Improve your data with model-based anomaly detection

Learn how to find outliers, anomalies, and hidden errors to protect you and your customers, and keep data quality high

Identifying and visualizing different sources of uncertainty in machine learning

How the Redpoll platform conveys uncertainty information to promote appropriate trust, and to guide efficient data collection

Better Synthetic Data with Redpoll Reformer

Complex artificial data creation that maintains meaning

Tutorial: Infinite Mixture Model in Rust with rv 0.12

Building a supremely useful model in a supremely useful programming language.

Epistasis is easy

Nonlinearity can be understood simply... with the right tools

Use Case: Anomaly as Diversity in Plant Breeding

Optimizing for genetic distance can cause information loss

Escaping the data science death spiral

How today's Machine Learning technology forces us into wasteful processes and how we can escape them

Faster and cheaper with stream-native artificial intelligence

Use Case: Gamma Ray Detection with the MAGIC Telescope

Hands-on with Reformer

Components of safe Artificial Intelligence

What artificial intelligence needs — in addition to people — to be safe

On Humanistic Artificial Intelligence

Choosing cognition — not the brain — as the basis of Artificial Intelligence design

Why we are using plant breeding to test defense AI

Like the battlefield, nature is a complex and unpredictable system that crushes best-laid plans under constant and unprecedented change

Redpoll partners with Rutgers and DARPA to build AI that adapts to dynamic worlds

The OTACON project aims to deliver introspective AI

Announcing rv 0.8.0

A rust crate for building probabilistic programming tools

Explainable AI is not enough.

Explaining black box AI won't prevent problems; it will make them worse.

How to design an efficient data collection plan for science and AI

To ensure that our AI predict accurately, we must provide it with the right data.

Three ways to get value out of machine learning in scientific research

Mainstream AI has neglected the needs of scientists, but that doesn't mean there is nothing for us to do.