. This pretraining is intended to equip the robots with a broad understanding of general tasks and environments, allowing them to generalize knowledge and adapt to new situations more effectively. The objective is to create a foundation of learned behaviors that can be readily applied across various applications.

Direct Human-to-Robot Transfer

A key component of the project is the development of a direct human-to-robot transfer method. This approach aims to facilitate the efficient and intuitive teaching of complex tasks to humanoid robots. By enabling direct transfer from human demonstration, Figure seeks to accelerate the learning process and improve the accuracy and reliability of robot performance in real-world scenarios.

In summary, Figure's Project Go Big represents a significant undertaking in humanoid robot development. The initiative centers on leveraging internet-scale pretraining and a direct human-to-robot transfer learning methodology to enhance the capabilities and learning efficiency of humanoid robots.