TheSequence

TheSequence

Share this post

TheSequence
TheSequence
The Sequence Radar #693: A New Series About Interpretability in Foundation Models

The Sequence Radar #693: A New Series About Interpretability in Foundation Models

What are our best chances to understand AI black boxes ?

Jul 29, 2025
∙ Paid
12

Share this post

TheSequence
TheSequence
The Sequence Radar #693: A New Series About Interpretability in Foundation Models
Share
Created Using GPT-4o

Today we will Discuss:

  1. An intro to our series about AI interpretability in foundation models.

  2. A review of the famous paper Attention is No Explanation.

💡 AI Concept of the Day: A New Series About Interpretability in Foundation Models

Today, we start a new series about one of hottest trends in AI: interpretability in frontier models.

Frontier models—neural networks with trillions of parameters trained on vast, diverse datasets—have redefined the limits of AI performance. Yet their sheer complexity renders them largely inscrutable, obscuring how they arrive at specific predictions or decisions. Bridging this gap between unparalleled capabilities and human understanding has become imperative for advancing AI safety, accountability, and trust.

Mechanistic Interpretability

This post is for paid subscribers

Already a paid subscriber? Sign in
© 2025 Jesus Rodriguez
Privacy ∙ Terms ∙ Collection notice
Start writingGet the app
Substack is the home for great culture

Share