In this talk, we examine potential developments in the field of computing. Recall that Computer Science is defined as the science of algorithms. The development of computer science and its applications have relied on two cornerstones: Mathematical logic and semiconductor technology. Computing, i.e., execution of an algorithm, is a process of evaluating a logical expression; by the principles of mathematical logic, all logical expression is a combination of simple logical operations, namely, “and”, “or”, and “not”. Thanks to semiconductor technology, these logical operations can be implemented in a substantial manner with high density, high reliability, and low cost. Based on these two cornerstones, the complexity theory has been the major theoretical development of Computer Science. According to this theory, computing problems can be classified as “easy” and “hard”. Easy ones are those in which the computation time is bounded by a polynomial of input size. The majority of computing applications today are in this category. In the future, we must focus on hard problems. One approach is to use non-semiconductor-based physical devices; initial work in quantum computers would fall within this category. Another approach is to develop heuristic algorithms with much lower complexity; this is very much an objective of “Artificial Intelligence” development. The third approach is to leverage properties inherently located within input data, hence improving the computation efficiency.