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OpenAI News

OpenAI Scholars 2019: Meet our Scholars

Our class of eight scholars (out of 550 applicants) brings together collective expertise in literature, philosophy, cell biology, statistics, economics, quantum physics, and business innovation.

Topics: Models

Entities: OpenAIModels

OpenAI News

OpenAI LP

We’ve created OpenAI LP, a new “capped-profit” company that allows us to rapidly increase our investments in compute and talent while including checks and balances to actualize our mission.

Topics: Models

Entities: OpenAIModels

OpenAI News

Introducing Activation Atlases

We’ve created activation atlases (in collaboration with Google researchers), a new technique for visualizing what interactions between neurons can represent. As AI systems are deployed in increasingly sensitive contexts, having a better understanding of...

Entities: Google

OpenAI News

Neural MMO: A massively multiagent game environment

We’re releasing a Neural MMO, a massively multiagent game environment for reinforcement learning agents. Our platform supports a large, variable number of agents within a persistent and open-ended task. The inclusion of many agents and species leads to...

Topics: Agents

Entities: Agents

OpenAI News

AI safety needs social scientists

We’ve written a paper arguing that long-term AI safety research needs social scientists to ensure AI alignment algorithms succeed when actual humans are involved. Properly aligning advanced AI systems with human values requires resolving many uncertainties...

Topics: ModelsPolicy

Entities: OpenAIModelsPolicy

OpenAI News

Computational limitations in robust classification and win-win results

We continue the study of statistical/computational tradeoffs in learning robust classifiers, following the recent work of Bubeck, Lee, Price and Razenshteyn who showed examples of classification tasks where (a) an efficient robust classifier exists, in the...

OpenAI News

How AI training scales

We’ve discovered that the gradient noise scale, a simple statistical metric, predicts the parallelizability of neural network training on a wide range of tasks. Since complex tasks tend to have noisier gradients, increasingly large batch sizes are likely to...

Topics: Infrastructure

Entities: Infrastructure