-
Google presents PaLM-E. An Embodied Multimodal Language Model
PaLM-E has 562B parameters which make it one of the largest models today. It combines sensory data from a robot with text and image data. It is based on PaLM and was fine-tuned on input & scene representations for different sensor modalities. These kinds of more general models are the way to more powerful and… — read more
-
Google found a way to make Qubits more stable which scales well
A new paper was published by Google 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. — read more
-
New Paper by Google uses Generative AI to train 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… — read more