From Empty Rhetoric to Meaningful Impact

Mission-Driven Innovation / Fall 2017 Report

We’ve used machine learning to analyze 1,500+ press releases from major public and private organizations, and to reveal what is driving their innovation. By being more specific, and not being afraid to pursue different goals and have distinct values, public and private organizations could create a dynamic that fosters innovation. 

In this report: Google, Tesla, Microsoft, Amazon, Netflix, Samsung, Toyota, Facebook, IBM, Wikimedia, the University of Cambridge, the UK government, the European Commission.

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Dealing with Diversity of Meaning

Machine Learning / Winter 2017 Report

While current vector space models are far from being able to capture all nuances of a language or culture, their geometry could represent early attempts to grasp a universal pattern in the human mind, one that would come with its own structure and logic.

What exactly is the nature of their geometry, and how universal is it?

“Machine Learning: A Structuralist Discipline?” paper published in:

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Well-being and its Norms

Quantified-Self / Summer 2016 Report

We have collaborated with a team of life coaches to develop a series of A.I. powered prototypes aiming at competing with quantified well-being applications. By focussing on asking the right questions and not providing any answers, our prototypes promote a more personal and diverse approach to well-being.


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