RT-1: Robotics Transformer for Real-World Control at Scale

Favorite Posted Keerthana Gopalakrishnan and Kanishka Rao, Google Research, Robotics at Google Major recent advances in multiple subfields of machine learning (ML) research, such as computer vision and natural language processing, have been enabled by a shared common approach that leverages large, diverse datasets and expressive models that can absorb

Read More
Shared by Google AI Technology December 13, 2022

Formation of Robust Bound States of Interacting Photons

Favorite Posted by Alexis Morvan and Trond Andersen, Research Scientists, Google Quantum AI When quantum computers were first proposed, they were hoped to be a way to better understand the quantum world. With a so-called “quantum simulator,” one could engineer a quantum computer to investigate how various quantum phenomena arise,

Read More
Shared by Google AI Technology December 8, 2022

Private Ads Prediction with DP-SGD

Favorite Posted by Krishna Giri Narra, Software Engineer, Google, and Chiyuan Zhang, Research Scientist, Google Research Ad technology providers widely use machine learning (ML) models to predict and present users with the most relevant ads, and to measure the effectiveness of those ads. With increasing focus on online privacy, there’s

Read More
Shared by Google AI Technology December 7, 2022

Google at EMNLP 2022

Favorite Posted by Malaya Jules, Program Manager, Google This week, the premier conference on Empirical Methods in Natural Language Processing (EMNLP 2022) is being held in Abu Dhabi, United Arab Emirates. We are proud to be a Diamond Sponsor of EMNLP 2022, with Google researchers contributing at all levels. This

Read More
Shared by Google AI Technology December 7, 2022

How startups can help build a sustainable future

Favorite Google’s Startups for Sustainable Development program supports impact-driven startups who are building a more sustainable future. View Original Source (blog.google/technology/ai/) Here.

Will You Find These Shortcuts?

Favorite Posted by Katja Filippova, Research Scientist, and Sebastian Ebert, Software Engineer, Google Research, Brain team Modern machine learning models that learn to solve a task by going through many examples can achieve stellar performance when evaluated on a test set, but sometimes they are right for the “wrong” reasons:

Read More
Shared by Google AI Technology December 6, 2022

Talking to Robots in Real Time

Favorite Posted by Corey Lynch, Research Scientist, and Ayzaan Wahid, Research Engineer, Robotics at Google A grand vision in robot learning, going back to the SHRDLU experiments in the late 1960s, is that of helpful robots that inhabit human spaces and follow a wide variety of natural language commands. Over

Read More
Shared by Google AI Technology December 1, 2022

Making a Traversable Wormhole with a Quantum Computer

Favorite Posted by Alexander Zlokapa, Student Researcher, and Hartmut Neven, VP of Engineering, Quantum AI Team Wormholes — wrinkles in the fabric of spacetime that connect two disparate locations — may seem like the stuff of science fiction. But whether or not they exist in reality, studying these hypothetical objects

Read More
Shared by Google AI Technology November 30, 2022