Alan Fern points out the second branch prediction challenge (due September 29) which is a follow up to the first branch prediction competition. Branch prediction is one of the fundamental learning problems of the computer age: without it our computers might run an order of magnitude slower. This is a tough problem since there are sharp constraints on time and space complexity in an online environment. For machine learning, the “idealistic track” may fit well. Essentially, they remove these constraints to gain a weak upper bound on what might be done.