The reference to GC7 (Grand Challenge 7: Journeys in Non-Classical Computation)
assumes some knowledge about the recent UKCRC Research Grand Challenges initiative.
The main 'Grand Challenges' site is at http://www.ukcrc.org.uk/grand-challenge/
If anyone wishes to add comments on this document, attributed or unattributed, send them to me in html or plain text please.
A note referring to a short e-book by Tuck Newton, inspired by John von Neumann, is below (added 8 Feb 2015).
In order to evaluate the proposal, I tried peering into my googol-ball that takes me into the future, turning the knob to the year 2106 and focusing on major educational and research activities. Unfortunately at that distance things get a bit blurred, but this is what I saw through the mists and swirls (I think).
There are some people giving inspiring lectures to large, enthusiastic classes of first year students on varieties of information processing, in brains, in minds, in ecosystems, in developing embryos, in social systems, in control of space-time transporters, and also a few other application areas.
These students seem to be learning about multi-layered virtual machines of various kinds, and also learning the recent history of how this sort of study stood philosophy of mind on its head, revolutionised ideas about causation (because processes in virtual machines cause and control most of the phenomena we find interesting), transformed and unified a host of academic disciplines that used to be in separate departments and also led to new cosmological theories, including the latest proposal for combining relativity and quantum theory in an information processing framework.
Information as inherently involving semantic content (reference, truth, falsity, implication relations) has joined matter and energy as fundamental constituents of reality though the relations between those three, and whether life has to be something extra or merely a manifestation of their interaction remains controversial in some quarters. There is a groundswell of support in a few religiously controlled countries for compulsory teaching of the 'IL' theory (Irreducibility of Life Theory).
In the most internationally respected universities, students in the main science, humanities, medical, and engineering fields, all come to university already having had experience of designing, implementing, documenting, analysing, explaining, and criticising a variety of information processing systems.
Most of the scientific, engineering and medical centres in universities expect their students to spend much of their first year extending and deepening their general understanding of such systems through more practical work, theoretical and modelling studies of varieties of information processing systems in nature and to a lesser extent in artifacts, and through an introduction to the new mathematics developed for the study of multiple, changing, continuously interacting multi-level information processing systems embedded in complex dynamic environments, especially Bornat's theorem (2025) about the nearly cyclic growth and decay of multi-level interacting attractor basins.
The practical modelling work by students is done in large central learning-support virtual buildings (linking student accommodation and some core on-campus buildings and machines, as well as portable terminals) in which students have access to the latest ways of specifying, implementing, running, and analysing a wide range of types of systems of varying complexity, including interacting with pre-built re-usable environments modelling many different kinds of natural, engineered, and highly fanciful entities including mythical creatures in infinite-dimensional worlds, and virtual environments with hundreds of now extinct species at various stages of our history.
Of course the students are expected not merely to play with these pre-built systems, but to find out how they work, and also to modify, extend, or redesign them, always producing analytical reports on what they have done and why and what they have learnt.
I can't make out what sort of technology is used to underpin these systems but I find it curious that besides what seem to be electrical power lines going into these centres there also seem to be many tanks with different sorts of chemicals connected to them and they appear to need large specialised exhaust systems. One of them has a plaque: 'Homage to GC7'[*]. Others quote Turing "In the nervous system chemical phenomena are at least as important as electrical" [Turing 1950], or what he wrote to W.R. Ashby in 1946: "In working on the ACE I am more interested in the possibility of producing models of the actions of the brain than in the practical applications to computing."
Almost all the student work is collaborative, sometimes across universities or countries. Students get individually tailored automatically generated critical reports on their work from the systems they interact with, and this forms a major part of their assessment.
At various stages (about four times a year) students who deem themselves ready diverge into a host of teaching and research centres, many of them studying information processing systems of special kinds, some natural some artificial -- e.g. what used to be called biology, embryology, biochemistry, psychology, neuroscience, economics, sociology, anthropology, management science, internet studies, and various kinds of engineering -- some concerned with development of new kinds of physical or chemical materials or mechanisms (many of them bio-inspired), others with various kinds of virtual machines, but most with a mixture.
The students all continue throughout their studies to take classes taught by the General Theory (GT) departments which resulted from the merger around 2087 of mathematics and philosophy, in which much of the research and teaching is concerned with new conceptual frameworks and mathematical structures for understanding both systems found in nature and also complex newly designed artificial systems including the international Braindome and Evodome experiments, the latter in geostationary orbit above the equator, and of course the galaxynet system under construction in the largest international collaborative project in our history. I notice that a few universities have departments labelled 'Semantic Galaxynet Studies' (SGS).
Staff and students from all departments help to specify requirements for, and some also to design and implement, the learning support systems in the central learning buildings, which are frequently updated.
A high proportion of them seem to be using technology developed at a non-profitable Asian Corporation for Collaborative Open Technology (ACCOT), which for some reason has its headquarters in Devon.
A few of the old pioneering universities have monuments commemorating what used to be known as computer science and their role in helping to bring it into existence, before it metamorphosed (between about 2025 and 2075) into the much broader meta-discipline of IPS and computers became obsolete.
Most of the learned societies to which academics belong are special interest groups within the ISSCIPS (International Society for the Study and Creation of Information Processing Systems). There are some rebel sub-groups who try to preserve what used to be the British Psychological Society, The British Computer Society, The Institute of Physics, The Mind Association, and several others, but they are having to face up to the fact that their authority and status have diminished to the point that they are merely tolerated as quaint relics.
Oh dear --- it has started to get much more fuzzy. I seem to have almost
exhausted the machine for today. (It's an early prototype accidentally left
behind by some time-travellers on a sight-seeing trip from 2206 and it seems to
be getting more flaky each time I use it). Just before it shut down I just
managed to find a relic in the Birmingham University archives of a document
arising out of a CPHC meeting in January 2000 discussing the future of research
in CS in the UK
apparently last accessed on 27 Feb 2006.
What is Computer Science?
A short answer.
A longer answer.
What do computer scientists actually do?
A partial answer:
The numbers presented are staggering. I suspect it would have more impact on scientific readers if it included references to reputable sources for the numbers. I attended a lecture in Cambridge around 2008 by neuroscientist Seth Grant, on what was known about synapses. He concluded (to the horror of most AI colleagues at the meeting) that each synapse has computational power roughly equivalent to the internet. (Of course it was much smaller then than now - 2015).
Few people seem to have noticed that Alan Turing wrote, in his 1950 paper:
"In the nervous system chemical phenomena are at least as important as electrical"
'Computing machinery and intelligence', Mind, 59, 1950, pp. 433--460
Presumably by then he had already been working on "The Chemical Basis of Morphogenesis" published two years later, now apparently his most cited paper.
Reading that paper in 2011 led me to propose the Turing-inspired