This paper discusses the role of the data scientist, what a data scientist is, and the set of skills needed to become one.
Articles Published by Francesco Corea
Conversational User Interfaces (CUI) are at the heart of the current wave of AI development. Although many applications and products out there are simply “Mechanical Turks” — which means machines that pretend to be automatized while a hidden person is actually doing all the work — there have been many interesting advancements in speech recognition from the symbolic or statistical learning approaches.
In particular, deep learning is drastically augmenting the abilities of the bots with respect to traditional NLP (i.e., bag-of-words clustering, TF-IDF, etc.) and is creating the concept of “conversation-as-a-platform”, which is disrupting the apps market.
This paper focuses on how AI is disrupting the insurance sector. Starting from the conventional insurance process, we will move through the specific novelties AI is introducing in the field in order to understand how AI is completely changing the way people buy and think of insurance products. Finally, an eight-group classification is proposed for the insurtech ecosystem.
Big data is often approached as a mere technical problem, while many times projects fail because of lack of strategic focus. Implementing the right process may help companies to efficiently run analytics works and for this reason, the paper proposes a few concepts that can support the organizational development of a big data blueprint. Three main ideas will be outlined here: the data lean approach, the maturity map, and different organization models for a data team.
This article explains the rationale of why ML and AI are so important nowadays, as well as tackle a few relevant issues related to AI development.