We’re working with Microsoft to start running most of our large-scale experiments on Azure.
Last week we hosted over a hundred and fifty AI practitioners in our offices for our first self-organizing conference on machine learning.
Deep learning is an empirical science, and the quality of a group’s infrastructure is a multiplier on progress. Fortunately, today’s open-source ecosystem makes it possible for anyone to build great deep learning infrastructure.
QEST is a leading forum on quantitative evaluation and verification of computer systems and networks, through stochastic models and measurements
The latest information about the Unconference is now available at the Unconference wiki, which will be periodically updated with more information for attendees.
We’ve hired more great people to help us achieve our goals. Welcome, everyone!
Impactful scientific work requires working on the right problems—problems which are not just interesting, but whose solutions matter.
We will be holding a Graduate Open Day on Saturday 5 November for those interested in the DPhil and MSc in Computer Science
The National Centre for the Replacement, Refinement & Reduction of Animals in Research (NC3Rs) has awarded £500k to department Prof. Blanca Rodriguez
The HVC award is given to the most influential work in the last five years in formal verification, simulation, and testing.
We (along with researchers from Berkeley and Stanford) are co-authors on today’s paper led by Google Brain researchers, Concrete Problems in AI Safety. The paper explores many research problems around ensuring that modern machine learning systems operate as intended.
OpenAI’s mission is to build safe AI, and ensure AI’s benefits are as widely and evenly distributed as possible.
The 2016 Workshop on Research for Insider Threats held as part of the 37th IEEE Symposium on Security and Privacy
We’d like to welcome the latest set of team members to OpenAI (and we’re still hiring!)
14:00, 24 May 2016, Oxford
Thursday 16 June 2016, 13:00 – 18:00
We’re releasing the public beta of OpenAI Gym, a toolkit for developing and comparing reinforcement learning (RL) algorithms. It consists of a growing suite of environments (from simulated robots to Atari games), and a site for comparing and reproducing results.
We have two more team updates.
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