"Computing can change our ways of thinking about many things, mathematics, biology, engineering, administrative procedures, and many more. But my main concern is that it can change our thinking about ourselves: giving us new models, metaphors, and other thinking tools to aid our efforts to fathom the mysteries of the human mind and heart. The new discipline of Artificial Intelligence is the branch of computing most directly concerned with this revolution. By giving us new, deeper, insights into some of our inner processes, it changes our thinking about ourselves. It therefore changes some of our inner processes, and so changes what we are, like all social, technological and intellectual revolutions." This book, published in 1978 by Harvester Press and Humanities Press, has been out of print for many years, and is now online, produced from a scanned in copy of the original, digitised by OCR software and made available in September 2001. Since then a number of notes and corrections have been added. Atlantic Highlands, NJ: Humanities Press.

We have attempted to discover formal rules for transcribing into musical notation the fugue subjects of the Well-Tempered Clavier, as this might be done by an amanuensis listening to a'deadpan' performance on the keyboard. In this endeavour two kinds of problem arise: what are the harmonic relations between the notes, and what are the metrical units into which they are grouped? The harmonic problem is that the number of keyboard semitones between two notes does not define-- their harmonic relation, and we further develop an earlier theory of such relations, arriving at an algorithm which assigns every fugue to the right key and correctly notates every accidental in its subject.

Over the past few years, there has been a growing interest in statistics and machine learning. Today, machine learning can help us make smarter decisions, and big data controls everything in our lives. It influences how we work, shop and do business. Data even help the police determine when and where the next crime is likely to happen. But how is it all happening and how did it all start?

How often do you hear people use the terms "artificial intelligence" and "machine learning" interchangeably? The two are definitely related, and machine learning is actually a subset of artificial intelligence. However, as a greater number of businesses begin offering "intelligent" solutions, it becomes more vital than ever before to differentiate between these two concepts. After all, you may find yourself giving a presentation or speaking with someone who specializes in one of these fields, and you want to know what you're talking about. From cancer screenings to climate change, there are numerous applications for artificial intelligence.

E.A. Feigenbaum and J. Feldman (Eds.). Computers and Thought. McGraw-Hill, 1963. This collection includes twenty classic papers by such pioneers as A. M. Turing and Marvin Minsky who were behind the pivotal advances in artificially simulating human thought processes with computers. All Parts are available as downloadable pdf files; most individual chapters are also available separately. COMPUTING MACHINERY AND INTELLIGENCE. A. M. Turing. CHESS-PLAYING PROGRAMS AND THE PROBLEM OF COMPLEXITY. Allen Newell, J.C. Shaw and H.A. Simon. SOME STUDIES IN MACHINE LEARNING USING THE GAME OF CHECKERS. A. L. Samuel. EMPIRICAL EXPLORATIONS WITH THE LOGIC THEORY MACHINE: A CASE STUDY IN HEURISTICS. Allen Newell J.C. Shaw and H.A. Simon. REALIZATION OF A GEOMETRY-THEOREM PROVING MACHINE. H. Gelernter. EMPIRICAL EXPLORATIONS OF THE GEOMETRY-THEOREM PROVING MACHINE. H. Gelernter, J.R. Hansen, and D. W. Loveland. SUMMARY OF A HEURISTIC LINE BALANCING PROCEDURE. Fred M. Tonge. A HEURISTIC PROGRAM THAT SOLVES SYMBOLIC INTEGRATION PROBLEMS IN FRESHMAN CALCULUS. James R. Slagle. BASEBALL: AN AUTOMATIC QUESTION ANSWERER. Green, Bert F. Jr., Alice K. Wolf, Carol Chomsky, and Kenneth Laughery. INFERENTIAL MEMORY AS THE BASIS OF MACHINES WHICH UNDERSTAND NATURAL LANGUAGE. Robert K. Lindsay. PATTERN RECOGNITION BY MACHINE. Oliver G. Selfridge and Ulric Neisser. A PATTERN-RECOGNITION PROGRAM THAT GENERATES, EVALUATES, AND ADJUSTS ITS OWN OPERATORS. Leonard Uhr and Charles Vossler. GPS, A PROGRAM THAT SIMULATES HUMAN THOUGHT. Allen Newell and H.A. Simon. THE SIMULATION OF VERBAL LEARNING BEHAVIOR. Edward A. Feigenbaum. PROGRAMMING A MODEL OF HUMAN CONCEPT FORMULATION. Earl B. Hunt and Carl I. Hovland. SIMULATION OF BEHAVIOR IN THE BINARY CHOICE EXPERIMENT Julian Feldman. A MODEL OF THE TRUST INVESTMENT PROCESS. Geoffrey P. E. Clarkson. A COMPUTER MODEL OF ELEMENTARY SOCIAL BEHAVIOR. John T. Gullahorn and Jeanne E. Gullahorn. TOWARD INTELLIGENT MACHINES. Paul Armer. STEPS TOWARD ARTIFICIAL INTELLIGENCE. Marvin Minsky. A SELECTED DESCRIPTOR-INDEXED BIBLIOGRAPHY TO THE LITERATURE ON ARTIFICIAL INTELLIGENCE. Marvin Minsky.

Between 1946 and 1956, a number of BBC radio broadcasts were made by pioneers in the fields of computing, artificial intelligence and cybernetics. Although no sound recordings of the broadcasts survive, transcripts are held at the BBC's Written Archives Centre at Caversham in the UK. This paper is based on a study of these transcripts, which have received little attention from historians. The paper surveys the range of computer-related broadcasts during 1946-1956 and discusses some recurring themes from the broadcasts, especially the relationship of'artificial intelligence' to human intelligence.