Linear Digressions

Technology Podcasts

Linear Digressions is a podcast about machine learning and data science. Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago. 896520

Episodes

The Impact of AI on Podcasting (Harvard Data Science Review Cross-Post)

Better Know A Benchmark: ExploitGym

Constitutional AI

A Data-Driven Reality Check on AI in Business (Interview with Tom Davenport, Babson College)

Understanding AI Text Watermarking

Better Know a Benchmark: Humanity's Last Exam

A Scientific Deep Dive into Overconfident LLMs: Interview with Kaitlyn Zhou (Cornell)

Reasoning Models: When LLMs Went Beyond Fancy Autocomplete

Distillation, or, How to Steal a Model

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

Still summer break: back next week

Summer break: back soon

Interviewing the Linear Digressions Agents (The Agents Season, Episode 11)

Agent Economics (The Agents Season, Episode 10)

Agent Trust, Oversight and Control (The Agents Season, Episode 9)

Many Agents, Many Problems (The Agents Season, Episode 8)

How Do You Evaluate An AI Agent? (The Agents Season, Episode 7)

AI Agent Failure Modes (The Agents Season, Episode 6)

Agentic Planning (The Agents Season, Episode 5)

Memory Management for AI Agents (The Agents Season, Episode 4)