Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Singularities against the Singularity: Announcing Workshop on Singular Learning Theory and Alignment, published by Jesse Hoogland on April 1, 2023 on LessWrong.

We are excited to announce a two-week seminar on singular learning theory (SLT) and AI alignment, taking place from June 19th to July 2nd in Berkeley. SLT studies the relation between the geometry of the loss landscape and the computational properties of machines learning in that landscape. It builds on powerful theoretical and experimental machinery developed in physics (esp. solid-state physics), where it is the geometry of the energy landscape that determines the relevant properties of physical systems.

During this workshop, we'll bring together singular learning theorists and alignment researchers to connect and further the applications of singular learning theory to alignment. The workshop aims to familiarize alignment researchers with SLT, seed new research collaborations, and develop tools based on SLT ideas. There will be talks by Daniel Murfet, Susan Wei, Shaowei Lin, Alexander Gietelink Oldenziel, Jesse Hoogland, and others.

Time-Commitment Options

We offer two different time-commitment options for participants.

Full-Time: This track is designed for participants who want to fully engage with the material and delve deep into the concepts and applications of SLT.

Intermittent: This track is designed for participants who want to get a taster of SLT and its applications for alignment without committing to the full two-week program. Several lectures will be open to a broader AI safety audience and will assume less familiarity with the subject. Participants will be able to join for just the afternoon or attend selected lectures throughout the two weeks.

Overview

The seminar consists of two parts.

Week 1: "The Primer"

The first week will provide a comprehensive introduction to SLT and its relevance to AI alignment. The material is designed to be approachable if you have the equivalent of a technical undergraduate degree (e.g., in CS, math, or physics).

Participants will have the opportunity to learn from lectures covering topics such as thermodynamics, catastrophe theory, algebraic geometry, and SLT. There will also be sessions focused on experimental aspects of SLT and introductions to AI alignment and mechanistic interpretability.

Weekend: Hackathon

During the weekend, we will host a hackathon dedicated to developing novel SLT-based tools.

Week 2: Advanced Topics and Collaboration

The second week will delve deeper into the SLT and algebro-geometric foundations behind the toy models of superposition paper. This will serve as an application of the material covered in the first week, allowing participants to fully grasp the concepts and their relevance to AI alignment. The week will also feature presentations from researchers, open discussions, and opportunities for networking and collaboration.

Registration

If you're interested in participating, please register by filling out this form. Further updates on event details will be provided to registered participants.

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