Millions of Neuron Visualizations Help Interpret Network Behavior

OpenAI recently launched Microscope, a library of neuron visualizations starting with nine popular or heavily neural networks. In all, the collection encompasses millions of images.  Microscope helps AI researchers better understand the architecture and behavior of neural networks with tens of thousands of neurons, according to a story.

The library includes historically important and common computer vision models like AlexNet, 2012 winner of the now-retired ImageNet challenge, cited over 50,000 times in research. The 2014 winner ImageNet winner GoogleNet (aka Inception V1) and ResNet v2, are also included. Each model visualization comes with a handful of scenarios, and images are available in the OpenAI Lucid library for reuse under a Creative Commons license.

“While we’re making this available to anyone who’s interested in exploring how neural networks work, we think the primary value is in providing persistent, shared artifacts to facilitate long-term comparative study of these models,”OpenAI said on the Microscope website.

Microscope is the latest in attempts to visualize neurons as they perform in the depths of algorithms and neural networks, according to OpenAI in a blog. The neurons look and act like this:

OpenAI bloggers wrote that the program, “has a lot of potential in supporting the Circuits collaboration—a project to reverse engineer neural networks by analyzing individual neurons and their connections—or similar work.”