Artificial Intelligence

Posted by Vikas Bahirwani, Research Scientist, and Susan Xu, Software Engineer, Google Augmented Reality Automatic speech recognition (ASR) technology has made conversations more accessible with live captions in remote conferencing software, mobile applications, and head-worn displays. However, to maintain real-time responsiveness, live caption systems often display interim predictions that are updated as new utterances are…

MIT Professor Jonathan How’s research interests span the gamut of autonomous vehicles — from airplanes and spacecraft to unpiloted aerial vehicles (UAVs, or drones) and cars. He is particularly focused on the design and implementation of distributed robust planning algorithms to coordinate multiple autonomous vehicles capable of navigating in dynamic environments. For the past year…

On Wednesday, Baidu, one of China’s leading artificial intelligence companies, announced it would open up access to its ChatGPT-like large language model, Ernie Bot, to the general public. It’s been a long time coming. Launched in mid-March, Ernie Bot was the first Chinese ChatGPT rival. Since then, many Chinese tech companies have followed suit and…

Posted by Yujin Tang and Wenhao Yu, Research Scientists, Google Simple and effective interaction between human and quadrupedal robots paves the way towards creating intelligent and capable helper robots, forging a future where technology enhances our lives in ways beyond our imagination. Key to such human-robot interaction systems is enabling quadrupedal robots to respond to…

Google DeepMind has launched a new watermarking tool that labels whether images have been generated with AI. The tool, called SynthID, will initially be available only to users of Google’s AI image generator Imagen, which is hosted on Google Cloud’s machine learning platform Vertex. Users will be able to generate images using Imagen and then…

Posted by Dahun Kim and Weicheng Kuo, Research Scientists, Google The ability to detect objects in the visual world is crucial for computer vision and machine intelligence, enabling applications like adaptive autonomous agents and versatile shopping systems. However, modern object detectors are limited by the manual annotations of their training data, resulting in a vocabulary…

Posted by Susanna Ricco and Utsav Prabhu, co-leads, Perception Fairness Team, Google Research Google’s Responsible AI research is built on a foundation of collaboration — between teams with diverse backgrounds and expertise, between researchers and product developers, and ultimately with the community at large. The Perception Fairness team drives progress by combining deep subject-matter expertise…

Posted by Sergio Boixo and Vadim Smelyanskiy, Principal Scientists, Google Quantum AI Team A full-scale error-corrected quantum computer will be able to solve some problems that are impossible for classical computers, but building such a device is a huge endeavor. We are proud of the milestones that we have achieved toward a fully error-corrected quantum…

Posted by Hattie Zhou, Graduate Student at MILA, Hanie Sedghi, Research Scientist, Google Large language models (LLMs), such as GPT-3 and PaLM, have shown impressive progress in recent years, which have been driven by scaling up models and training data sizes. Nonetheless, a long standing debate has been whether LLMs can reason symbolically (i.e., manipulating…

Should artificial intelligence be allowed to make care decisions for patients? Though the future of AI may conjure up doomsday visions of robots and computers intent on rendering human existence superfluous, the MIT Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic) addressed questions surrounding the use of AI in health through their…