Given n i.i.d. samples from an unknown discrete distribution over an unknown alphabet, the classical unseen species problem is to predict how many previously unobserved outcomes will be observed in the next m samples. The problem originates with forecasting the number of new species that will be discovered by an ecological expedition. We will discuss a new estimator defined in terms of the minimizer of a certain convex functional and a generalization to set-valued observations.