Humans are pretty good at looking at a single two-dimensional image and understanding the full three-dimensional scene that it captures. Artificial intelligence agents are not. Yet a machine that needs to interact with objects in the world — like a robot designed to harvest crops or assist with surgery — must be able to infer…
Posted by Jaqui Herman and Cat Armato, Program Managers This week marks the beginning of the 35th annual Conference on Neural Information Processing Systems (NeurIPS 2021), the biggest machine learning conference of the year. NeurIPS 2021 will be held virtually and includes invited talks, demonstrations and presentations of some of the latest in machine learning…
While standing in a kitchen, you push some metal bowls across the counter into the sink with a clang, and drape a towel over the back of a chair. In another room, it sounds like some precariously stacked wooden blocks fell over, and there’s an epic toy car crash. These interactions with our environment are…
Kevin Cowley remembers many things about April 15, 1989. He had taken the bus to the Hillsborough soccer stadium in Sheffield, England, to watch the semifinal championship game between Nottingham Forest and Liverpool. He was 17. It was a beautiful, sunny afternoon. The fans filled the stands. He remembers being pressed between people so tightly…
In their quest to discover effective new medicines, scientists search for drug-like molecules that can attach to disease-causing proteins and change their functionality. It is crucial that they know the 3D shape of a molecule to understand how it will attach to specific surfaces of the protein. But a single molecule can fold in thousands…
Posted by Jason Wei, AI Resident and Dan Garrette, Research Scientist, Google Research In recent years, pre-trained language models, such as BERT and GPT-3, have seen widespread use in natural language processing (NLP). By training on large volumes of text, language models acquire broad knowledge about the world, achieving strong performance on various NLP benchmarks….
Posted by Sabela Ramos, Software Engineer and Léonard Hussenot, Student Researcher, Google Research, Brain Team Most reinforcement learning (RL) and sequential decision making algorithms require an agent to generate training data through large amounts of interactions with their environment to achieve optimal performance. This is highly inefficient, especially when generating those interactions is difficult, such…
Posted by Aashi Jain, AI Resident and Yinfei Yang, Staff Research Scientist, Google Research For many concepts, there is no direct one-to-one translation from one language to another, and even when there is, such translations often carry different associations and connotations that are easily lost for a non-native speaker. In such cases, however, the meaning…
Posted by Florian Hartmann, Software Engineer, Google Research Smart Text Selection, launched in 2017 as part of Android O, is one of Android’s most frequently used features, helping users select, copy, and use text easily and quickly by predicting the desired word or set of words around a user’s tap, and automatically expanding the selection…
Posted by Pete Florence, Research Scientist and Corey Lynch, Research Engineer, Robotics at Google Despite considerable progress in robot learning over the past several years, some policies for robotic agents can still struggle to decisively choose actions when trying to imitate precise or complex behaviors. Consider a task in which a robot tries to slide…