“Research at Netflix is aimed at improving various aspects of our business. Research applications span many areas including our personalization algorithms, content valuation, and streaming optimization. To maximize the impact of our research, we do not centralize research into a separate organization. Instead, we have many teams that pursue research in collaboration with business teams, engineering teams, and other researchers.
This allows for close partnerships between researchers and the business or engineering teams in each area. In addition, research that applies to the same methodological area or business area is shared and highlighted in discussion and debate forums to strengthen the work and its impact. These forums also serve to identify and motivate future research directions”.
« Here, we are interested in the 2006-2015 period, ten years during which 25.000 projects involving 45.000 people produce a 2-mode graph of more than 63.000 edges. To focus on projects and disciplines, the network is projected into a 1-mode graph of projects only. Thus, the graph displayed below contains over 15.000 projects that were funded between 2006 and 2015 » – Martin Grandjean.
« L’analyse automatique des textes se prête bien à l’apprentissage profond, capable de traiter efficacement de grandes quantités de données », explique Yoshua Bengio, directeur du MILA. « Grâce au Fonds Druide, nous pourrons accroitre d’environ 20 % notre budget de recherche pour l’analyse des textes.