Latest from MIT Tech Review – We know remarkably little about how AI language models work

AI language models are not humans, and yet we evaluate them as if they were, using tests like the bar exam or the United States Medical Licensing Examination. The models tend to do really well in these exams, probably because examples of such exams are abundant in the models’ training data. Yet, as my colleague…

Latest from MIT : Fast-tracking fusion energy’s arrival with AI and accessibility

As the impacts of climate change continue to grow, so does interest in fusion’s potential as a clean energy source. While fusion reactions have been studied in laboratories since the 1930s, there are still many critical questions scientists must answer to make fusion power a reality, and time is of the essence. As part of…

Latest from Google AI – WeatherBench 2: A benchmark for the next generation of data-driven weather models

Posted by Stephan Rasp, Research Scientist, and Carla Bromberg, Program Lead, Google Research In 1950, weather forecasting started its digital revolution when researchers used the first programmable, general-purpose computer ENIAC to solve mathematical equations describing how weather evolves. In the more than 70 years since, continuous advancements in computing power and improvements to the model…

Latest from Google AI – Modeling and improving text stability in live captions

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…

Latest from MIT : Autonomous innovations in an uncertain world

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…

Latest from MIT Tech Review – Chinese ChatGPT-alternatives receive government approval for widespread public access

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…

Latest from Google AI – SayTap: Language to quadrupedal locomotion

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…

Latest from MIT Tech Review – Google DeepMind has launched a watermarking tool for AI-generated images

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…

Latest from Google AI – RO-ViT: Region-aware pre-training for open-vocabulary object detection with vision transformers

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…

Latest from Google AI – Responsible AI at Google Research: Perception Fairness

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…