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Why responsible AI development needs cooperation on safety
We’ve written a policy research paper identifying four strategies that can be used today to improve the…
Transfer of adversarial robustness between perturbation types
Transfer of adversarial robustness between perturbation types. OpenAI News - artificial intelligence news.
Generative modeling with sparse transformers
We’ve developed the Sparse Transformer, a deep neural network which sets new records at predicting what…
Implicit generation and generalization methods for energy-based models
We’ve made progress towards stable and scalable training of energy-based models (EBMs) resulting in…
Introducing Activation Atlases
We’ve created activation atlases (in collaboration with Google researchers), a new technique for…
Neural MMO: A massively multiagent game environment
We’re releasing a Neural MMO, a massively multiagent game environment for reinforcement learning agents.…
Spinning Up in Deep RL: Workshop review
On February 2, we held our first Spinning Up Workshop as part of our new education initiative at OpenAI.
AI safety needs social scientists
We’ve written a paper arguing that long-term AI safety research needs social scientists to ensure AI…
Better language models and their implications
We’ve trained a large-scale unsupervised language model which generates coherent paragraphs of text,…
Computational limitations in robust classification and win-win results
Computational limitations in robust classification and win-win results. OpenAI News - artificial intelligence…
How AI training scales
We’ve discovered that the gradient noise scale, a simple statistical metric, predicts the parallelizability…
Quantifying generalization in reinforcement learning
We’re releasing CoinRun, a training environment which provides a metric for an agent’s ability to…
Spinning Up in Deep RL
We’re releasing Spinning Up in Deep RL, an educational resource designed to let anyone learn to become a…
Learning concepts with energy functions
We’ve developed an energy-based model that can quickly learn to identify and generate instances of…
Plan online, learn offline: Efficient learning and exploration via model-based control
Plan online, learn offline: Efficient learning and exploration via model-based control. OpenAI News -…
Reinforcement learning with prediction-based rewards
We’ve developed Random Network Distillation (RND), a prediction-based method for encouraging reinforcement…
Learning complex goals with iterated amplification
We’re proposing an AI safety technique called iterated amplification that lets us specify complicated…
FFJORD: Free-form continuous dynamics for scalable reversible generative models
FFJORD: Free-form continuous dynamics for scalable reversible generative models. OpenAI News - artificial…
The International 2018: Results
OpenAI Five lost two games against top Dota 2 players at The International in Vancouver this week,…
Large-scale study of curiosity-driven learning
Large-scale study of curiosity-driven learning. OpenAI News - artificial intelligence news.
Learning dexterity
We’ve trained a human-like robot hand to manipulate physical objects with unprecedented dexterity.
Variational option discovery algorithms
Variational option discovery algorithms. OpenAI News - artificial intelligence news.
Glow: Better reversible generative models
We introduce Glow, a reversible generative model which uses invertible 1x1 convolutions. It…
Learning Montezuma’s Revenge from a single demonstration
We’ve trained an agent to achieve a high score of 74,500 on Montezuma’s Revenge from a single human…