AI

Prototypical Contrastive Learning unifies clustering and contrastive self-supervised learning to push the frontiers of unsupervised learning.

You know what data is: facts and figures and info. And you know what analytics is: analysis involves looking at facts and coming to conclusions. So how do they fit together? Easily, it…

Conversational commerce is a new way to provide excellent customer service and commerce experiences on digital channels.

When call volume spikes, how do customer support teams scale up to meet needs and maintain CX? Automation to the rescue! Here’s how.

Marketers need to channel their stores of empathy when contacting customers in today’s climate. Here's how to use AI to help craft those messages.

We show that deep neural models can describe common sense physics in a valid and sufficient way that is also generalizable. Our ESPRIT framework is trained on a new dataset with physics simulations and descriptions that we collected and have open-sourced.

In this work, we focus on the opportunity to use AI to promote social welfare through the design of optimal tax policies in dynamic economies.

Plus More Insights From the Q1 Shopping Index

In the face of COVID-19, we’ve changed how we interact with friends, families, colleagues — and businesses. As our behavior has shifted, so has the data connected with it. Now your models may be producing atypical results. Here’s what you need to know to make sure your AI predictions support your customers now.