We’re on a journey to advance and democratize artificial intelligence through open source and open science. (more…)

Ensuring fairness in machine learning is important but not straightforward. At Amplitude, we are investing in solutions to address different conceptions of fairness, such as equalized odds, equalized opportunities, and demographic parity. (more…)

As machine learning techniques are increasingly used to make predictions about people, there are a few big ethical questions we need to be asking ourselves.

The ternary classification of the Iris flower data set. (more…)

Learn more about how our Drive Stats data was used in a research paper that examined whether the application of algorithms for interpretable machine learning would predict drive failure and provide meaningful insights about drive health. (more…)