The Next Input updates
Browse every published The Next Input update in a calm card overview with images, dates, and direct access to each article.
The Next Input update
PixelCNN++: Improving the PixelCNN with discretized logistic mixture likelihood and other modifications
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The Next Input update
Faulty reward functions in the wild
Reinforcement learning algorithms can break in surprising, counterintuitive ways. In this post we’ll explore one failure mode, which is where you misspecify your reward function.
The Next Input update
Universe
We’re releasing Universe, a software platform for measuring and training an AI’s general intelligence across the world’s supply of games, websites and other applications.
The Next Input update
OpenAI and Microsoft
We’re working with Microsoft to start running most of our large-scale experiments on Azure.
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#Exploration: A study of count-based exploration for deep reinforcement learning
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On the quantitative analysis of decoder-based generative models
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A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models
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RL²: Fast reinforcement learning via slow reinforcement learning
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Variational lossy autoencoder
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Extensions and limitations of the neural GPU
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Semi-supervised knowledge transfer for deep learning from private training data
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The Next Input update
Report from the self-organizing conference
Last week we hosted over a hundred and fifty AI practitioners in our offices for our first self-organizing conference on machine learning.
Showing 1105 to 1116 of 1,197 updates.