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Research Agent57: Outperforming the human Atari benchmark Published 31 March 2020 Authors Adrià Puigdomènech, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi, Daniel Guo, Charles Blundell 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
Research AlphaStar: Grandmaster level in StarCraft II using multi-agent reinforcement learning Published 30 October 2019 Authors The AlphaStar team TL;DR: AlphaStar is the first AI to reach the top league of a widely popular esport without any game restrictions. This January, a preliminary version of AlphaStar challenged two of the world's top players in StarCraft II, one of the most enduring and
Research Unsupervised learning: The curious pupil Published 25 June 2019 Authors Alexander Graves, Kelly Clancy One in a series of posts explaining the theories underpinning our research. Over the last decade, machine learning has made unprecedented progress in areas as diverse as image recognition, self-driving cars and playing complex games like Go. These successes have been largely realised by
Open source TF-Replicator: Distributed Machine Learning for Researchers Published 7 March 2019 Authors Dominik Grewe, Peter Buchlovsky, Chris Jones, David Budden, Tom Hennigan, Aedan Pope At DeepMind, the Research Platform Team builds infrastructure to empower and accelerate our AI research. Today, we are excited to share how we developed TF-Replicator, a software library that helps researchers de
Research Machine learning can boost the value of wind energy Published 26 February 2019 Authors Carl Elkin, Sims Witherspoon Carbon-free technologies like renewable energy help combat climate change, but many of them have not reached their full potential. Consider wind power: over the past decade, wind farms have become an important source of carbon-free electricity as the cost of turbines has plu
Research AlphaStar: Mastering the real-time strategy game StarCraft II Published 24 January 2019 Authors The AlphaStar team Games have been used for decades as an important way to test and evaluate the performance of artificial intelligence systems. As capabilities have increased, the research community has sought games with increasing complexity that capture different elements of intelligence req
Latest news Discover our latest AI breakthroughs and updates from the lab Responsibility & Safety The ethics of advanced AI assistants The ethics of advanced AI assistants Exploring the promise and risks of a future with more capable AI Research TacticAI: an AI assistant for football tactics As part of our multi-year collaboration with Liverpool FC, we develop a full AI system that can advise coac
Research AlphaZero: Shedding new light on chess, shogi, and Go Published 6 December 2018 Authors David Silver, Thomas Hubert, Julian Schrittwieser, Demis Hassabis In late 2017 we introduced AlphaZero, a single system that taught itself from scratch how to master the games of chess, shogi(Japanese chess), and Go, beating a world-champion program in each case. We were excited by the preliminary resu
Research AlphaFold: Using AI for scientific discovery Published 15 January 2020 Authors Andrew Senior, John Jumper, Demis Hassabis, Pushmeet Kohli UPDATE: In July 2022, we released AlphaFold protein structure predictions for nearly all catalogued proteins known to science. Read the latest blog here. In our study published in Nature, we demonstrate how artificial intelligence research can drive and
Research Capture the Flag: the emergence of complex cooperative agents Published 30 May 2019 Authors Max Jaderberg, Wojciech Marian Czarnecki, Iain Dunning, Thore Graepel, Luke Marris Mastering the strategy, tactical understanding, and team play involved in multiplayer video games represents a critical challenge for AI research. In our latest paper, now published in the journal Science, we present
Research Neural scene representation and rendering Published 14 June 2018 Authors Ali Eslami, Danilo Jimenez Rezende There is more than meets the eye when it comes to how we understand a visual scene: our brains draw on prior knowledge to reason and to make inferences that go far beyond the patterns of light that hit our retinas. For example, when entering a room for the first time, you instantly
Impact DeepMind, meet Android Published 8 May 2018 Authors James Smith, Simon Rosen, Chris Gamble We’re delighted to announce a new collaboration between DeepMind for Google and Android, the world’s most popular mobile operating system. Together, we’ve created two new features that will be available to people with devices running Android P later this year: Adaptive Battery: A smart battery managem
Research Learning to navigate in cities without a map Published 29 March 2018 Authors Piotr Mirowski, Raia Hadsell, Andrew Zisserman How did you learn to navigate the neighborhood of your childhood, to go to a friend’s house, to your school or to the grocery store? Probably without a map and simply by remembering the visual appearance of streets and turns along the way. As you gradually explored y
Research Learning to write programs that generate images Published 27 March 2018 Authors Ali Eslami, Tejas Kulkarni, Oriol Vinyals Through a human’s eyes, the world is much more than just the images reflected in our corneas. For example, when we look at a building and admire the intricacies of its design, we can appreciate the craftsmanship it requires. This ability to interpret objects through th
Research Understanding deep learning through neuron deletion Published 21 March 2018 Authors Ari Morcos, David Barrett Deep neural networks are composed of many individual neurons, which combine in complex and counterintuitive ways to solve a wide range of challenging tasks. This complexity grants neural networks their power but also earns them their reputation as confusing and opaque black boxes.
