Linear Digressions

Katie Malone

hello@lineardigressions.com

For verified host and producer emails, sign up to view.

Booking Overview

This is an interview-led AI explainer show focused on making artificial intelligence understandable, with external conversations featuring highly qualified academic and technical experts. Credible pitches include AI researchers, linguists, cognitive scientists, machine-learning specialists, and experts in human-AI interaction who can explain complex concepts clearly; booking difficulty is likely medium to high because the demonstrated guest profile includes a Stanford professor with cross-disciplinary expertise.

Metrics

Episodes: 318

Frequency: Weekly

Rating: 4.8/5.0

Estimated listeners: 1k-10k

Gender skew: Unknown

Location: USA

Contact Information

hello@lineardigressions.com

For verified host and producer emails, sign up to view.

Host

Katie Malone - Host and creator focused on demystifying artificial intelligence for intellectually curious listeners.

Booking Intelligence

Booking Requirements

high
Typical Credentials:  
Established academic or technical authority in artificial intelligence, machine learning, linguistics, cognition, or human-AI interaction, with the ability to explain complex ideas clearly.
Required Achievements:  

Recent Guest Discussions

Chris Potts - Invisible Failure Modes In AI Chatbots, AI Fluency, Human Misunderstanding Of Language Models, And The Alien Nature Of AI Systems.

Recent Topics

Artificial Intelligence, Machine Learning, Linguistics, Cognition, Human Computer Interaction

Episodes

Here's the recent few episodes on
Linear Digressions
:

Reasoning Models: When LLMs Went Beyond Fancy Autocomplete

August 03, 2026

Reasoning models don't just answer your question — they *think out loud* first. In this episode we dig into the class of AI models that generate intermediate chains of thought before arriving at a final answer, exploring how the internal reasoning process works. Are these models genuinely "thinking," or is something else going on under the hood?

Distillation, or, How to Steal a Model

July 27, 2026

This week we’re covering model distillation: the technique of using a large "teacher" model's outputs to train a smaller, cheaper "student" model that mimics it. They cover the two big reasons labs do this — making lighter, faster, more focused models for specific tasks, and the more contentious use case of effectively copying a rival's flagship model by hammering its API with questions (with a callback to the old Bing/Google search controversy). They also get into why it's so hard to prove d...

Invisible LLM Failures and AI Fluency with Chris Potts (Stanford)

July 20, 2026

What happens when a Stanford linguistics professor turns his attention to AI chatbots — and the surprisingly invisible ways humans misunderstand them? Chris Potts joins the show to unpack the hidden failure modes in how we interact with AI, what it really means to become a more fluent user, and why these language-wielding systems are genuinely alien in ways we're only beginning to reckon with. His perspective sits at a rare intersection of linguistics, cognition, and machine learning — and it...

Get your clients booked on top podcasts

Try us risk free with a FREE 3 days trial.

Start Your Free Trial

Join hundreds of PR teams using Podseeker to pitch and land bookings