In the early 1960s, computer scientist Ed Feigenbaum became interested in "creating models of the thinking processes of scientists, especially the processes of empirical induction by which hypotheses and theories were inferred from data." In April 1964, he met geneticist (and Noble-prize winner) Joshua Lederberg who told him how experienced chemists use their knowledge about how compounds tend to break up in a mass spectrometer to make guesses about a compound's structure. Recalling in 1987 the development of DENDRAL, the first expert system, Lederberg remarked: "…we were trying to invent AI, and in the process discovered an expert system. This shift of paradigm, 'that Knowledge IS Power' was explicated in our 1971 paper [On Generality and Problem Solving: A Case Study Using the DENDRAL Program], and has been the banner of the knowledge-based-system movement within AI research from that moment." Expert systems represented a new stage in the evolution of AI, shifting from its initial emphasis on general problem-solvers focused on expressing in code human reasoning, i.e., drawing inferences and arriving at logical conclusions.

The American scientist Joshua Lederberg, who has died aged 82, won the 1958 Nobel prize in physiology or medicine for showing that bacteria can conjugate and exchange small strips of genetic material. Among the consequences of this was the realisation that antibiotic resistance can be passed around between bacteria, rather than emerging from selective breeding of resistant strains. This opened new paths in genetic research. He went on to a distinguished career in science policy, advising government committees and presidents, heading Rockefeller University and writing a Washington Post column on science and society. Lederberg's father was an orthodox rabbi - the family had come to New York from Palestine - who wanted Joshua to follow in his footsteps.

James A. Hendler, Edward A. Feigenbaum: Knowledge Is Power: The Semantic Web Vision.

Another concern has been to exploit (d) detection of metabolic disorders of genetic, developmental, toxic or infectious the AI methodology to understand better some fundamental questions in the origins by identification of organic constituents excreted in abnormal quantities philosophy of science, for example the processes by which explanatory hypotheses in human body fluids.

A. Conduct of Science: Computers and Communications and opportunities for the scientific community to share The claim of science to universal validity is supportable only

The discussion centers on a specific video terminal designed and constructed by the authors. This terminal is based on the Intel 8080 microprocessor and is equipped with software sufficient to emiflate the characteristics of standard video terminals required by eral available screen -oriented text editors in common use at sites throughout the ARPAnet (such as E [Samuel, 1978] and TV-Edit [kanerva, 1975]). Screen-oriented editors2 differ from other editors In their use of high-speed video terminals to display the contents of large sections of a file being edited. As editing operations are performed, the display Is revised to indicate their effects on the file (i.e., editing operates In a What you see is what you get mode). Such editors require ter.linals capable of primitive text-processing operations, such as inserting a character in a line of text by shifting the existing characters. In addition to such capabilities, the terminal is typically expected to support 8-bit transmission (instead of the usual 7 bits plus parity), selectable modes for displaying characters (e.g., normal or inverse video, blinking, or dual intensity), and an 80-character line width.

One of the most difficult steps in the development of an expert system is the recruitment and exploitation of the domain wizards. Almost always it is necessary to establish teams of specialists to deal with the programming issues and the user interfaces as well as the incorporation of domain specific knowledge. Experts will communicate how they read a gel, or what is the canonical biological interpretation of DNA sequences conserved over phyletically diverse organisms. The computer scientist will rarely have an independent base of knowledge and experience for critical judgments about the wisdom thus received. Therein may lie the greatest hazards from the proliferation of expert systems; for much of that expertise is fallible.

Cohen, Design Considerations for a Program to Provide Consultations in Clinical Therapeutics, in Proceedings of San Diego Biomedical Symposium, February 1974.

Cohen, Design Considerations for a Program to Provide Consultations in Clinical Therapeutics, in Proceedings of San Diego Biomedical Symposium, February 1974.

The last seven years have seen the field of artificial intelligence (AI) transformed. This transformation is not simple, nor has it yet run its course. The transformation has been generated by the emergence of expert systems. Whatever exactly these are or turn out to be, they first arose during the 1970s, with a triple claim: to be AI systems that used large bodies of heuristic knowledge, to be AI systems that could be applied, and to be the wave of the future. The exact status of these claims (or even whether my statement of them is anywhere close to the mark) is not important. The thrust of these systems was strong enough and the surface evidence impressive enough to initiate the transformation. This transformation has at least two components.