Research Scalable agent architecture for distributed training Published 5 February 2018 Authors Hubert Soyer, Drew Purves, Lasse Espeholt Deep Reinforcement Learning (DeepRL) has achieved remarkable success in a range of tasks, from continuous control problems in robotics to playing games like Go and Atari. The improvements seen in these domains have so far been limited to individual tasks where a
Research Learning explanatory rules from noisy data Published 29 January 2018 Authors Richard Evans, Edward Grefenstette Suppose you are playing football. The ball arrives at your feet, and you decide to pass it to the unmarked striker. What seems like one simple action requires two different kinds of thought. First, you recognise that there is a football at your feet. This recognition requires in
Company 2017: DeepMind's year in review Published 21 December 2017 Authors Demis Hassabis, Mustafa Suleyman, Shane Legg In July, the world number one Go player Ke Jie spoke after a streak of 20 wins. It was two months after he had played AlphaGo at the Future of Go Summit in Wuzhen, China. “After my match against AlphaGo, I fundamentally reconsidered the game, and now I can see that this reflectio
Research Population based training of neural networks Published 27 November 2017 Authors Max Jaderberg Neural networks have shown great success in everything from playing Go and Atari games to image recognition and language translation. But often overlooked is that the success of a neural network at a particular application is often determined by a series of choices made at the start of the resear
Research High-fidelity speech synthesis with WaveNet Published 22 November 2017 Authors Aäron van den Oord, Yazhe Li, Igor Babuschkin In October we announced that our state-of-the-art speech synthesis model WaveNet was being used to generate realistic-sounding voices for the Google Assistant globally in Japanese and the US English. This production model - known as parallel WaveNet - is more than 1
Research AlphaGo Zero: Starting from scratch Published 18 October 2017 Authors David Silver, Demis Hassabis Artificial intelligence research has made rapid progress in a wide variety of domains from speech recognition and image classification to genomics and drug discovery. In many cases, these are specialist systems that leverage enormous amounts of human expertise and data. However, for some pro
Company DeepMind and Blizzard open StarCraft II as an AI research environment Published 9 August 2017 Authors Oriol Vinyals, Stephen Gaffney, Timo Ewalds DeepMind's scientific mission is to push the boundaries of AI by developing systems that can learn to solve complex problems. To do this, we design agents and test their ability in a wide range of environments from the purpose-built DeepMind Lab
Research Imagine this: Creating new visual concepts by recombining familiar ones Published 12 July 2017 Authors Alexander Lerchner, Irina Higgins, Matt Botvinick Around two and a half thousand years ago a Mesopotamian trader gathered some clay, wood and reeds and changed humanity forever. Over time, their abacus would allow traders to keep track of goods and reconcile their finances, allowing econ
Research Producing flexible behaviours in simulated environments Published 10 July 2017 Authors Nicolas Heess, Josh Merel, Ziyu Wang The agility and flexibility of a monkey swinging through the trees or a football player dodging opponents and scoring a goal can be breathtaking. Mastering this kind of sophisticated motor control is a hallmark of physical intelligence, and is a crucial part of AI re
Explore our research on some of the most complex and interesting challenges in AI. Latest research news Discover our latest AI breakthroughs and updates from the lab Research TacticAI: an AI assistant for football tactics As part of our multi-year collaboration with Liverpool FC, we develop a full AI system that can advise coaches on corner kicks
Research A neural approach to relational reasoning Published 6 June 2017 Authors Adam Santoro, David Raposo, Nick Watters Consider the reader who pieces together the evidence in an Agatha Christie novel to predict the culprit of the crime, a child who runs ahead of her ball to prevent it rolling into a stream or even a shopper who compares the relative merits of buying kiwis or mangos at the marke
Research AlphaGo's next move Published 27 May 2017 Authors Demis Hassabis, David Silver With just three stones on the board, it was clear that this was going to be no ordinary game of Go. Chinese Go Grandmaster and world number one Ke Jie departed from his typical style of play and opened with a “3:3 point” strategy - a highly unusual approach aimed at quickly claiming corner territory at the star
Making historyOur artificial intelligence (AI) system, AlphaGo, learned to master the ancient Chinese game of Go — a profoundly complex board game of strategy, creativity, and ingenuity. AlphaGo defeated a human Go world champion a decade before experts thought possible, inspired players around the world to discover new approaches, and arguably, became the strongest Go player in history. It proved
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