Thread: Circuits

In the original narrative of deep learning, each neuron builds progressively more abstract, meaningful features by composing features in the preceding layer. In recent years, there’s been some skepticism of this view, but what happens if you take it really seriously?

InceptionV1 is a classic vision model with around 10,000 unique neurons — a large number, but still on a scale that a group effort could attack. What if you simply go through the model, neuron by neuron, trying to understand each one and the connections between them? The circuits collaboration aims to find out.

Articles & Comments

The natural unit of publication for investigating circuits seems to be short papers on individual circuits or small families of features. Compared to normal machine learning papers, this is a small and unusual topic for a paper.

To facilitate exploration of this direction, Distill is inviting a “thread” of short articles on circuits, interspersed with critical commentary by experts in adjacent fields. The thread will be a living document, with new articles added over time, organized through an open slack channel (#circuits in the Distill slack). Content in this thread should be seen as early stage exploratory research.

Articles and comments are presented below in chronological order:

Get Involved

The Circuits thread is open to articles exploring individual features, circuits, and their organization within neural networks. Critical commentary and discussion of existing articles is also welcome. The thread is organized through the open #circuits channel on the Distill slack. Articles can be suggested there, and will be included at the discretion of previous authors in the thread, or in the case of disagreement by an uninvolved editor.

If you would like get involved but don’t know where to start, small projects may be available if you ask in the channel.

About the Thread Format

Part of Distill’s mandate is to experiment with new forms of scientific publishing. We believe that that reconciling faster and more continuous approaches to publication with review and discussion is an important open problem in scientific publishing.

Threads are collections of short articles, experiments, and critical commentary around a narrow or unusual research topic, along with a slack channel for real time discussion and collaboration. They are intended to be earlier stage than a full Distill paper, and allow for more fluid publishing, feedback and discussion. We also hope they’ll allow for wider participation. Think of a cross between a Twitter thread, an academic workshop, and a book of collected essays.

Threads are very much an experiment. We think it’s possible they’re a great format, and also possible they’re terrible. We plan to trial two such threads and then re-evaluate our thought on the format.