It’s no surprise to find music at the center of many important moments of our lives – think of a wedding march, a “Happy Birthday”, or even a funeral procession. Music is deeply tied to the human experience; each song and each moment is personal to the listener. Over the last year, Watson has been studying up on music themes, theory, moods, and emotions – and how they correlate and connect with each other. Now, Watson is inspiring musical creativity with Grammy-winning music producer Alex Da Kid, who used Watson’s technology to inspire his new song about heartbreak, “Not Easy”. This is the first song in Alex’s 4-track EP in collaboration with Watson.
Ten months ago we assembled a team from IBM Research in Switzerland and IBM tape developers based in Tucson, Arizona, to try to build something which has never been built before to address a risk that may not materialize for another decade or more. As you can tell, we love a good challenge.
Convex optimization problems, which involve the minimization of a convex function over a convex set, can be approximated in theory to any fixed precision in polynomial time. However, practical algorithms are known only for special cases. An important question is whether it is possible to develop algorithms for a broader subset of convex optimization problems that are efficient in both theory and practice.