This is the best summary I could come up with:

Google’s data gathering system, AutoRT, can use a visual language model (VLM) and large language model (LLM) working hand in hand to understand its environment, adapt to unfamiliar settings, and decide on appropriate tasks.

For additional safety, DeepMind programmed the robots to stop automatically if the force on its joints goes past a certain threshold and included a physical kill switch human operators can use to deactivate them.

Over a period of seven months, Google deployed a fleet of 53 AutoRT robots into four different office buildings and conducted over 77,000 trials.

DeepMind’s other new tech includes SARA-RT, a neural network architecture designed to make the existing Robotic Transformer RT-2 more accurate and faster.

It also announced RT-Trajectory, which adds 2D outlines to help robots better perform specific physical tasks, such as wiping down a table.

We still seem to be a very long way from robots that serve drinks and fluff pillows autonomously, but when they’re available, they may have learned from a system like AutoRT.

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