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We introduce Glow, a reversible generative model which uses invertible 1x1 convolutions. It extends previous work on reversible generative m...
We’ve trained an agent to achieve a high score of 74,500 on Montezuma’s Revenge from a single human demonstration, better than any previousl...
Our team of five neural networks, OpenAI Five, has started to defeat amateur human teams at Dota 2....
The first run of our Retro Contest—exploring the development of algorithms that can generalize from previous experience—is now complete....
We’ve obtained state-of-the-art results on a suite of diverse language tasks with a scalable, task-agnostic system, which we’re also releasi...
We’re now accepting applications for the next cohort of OpenAI Fellows, a program which offers a compensated 6-month apprenticeship in AI re...
We’re releasing the full version of Gym Retro, a platform for reinforcement learning research on games. This brings our publicly-released ga...
We’re releasing an analysis showing that since 2012, the amount of compute used in the largest AI training runs has been increasing exponent...
We’re proposing an AI safety technique which trains agents to debate topics with one another, using a human to judge who wins....
We’re releasing an experimental metalearning approach called Evolved Policy Gradients, a method that evolves the loss function of learning a...
We’re launching a transfer learning contest that measures a reinforcement learning algorithm’s ability to generalize from previous experienc...
On March 3rd, we hosted our first hackathon with 100 members of the artificial intelligence community....
We’ve developed a simple meta-learning algorithm called Reptile which works by repeatedly sampling a task, performing stochastic gradient de...
We’re providing 6–10 stipends and mentorship to individuals from underrepresented groups to study deep learning full-time for 3 months and o...