Models page 655

OpenAI News July 20, 2017 07:00

Proximal Policy Optimization

We’re releasing a new class of reinforcement learning algorithms, Proximal Policy Optimization (PPO), which perform comparably or better than state-of-the-art approaches while being much simpler to implement and tune. PPO has become the default...

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OpenAI News June 13, 2017 07:00

Learning from human preferences

One step towards building safe AI systems is to remove the need for humans to write goal functions, since using a simple proxy for a complex goal, or getting the complex goal a bit wrong, can lead to undesirable and even dangerous behavior. In collaboration...

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OpenAI News May 24, 2017 07:00

OpenAI Baselines: DQN

We’re open-sourcing OpenAI Baselines, our internal effort to reproduce reinforcement learning algorithms with performance on par with published results. We’ll release the algorithms over upcoming months; today’s release includes DQN and three of its variants.

Topics: Models

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OpenAI News May 15, 2017 07:00

Roboschool

We are releasing Roboschool: open-source software for robot simulation, integrated with OpenAI Gym.

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OpenAI News March 16, 2017 07:00

Learning to communicate

In this post we’ll outline new OpenAI research in which agents develop their own language.

Topics: Models Agents

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OpenAI News March 12, 2017 08:00

Prediction and control with temporal segment models

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OpenAI News February 24, 2017 08:00

Attacking machine learning with adversarial examples

Adversarial examples are inputs to machine learning models that an attacker has intentionally designed to cause the model to make a mistake; they’re like optical illusions for machines. In this post we’ll show how adversarial examples work across different...

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OpenAI News January 30, 2017 08:00

Team update

The OpenAI team is now 45 people. Together, we’re pushing the frontier of AI capabilities—whether by validating novel ideas, creating new software systems, or deploying machine learning on robots.

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OpenAI News January 19, 2017 08:00

PixelCNN++: Improving the PixelCNN with discretized logistic mixture likelihood and other modifications

PixelCNNs are a recently proposed class of powerful generative models with tractable likelihood. Here we discuss our implementation of PixelCNNs which we make available at this https URL⁠(opens in a new window). Our implementation contains a number of...

Topics: Models Infrastructure

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OpenAI News November 15, 2016 08:00

OpenAI and Microsoft

We’re working with Microsoft to start running most of our large-scale experiments on Azure.

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OpenAI News November 14, 2016 08:00

On the quantitative analysis of decoder-based generative models

The past several years have seen remarkable progress in generative models which produce convincing samples of images and other modalities. A shared component of many powerful generative models is a decoder network, a parametric deep neural net that defines...

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OpenAI News November 11, 2016 08:00

A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models

Generative adversarial networks (GANs) are a recently proposed class of generative models in which a generator is trained to optimize a cost function that is being simultaneously learned by a discriminator. While the idea of learning cost functions is...

Topics: Models Infrastructure

Entities: Models Infrastructure