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.
Company
ai, causal inference, deep-learning, generalization
What I Cannot Control, I Do not Understand
Xiaoyi Yin has graciously translated this blog post to 中文.
I often hear the remark around the proverbial AI watering hole that there are no examples of reinforcement learning (RL) deployed in commercial settings that couldn’t be replaced by simpl…
Uncategorised
Activation Atlas
By using feature inversion to visualize millions of activations from an image classification network, we create an explorable activation atlas of features the network has learned and what concepts it typically represents.
Safety & Alignment
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 o…
Research
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…
Company
Spinning Up in Deep RL: Workshop review
On February 2, we held our first Spinning Up Workshop as part of our new education initiative at OpenAI.
ai, deep-learning, generalization, Machine Learning, reinforcement-learning
Meta-Learning in 50 Lines of JAX
Github repo here: https://github.com/ericjang/maml-jax
Adaptive behavior in humans and animals occurs at many time scales: when I use a new shower handle for the first time, it takes me a few seconds to figure out how to adjust the water temperat…
Uncategorised
AI Safety Needs Social Scientists
If we want to train AI to do what humans want, we need to study humans.
Safety & Alignment
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 uncertain…