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Latest AI tool releases, research breakthroughs, and industry news.
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OpenAI and Microsoft
We’re working with Microsoft to start running most of our large-scale experiments on Azure.
On the quantitative analysis of decoder-based generative models
A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models
RL²: Fast reinforcement learning via slow reinforcement learning
Variational lossy autoencoder
Extensions and limitations of the neural GPU
Semi-supervised knowledge transfer for deep learning from private training data
Report from the self-organizing conference
Last week we hosted over a hundred and fifty AI practitioners in our offices for our first self-organizing conference on machine learning.
Transfer from simulation to real world through learning deep inverse dynamics model
Infrastructure for deep 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.
Machine Learning Unconference
The latest information about the Unconference is now available at the Unconference wiki, which will be periodically updated with more information for attendees.
Team update
We’ve hired more great people to help us achieve our goals. Welcome, everyone!
Special projects
Impactful scientific work requires working on the right problems—problems which are not just interesting, but whose solutions matter.
Concrete AI safety problems
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 technical goals
OpenAI’s mission is to build safe AI, and ensure AI’s benefits are as widely and evenly distributed as possible.
Generative models
This post describes four projects that share a common theme of enhancing or using generative models, a branch of unsupervised learning techniques in machine learning. In addition to describing our work, this post will tell you a bit more about generative models: what they are, why they are important, and where they might be going.
Adversarial training methods for semi-supervised text classification
Team update
We’d like to welcome the latest set of team members to OpenAI (and we’re still hiring!)
OpenAI Gym Beta
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.
Welcome, Pieter and Shivon!
We have two more team updates.