How Tesla plans to win the robot race with foundation models


On Twitter, Tesla’s AI team is sharing its plans for foundation models for autonomous robots like the Tesla Bot.

Tesla’s goal with the Tesla Bot is to create a universal, autonomous, bipedal humanoid robot capable of performing dangerous, repetitive, or boring tasks. Like other robotics projects, Tesla hopes to achieve this goal by using foundation models for autonomous robots.

Such models are trained on large amounts of data, and their general capabilities form the basis for specialized applications. In computational linguistics, GPT-4 is an example of such a model.

Tesla relies on big (video) data

For the robotic models, Tesla plans to rely on multimodal neural networks already used in Tesla’s autonomous driving vehicles. These currently process multiple modalities such as camera video, maps, navigation, IMU (Inertial Measurement Unit), or GPS to predict whether there are vehicles, cyclists, people, or other objects in the way.


Video: Tesla

According to Tesla’s AI team, these networks could also be used for collision avoidance in any robot. All the data from the entire fleet is also used to reconstruct sections of the road on which the AI ​​can be further trained. In addition, the team is developing generative models that can, for example, produce short new video clips in which the vehicle behaves differently based on diverse real-world data.

Video: Tesla

This increases the amount of data available – a basic requirement for foundation models. A short clip also shows how a Tesla bot or similar system collects data in offices.

Video: Tesla


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