Futuretalk: one small step towards a Chronolinguistics

In the area of linguistics and language teaching, science fiction is useful in very many ways. An obvious way is that it sets up many complex and rich worlds and outlines the sorts of adjustments that language must make in those contexts. It thus draws a strong link between language and context; it shows how the construction of reality is largely a matter of language; and it speculates on where we are linguistically heading. It is a useful mirror on language development. Extrapolating the dialects of the future has been the province of science fiction in the last century. Though few SF writers are professional linguists, their method in general tends to take a holistic view of form, meaning and social context. Characters in science fiction are not individuals but are 'everyman' tokens, and the language they use symbolises the culture they inhabit. Linguistic extrapolation in science fiction thus treats language both as the technology of communication and as an index of social change. In this paper, I argue that predicting the language of the future, though extremely difficult, is possible. I call this new discipline chronolinguistics, and I set out the draft principles and parameters of a chronolinguistics, based on the future languages speculated by John Brunner, Russell Hoban, William Gibson, Greg Bear, Neal Stephenson and Iain M.Banks.

The MUSE Machine -- an Architecture for Structured Data Flow Computation

Computers employing some degree of data flow organisation are now well established as providing a possible vehicle for concurrent computation. Although data-driven computation frees the architecture from the constraints of the single program counter, processor and global memory, inherent in the classic von Neumann computer, there can still be problems with the unconstrained generation of fresh result tokens if a pure data flow approach is adopted. The advantages of allowing serial processing for those parts of a program which are inherently serial, and of permitting a demand-driven, as well as data-driven, mode of operation are identified and described. The MUSE machine described here is a structured architecture supporting both serial and parallel processing which allows the abstract structure of a program to be mapped onto the machine in a logical way.