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Impact
Traffic prediction with advanced Graph Neural Networks
By partnering with Google, DeepMind is able to bring the benefits of AI to billions of people all over the world. From reuniting a speech-impaired user with his original voice, to helping users...
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Research
Computational predictions of protein structures associated with COVID-19
The scientific community has galvanised in response to the recent COVID-19 outbreak, building on decades of basic research characterising this virus family. Labs at the forefront of the outbreak...
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Research
RL Unplugged: Benchmarks for Offline Reinforcement Learning
We propose a benchmark called RL Unplugged to evaluate and compare offline RL methods. RL Unplugged includes data from a diverse range of domains including games (e.g., Atari benchmark) and...
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Company
Applying for technical roles
It’s no secret that the gender gap still exists within STEM. Despite a slight increase in recent years, studies show that women only make up about a quarter of the overall STEM workforce in the...
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Research
dm_control: Software and Tasks for Continuous Control
The dm_control software package is a collection of Python libraries and task suites for reinforcement learning agents in an articulated-body simulation. A MuJoCo wrapper provides convenient...
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Research
Acme: A new framework for distributed reinforcement learning
Acme is a framework for building readable, efficient, research-oriented RL algorithms. At its core Acme is designed to enable simple descriptions of RL agents that can be run at various scales of...
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Research
Using AI to predict retinal disease progression
Vision loss among the elderly is a major healthcare issue: about one in three people have some vision-reducing disease by the age of 65. Age-related macular degeneration (AMD) is the most common...
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Research
Simple Sensor Intentions for Exploration
In this paper we focus on a setting in which goal tasks are defined via simple sparse rewards, and exploration is facilitated via agent-internal auxiliary tasks. We introduce the idea of simple...
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Research
Learning to Segment Actions from Observation and Narration
We apply a generative segmental model of task structure, guided by narration, to action segmentation in video. We focus on unsupervised and weakly-supervised settings where no action labels are...
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Research
Specification gaming: the flip side of AI ingenuity
Specification gaming is a behaviour that satisfies the literal specification of an objective without achieving the intended outcome. We have all had experiences with specification gaming, even if...
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Research
Towards understanding glasses with graph neural networks
Under a microscope, a pane of window glass doesn’t look like a collection of orderly molecules, as a crystal would, but rather a jumble with no discernable structure. Glass is made by starting...
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Research
Agent57: Outperforming the human Atari benchmark
The Atari57 suite of games is a long-standing benchmark to gauge agent performance across a wide range of tasks. We’ve developed Agent57, the first deep reinforcement learning agent to obtain a...
