  This paper reviews the checkered history of predictive distributions in
statistics and discusses two developments, one from recent literature and the
other new. The first development is bringing predictive distributions into
machine learning, whose early development was so deeply influenced by two
remarkable groups at the Institute of Automation and Remote Control. The second
development is combining predictive distributions with kernel methods, which
were originated by one of those groups, including Emmanuel Braverman.
