Microsoft showed how to use chatGPT to control robots with your voice. APIs and Prompts can be designed to enable chatGPT to run the robot. By combining the spoken task with API information, it is possible to let chatGPT generate the code and API calls to execute the task with a given robot. While this is a powerful use case of LLMs it is not a secure way to handle a robot since the safety of the generated code can not be guaranteed.
Tag: Robots
Google just published the paper “Scaling Robot Learning with Semantically Imagined Experience” showing how to use generated images like Imagen to generate Training data for their robot system. This allows the robot to have a more diverse data set and therefore be more robust and able to solve unseen tasks. We saw similar approaches using simulations for cars, but this is the first time that generative models were used.
Also from google, we got a new paper where they present their advancements in quantum error correction. By scaling to larger numbers of Qubits and combining them to logical Qubits they can reduce the quantum error rate significantly. This opens up a clear path to better quantum computers by just scaling them up.