PowerWhy

A.I. needs to get real—and other takeaways from this year’s NeurIPS

Hello and welcome to the last “Eye on A.I.” of 2020! I spent last week immersed in the Neural Information Processing Systems (NeurIPS) conference, the annual gathering of top academic A.I. researchers. It’s always a good spot for taking...

Fujitsu uses AI to discover characteristic causal relationships of individual data in medicine, marketing, and more

In a recent trial demonstration, Fujitsu’s researchers succeeded in rediscovering the gene of interest in the colorectal cancer classification, offering a key to the development of a treatment plan individualised for each patient Fujitsu has developed...

This basic human skill is the next major milestone for A.I.

The original article was published at Digital Trends. Remember the amazing, revelatory feeling when you first discovered the existence of cause and effect? That’s a trick question. Kids start learning the principle of causality from as early as eight...

Understanding Causality Is the Next Challenge for Machine Learning

The original article was published here. “Causality is very important for the next steps of progress of machine learning,” said Yoshua Bengio, a Turing Award-wining scientist known for his work in deep learning, in an interview with IEEE Spectrum in...

DeepMind Introduces Algorithms for Causal Reasoning in Probability Trees

The original article was published here. Probability trees may have been around for decades, but they have received little attention from the AI and ML community. Until now. “Probability trees are one of the simplest models of causal generative processes,”...

What Statisticians Want to Know about Causal Inference and The Book of Why

I was privileged to be interviewed recently by David Hand, Professor of Statistics at Imperial College, London, and a former President of the Royal Statistical Society. I would like to share this interview with readers of this blog since many of the questions...