The Isaac Newton Institute: Creating eureka moments

Around 1,000 articles are published on arXiv every day — from the proof of the Poincaré Conjecture to research from AI companies like DeepSeek and Gemini. In this podcast we go behind the scenes to learn what it takes to run such a huge mathematical institution.

How is AI impacting mathematics today?  Geordie Williamson tells us about recent work resulting from genuine collaboration between human and machine.

Fields Medallist Wendelin Werner loves Brownian loop soups. We explore what they are, why he finds them so "natural", and how they are linked to the physics of elementary particles.

Causal inference is the art of discerning cause and effect from data. Find out more in this introduction.

RCTs are the gold standard when it comes to testing whether an intervention, such as a new medical drug, works.

Data can give us incredibly useful insight, but they can also mislead. Here's an example.

How do you discern cause and effect when you can't do a controlled experiment? Directed acyclic graphs (DAGs) are a fun and important tool.

A research programme at the Isaac Newton Institute is investigating how to best discern cause and effect from data.

Cognitive biases shape how we understand data. Being aware of them gives us a better chance of avoiding bias.

A law of nature that was reportedly inspired by an apple falling from a tree. 

In this excerpt from his new book, Blueprints, Marcus du Sautoy makes a case for the suprising connections between maths and art.

A short explanation of the fundamentals of category theory.