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Reinforcement learning with prediction-based rewards
We’ve developed Random Network Distillation (RND), a prediction-based method for encouraging reinforcement learning agents to explore their ...
Learning complex goals with iterated amplification
We’re proposing an AI safety technique called iterated amplification that lets us specify complicated behaviors and goals that are beyond hu...
OpenAI Scholars 2019: Applications open
We are now accepting applications for our second cohort of OpenAI Scholars, a program where we provide 6–10 stipends and mentorship to indiv...
OpenAI Fellows Winter 2019 & Interns Summer 2019
We are now accepting applications for OpenAI Fellows and Interns for 2019....
OpenAI Scholars 2018: Final projects
Our first cohort of OpenAI Scholars has now completed the program....
The International 2018: Results
OpenAI Five lost two games against top Dota 2 players at The International in Vancouver this week, maintaining a good chance of winning for ...
OpenAI Five Benchmark: Results
Yesterday, OpenAI Five won a best-of-three against a team of 99.95th percentile Dota players: Blitz, Cap, Fogged, Merlini, and MoonMeander—f...
Learning dexterity
We’ve trained a human-like robot hand to manipulate physical objects with unprecedented dexterity....
OpenAI Scholars 2018: Meet our Scholars
Our first class of OpenAI Scholars is underway, and you can now follow along as this group of experienced software developers becomes machin...
OpenAI Five Benchmark
The OpenAI Five Benchmark match is now over!...
Glow: Better reversible generative models
We introduce Glow, a reversible generative model which uses invertible 1x1 convolutions. It extends previous work on reversible generative m...
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 demonstration, better than any previousl...
OpenAI Five
Our team of five neural networks, OpenAI Five, has started to defeat amateur human teams at Dota 2....
Retro Contest: Results
The first run of our Retro Contest—exploring the development of algorithms that can generalize from previous experience—is now complete....
Improving language understanding with unsupervised learning
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...