Posted by Bahare Fatemi, Research Scientist, Google Research, and Bryan Perozzi, Research Scientist, Google Research Imagine all the things around you — your friends, tools in your kitchen, or even the parts of your bike. They are all connected in different ways. In computer science, the term graph is used to describe connections between objects….
I’ve had a ham radio license since the late 1960s and observed the transition from vacuum tubes (remember them?) to transistors firsthand. Because we’re allowed to operate high power transmitters (1500 watt output), tubes hang on in our world a lot longer than elsewhere. There’s a good reason: tubes are ideal high power devices for…
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. I remember the first time I tried on a VR headset. It was the first Oculus Rift, and I nearly fainted after experiencing an intense but visually clumsy VR roller-coaster. But…
Every year, the Berkeley Artificial Intelligence Research (BAIR) Lab graduates some of the most talented and innovative minds in artificial intelligence and machine learning. Our Ph.D. graduates have each expanded the frontiers of AI research and are now ready to embark on new adventures in academia, industry, and beyond. These fantastic individuals bring with them…
Since their inception, it’s been clear that large language models like ChatGPT absorb racist views from the millions of pages of the internet they are trained on. Developers have responded by trying to make them less toxic. But new research suggests that those efforts, especially as models get larger, are only curbing racist views that…
Posted by Zilong Wang, Student Researcher, and Chen-Yu Lee, Research Scientist, Cloud AI Team People use tables every day to organize and interpret complex information in a structured, easily accessible format. Due to the ubiquity of such tables, reasoning over tabular data has long been a central topic in natural language processing (NLP). Researchers in…
In the summer of 2021, OpenAI quietly shuttered its robotics team, announcing that progress was being stifled by a lack of data necessary to train robots in how to move and reason using artificial intelligence. Now three of OpenAI’s early research scientists say the startup they spun off in 2017, called Covariant, has solved that…
Posted by Dave Steiner, Clinical Research Scientist, Google Health, and Rory Pilgrim, Product Manager Google Research There’s a worldwide shortage of access to medical imaging expert interpretation across specialties including radiology, dermatology and pathology. Machine learning (ML) technology can help ease this burden by powering tools that enable doctors to interpret these images more accurately…
Peripheral vision enables humans to see shapes that aren’t directly in our line of sight, albeit with less detail. This ability expands our field of vision and can be helpful in many situations, such as detecting a vehicle approaching our car from the side. Unlike humans, AI does not have peripheral vision. Equipping computer vision…
Posted by Amirkeivan Mohtashami, Research Intern, and Florian Hartmann, Software Engineer, Google Research Large language models (LLMs) have significantly improved the state of the art for solving tasks specified using natural language, often reaching performance close to that of people. As these models increasingly enable assistive agents, it could be beneficial for them to learn…