A fast quantum mechanical algorithm for database search
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer
SIAM Journal on Computing
Statistical methods for speech recognition
Statistical methods for speech recognition
Computer Power and Human Reason: From Judgment to Calculation
Computer Power and Human Reason: From Judgment to Calculation
Christopher Strachey: Recollections of His Influence
Higher-Order and Symbolic Computation
Overview of candidate device technologies for storage-class memory
IBM Journal of Research and Development
Expert system based on neuro-fuzzy rules for diagnosis breast cancer
Expert Systems with Applications: An International Journal
Quantum computing: an IBM perspective
IBM Journal of Research and Development
Technologies for exascale systems
IBM Journal of Research and Development
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Every year, the IBM Research Division undertakes a year-long process to analyze and map out important trends and future directions shaping the advances and the applications of information technology (IT). The results are summarized in a document called the Global Technology Outlook (GTO), which influences IBM's strategy and technology roadmaps. Coinciding with the IBM Centennial, a special chapter was commissioned in the 2011 GTO, which was designed to both reflect on the historical evolution of computers and computation as well as to look a few decades ahead to explore the new frontiers of IT. This paper presents the results of this study. It provides a vision of the future in which advances in technology will enable the creation of a new class of "learning" systems, i.e., designed with people as an integral and central element of the process, and which are explicitly aimed to enhance human cognition. These systems will learn from both structured and unstructured data, find important correlations, create hypotheses for these correlations, and suggest and measure actions to enable better outcomes for users. Systems with these capabilities will transform our view of computers from "calculators" to "machines that learn," which is a shift that will radically alter our expectations of what computing ought to do for us as humans and that will equip us to successfully navigate the increasing complexity of our globally interconnected world.