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Seminary: "Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML (and what we are doing to get there)", Dott. Interlandi (Microsoft), Thursday December 19th, h. 14-16, room P1.3

Abstract: Machine learning (ML) has proven itself in high-value web applications such as search ranking and is emerging as a powerful tool in a much broader range of enterprise scenarios including voice recognition and conversational understanding for customer support, autotuning for videoconferencing, manufacturing and autonomous vehicle management, complex financial predictions, just to name a few. Meanwhile, as the value of data is increasingly recognized and monetized, concerns about securing valuable data and risks to individual privacy have been growing. Consequently, rigorous data management has emerged as a key requirement in enterprise settings. How will these trends (ML growing popularity, and stricter data governance) intersect? What are the unmet requirements for applying ML in enterprise settings? In this talk I will present our vision of how ML and database systems are likely to come together, and early steps we are taking towards making this vision a reality.

Bio: Matteo Interlandi is a Senior Scientist in GSL at Microsoft, working on scalable Machine Learning systems. Before Microsoft, he was a Postdoctoral Scholar in the CS Department at the University of California, Los Angeles under the supervision of Professor Tyson Condie and working on Big Data systems. Matteo Interlandi received his PhD on 2014 from the International Doctorate in Information and Communication Technologies at University of Modena and Reggio Emilia under the supervision of Professor Sonia Bergamaschi.

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