Research Prefrontal cortex as a meta-reinforcement learning system Published 14 May 2018 Authors Jane Wang, Zeb Kurth-Nelson, Matt Botvinick Recently, AI systems have mastered a range of video-games such as Atari classics Breakout and Pong. But as impressive as this performance is, AI still relies on the equivalent of thousands of hours of gameplay to reach and surpass the performance of human vid

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

Research FermiNet: Quantum physics and chemistry from first principles Using deep learning to solve fundamental problems in computational quantum chemistry and explore how matter interacts with light Company A new generation of African talent brings cutting-edge AI to scientific challenges Food security, healthcare and exploring the cosmos are among the ways students of a new pan-African Master’s

Research Measuring abstract reasoning in neural networks Published 11 July 2018 Authors Adam Santoro, David Barrett, Ari Morcos, Timothy Lillicrap, Felix Hill Neural network-based models continue to achieve impressive results on longstanding machine learning problems, but establishing their capacity to reason about abstract concepts has proven difficult. Building on previous efforts to solve this

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 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

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

Research Deep Reinforcement Learning Published 17 June 2016 Authors David Silver Humans excel at solving a wide variety of challenging problems, from low-level motor control through to high-level cognitive tasks. Our goal at DeepMind is to create artificial agents that can achieve a similar level of performance and generality. Like a human, our agents learn for themselves to achieve successful str

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 FermiNet: Quantum physics and chemistry from first principles Using deep learning to solve fundamental problems in computational quantum chemistry and explore how matter interacts with light

Research Reinforcement learning with unsupervised auxiliary tasks Published 17 November 2016 Authors Max Jaderberg, Vlad Mnih, Wojciech Marian Czarnecki Our primary mission at DeepMind is to push the boundaries of AI, developing programs that can learn to solve any complex problem without needing to be taught how. Our reinforcement learning agents have achieved breakthroughs in Atari 2600 games an

Research Open-sourcing DeepMind Lab Published 3 December 2016 Authors Charlie Beattie, Joel Leibo, Stig Petersen, Shane Legg DeepMind's scientific mission is to push the boundaries of AI, developing systems that can learn to solve any complex problem without needing to be taught how. To achieve this, we work from the premise that AI needs to be general. Agents should operate across a wide range of

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

Research Differentiable neural computers Published 12 October 2016 Authors Gregory Wayne, Alexander Graves In a recent study in Nature, we introduce a form of memory-augmented neural network called a differentiable neural computer, and show that it can learn to use its memory to answer questions about complex, structured data, including artificially generated stories, family trees, and even a map

Research WaveNet: A generative model for raw audio Published 8 September 2016 Authors Aäron van den Oord, Sander Dieleman This post presents WaveNet, a deep generative model of raw audio waveforms. We show that WaveNets are able to generate speech which mimics any human voice and which sounds more natural than the best existing Text-to-Speech systems, reducing the gap with human performance by ove