Such early and continuous connections were key. Leveraging commercial technology must be strategic. During this critical early period, core technologies are developed, standards are created, and rollout plans are shaped. When the right experts can connect early in the process, the right technologies can be applied to the right mission needs. Bringing two partners together isn't guaranteed to lead to innovation.

Everyone is talking about artificial intelligence (AI), and with good reason. AI now does simple tasks like playing games. But it also helps pilots fly planes, which is a big reason why we haven't seen a growth in the number of commercial airplane tragedies despite an increasing number of flights. As AI does more complex tasks, it will transform economies, industries and our everyday lives. It will also raise questions about its impact on our economy and jobs.

The deployment was the result of thorough evaluation and an online trial of a number of methods, including profile-based, collaborative filtering and hybrid algorithms. Results taken a few months after deployment show that the recommender system delivered its projected benefits. Traditionally these systems have been used to recommend items to users. The work we describe in this article concerns people-to-people recommendation in an online dating context. People-to-people recommendation is different from item-to-people recommendation: interactions between people are two-way, in that an approach initiated by one person to another can be accepted, rejected or ignored.

Online dating is a prime application area for recommender systems, as users face an abundance of choice, must act on limited information, and are participating in a competitive matching market. This article reports on the successful deployment of a people-to-people recommender system on a large commercial online dating site. The deployment was the result of thorough evaluation and an online trial of a number of methods, including profile-based, collaborative filtering and hybrid algorithms. Results taken a few months after deployment show that the recommender system delivered its projected benefits.