TL;DR:

This paper brings together ~30 mech interp researchers from 18 different research orgs to review current progress and the main open problems of the field.

This review collects the perspectives of its various authors and represents a synthesis of their views by Apollo Research on behalf of Schmidt Sciences. The perspectives presented here do not necessarily reflect the views of any individual author or the institutions with which they are affiliated.

Abstract

Mechanistic interpretability aims to understand the computational mechanisms underlying neural networks’ capabilities in order to accomplish concrete scientific and engineering goals.

Progress in this field thus promises to provide greater assurance over AI system behavior and shed light on exciting scientific questions about the nature of intelligence.

Despite recent progress toward these goals, there are many open problems in the field that require solutions before many scientific and [...]

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First published:

Source:

Narrated by TYPE III AUDIO.

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