Machine Learning

Machine learning is, without a doubt, a highly transformative technology for the future. Fueled by the breakthroughs in deep learning, predictive algorithms are quickly transforming and disrupting entire business models, with all major tech companies redefining themselves in light of an “AI-first” philosophy.

Consider the newly announced Google Duplex service, which can make phone calls autonomously on your behalf for multiple tasks, such as scheduling or deleting appointments. Behind the scenes, this requires a wide array of different skills, including (a) understanding what the user at the other end of the phone is saying, (b) keeping track of the context of the conservation, (c) generating answers, and (d) transforming these answers into human-like voice. Amazingly, all these skills are powered by deep learning technologies that appeared almost simultaneously in the last few years.

Figure 1: (image source)

In short: machine learning is evolving quickly and it is being adopted even faster. The session on machine learning (May 18, Room N13, 3:15pm) at the Data Driven Innovation conference will try to analyze how this process is advancing and how companies are responding to the change, with the participation of five guest speakers:

  • Giovanni Galloro (Google) will describe how both cloud solutions and open-sourcing can foster the adoption of machine learning, by lowering the technical requirements required to adopt an AI solution.
  • Raniero Romagnoli (AlmaWave) will focus on the disruption in natural language processing, and how deep learning has reinvented the way we model, analyze and generate language inside businesses and organizations.
  • Gabriele Randelli (HPE) on the use of machine learning in telecommunications, for analyzing and understanding the customer insights and offer personalized support and automated network operations.
  • Manuel Roveri (Politecnico di Milano) on how self-adapation goes much beyond telecommunications, becoming an essential aspect of the internet of things and of cyber-physical systems.
  • Davide Camera (Excelle) on how machine learning can benefit even not-for-profit organizations, by improving their fundraising, investments’ evaluations, and more.

Promosso e organizzato da

Roma Tre
Maker Faire

Con il contributo scientifico di


Under the Patronage
Autorità Garante della Concorrenza e del Mercato

Main Partner
Eni
Bnl
Acea
Google


Diamond Partner
Hpe

Silver Partner
Data ReplyCerved
Official Taxi
My Taxi

Technical Partner
Iaml Tecnopolo di Roma

Ecosystem Partner
Talent Garden

Community Partner
Machine Learning

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Car

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Il Messaggero

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