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Research
AlphaZero: Shedding new light on chess, shogi, and Go
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...
Open sourcing TRFL: a library of reinforcement learning building blocks
Today we are open sourcing a new library of useful building blocks for writing reinforcement learning (RL) agents in TensorFlow. Named TRFL (pronounced ‘truffle’), it represents a collection of...
Preserving Outputs Precisely while Adaptively Rescaling Targets
Multi-task learning - allowing a single agent to learn how to solve many different tasks - is a longstanding objective for artificial intelligence research. Recently, there has been a lot of...
Objects that Sound
Visual and audio events tend to occur together: a musician plucking guitar strings and the resulting melody; a wine glass shattering and the accompanying crash; the roar of a motorcycle as it...
Measuring abstract reasoning in neural networks
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...
DeepMind papers at ICML 2018
The 2018 International Conference on Machine Learning will take place in Stockholm, Sweden from 10-15 July. For those attending and planning the week ahead, we are sharing a schedule of DeepMind...
Neural scene representation and rendering
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...
Prefrontal cortex as a meta-reinforcement learning system
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...
Navigating with grid-like representations in artificial agents
Most animals, including humans, are able to flexibly navigate the world they live in – exploring new areas, returning quickly to remembered places, and taking shortcuts. Indeed, these abilities...
DeepMind papers at ICLR 2018
Between 30 April and 03 May, hundreds of researchers and engineers will gather in Vancouver, Canada, for the Sixth International Conference on Learning Representations.
Learning to navigate in cities without a map
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...
Learning to write programs that generate images
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...