AI safety via debate
We’re proposing an AI safety technique which trains agents to debate topics with one another, using a human to judge who wins.
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We’re proposing an AI safety technique which trains agents to debate topics with one another, using a human to judge who wins.
Learn how to build a realtime GraphQL server with subscriptions so clients can receive live event updates.
We’re releasing an experimental metalearning approach called Evolved Policy Gradients, a method that evolves the loss function of learning agents, which can enable fast training on novel tasks. Agents trained with EPG can succeed at basic tasks at test time that were outside their training regime, like learning to navigate to an object on a different side of the room from where it was placed during training.
We’re launching a transfer learning contest that measures a reinforcement learning algorithm’s ability to generalize from previous experience.
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