Virtual & On-Demand Content

Connections allow us to understand behaviours, dynamics, interactions, to define how certain phenomena occur and to foresee what is going to happen.
Therefore, connected data become fundamental also for AI because they create a better context for a better learning.
Moreover, the context itself becomes an essential tool for the explainability of the results, which is an increasingly important topic especially in those cases in which AI has an impact on human lives.
We will discuss all the above analysing a few successful examples.

Headspace is a values-first company: through 10 years of innovating the use of technology in meditation and mindfulness, the focus has never shifted from making sure that our approach to technological implementation is as mindful as our content.

Over the last year, much of that innovation has centered around ML-powered personalization: from in-app content recommendation to push notifications to AI-driven dynamic welcome flows. But implementing ML/AI solutions brings unique challenges: personalization is inherently intimate and demands great sensitivity in the ways we use and communicate member data.

In this talk, we’ll explore how Headspace balances the intimate and data-centric process of building ML solutions while maintaining our brand identity as a mindful actor.