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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 ...
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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...
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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...
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OpenAI Fellows Winter 2019 & Interns Summer 2019
We are now accepting applications for OpenAI Fellows and Interns for 2019....
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OpenAI Scholars 2018: Final projects
Our first cohort of OpenAI Scholars has now completed the program....
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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 ...
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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...
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Learning dexterity
We’ve trained a human-like robot hand to manipulate physical objects with unprecedented dexterity....
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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...
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OpenAI Five Benchmark
The OpenAI Five Benchmark match is now over!...
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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...
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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...
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OpenAI Five
Our team of five neural networks, OpenAI Five, has started to defeat amateur human teams at Dota 2....
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OpenAI Blog
Retro Contest: Results
The first run of our Retro Contest—exploring the development of algorithms that can generalize from previous experience—is now complete....
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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...