Design and Intelligent Machines

Many are interested in the design of intelligent machines. The fact is, despite enormous individual engineering lack design tools able to operate on such complex advances in recent years, we remain woefully planes. If which is that machines can be designed to work in anything, we should be not afraid of what we are partnership with people to extend and augment designing but rather accelerating our efforts in the human cognitive capabilities (Licklider 1960). We domain of design -- in part to design machines that have created impressive systems that can enhance can, in turn, help us become better designers. In his seminal work, The Sciences of the Of course, we have computer-aided design tools.

This article focuses on a broad framing of the DARPA Transfer Learning Program research and an assessment of its progress, limitations, and challenges, from an admittedly personal but DARPA-influenced perspective. I will focus on a broad framing of TL that that will allow us to talk about this body of work as a whole, and use this to look towards work yet to be done in this area. I will consider both indicated application areas for transfer learning, as well as indicated future research challenges. With each of these I will also venture assessment of the "ripeness" of each of these subareas for follow on work-of course this assessment will be a very personal estimation based on the effort and progress made during the TL program.