Learning jazz improvisation

A few days ago, writing about bank bonuses, I talked about the skills needed to get-things-done, a form of intelligence I believe is distinct (and rarer than) other, better-known forms — mathematical, linguistic, emotional, etc. There are in fact many skill sets and forms of intelligence which don’t feature prominently in our text-biased culture. One of these is musical intelligence, and I have come across a fascinating description of taking jazz improvisation and composition lessons from pianist and composer Hall Overton (1920-1972), written by Jack Reilly (1932-2018):

The cigarette dangled out the right side of his mouth, the smoke rising causing his left eye to squint, the ashes from the burning bush got longer and longer, poised precipitously to fall at any moment on the keyboard. Hall always sat at the upright piano smoking, all the while playing, correcting, and making comments on my new assighment, exercises in two-part modern counterpoint. I was perched on a rickety chair to his left, listening intensely to his brilliant exegesis, waiting in vain for the inch-long+ cigarette ash to fall. The ashes never fell! Hall instinctively knew the precise moment to stop playing , take the butt out of his mouth and flick the ashes in the tray on the upright piano to his left. He would then throw the butt in the ash tray and immediately light another cigarette. His concentration and attention to every detail of my assighment made him unaware that he never took a serious puff on the bloody cigarette. I think the cigarette was his “prop” so to speak, his way of creating obstacles that tested my concentration on what he was saying. In other words, Hall was indirectly teaching me to block out any external distractions when doing my music, even when faced with a comedic situation like wondering when the cigarette ashhes would fall on the upright keyboard or even on his tie. Yes, Hall wore a tie, and a shirt and a jacket. All memories of Hall Overton by his former students 9 times out ot 10 begin with the Ashes to Ashes situation. A champion chain smoker and indeed, a master ash flickerer, never once dirtying the floor, piano or his professorial attire.

Hall Overton, composer, jazz pianist, advocate/activist for the New Music of his time and a lover of Theolonius Monk’s music, was my teacher for one year beginning in 1957. I first heard about him from a fellow classmate at the Manhattan School of Music, which at that time was located on East 103rd street, between 2nd and 3rd avenue, an area then known as Spanish Harlem. This chap was playing in one of the basement practice rooms where I heard him playing Duke Jordan’s “Jordu”. I liked what I heard so much so I asked him where he learned to play that way. Hall Overton, was his reply. I took down Hall’s number, called him and said I wanted to take jazz piano lessons. He sounded warm and gracious over the phone which made me feel relaxed because I was nervous about playing for him. I had been playing jazz gigs and casuals since my teens but still felt light years away from my vision of myself as a complete jazz pianist. Hall was going to push the envelope. We set up weekly lessons.
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Computer Science, love-child

With the history and pioneers of computing in the British news this week, I’ve been thinking about a common misconception:  many people regard computer science as very closely related to Mathematics, perhaps even a sub-branch of Mathematics.  Mathematicians and physical scientists, who often know little and that little often outdated about modern computer science and software engineering, are among the worst offenders here.  For some reason, they often think that computer science consists of Fortran programming and the study of algorithms, which has been a long way from the truth for, oh, the last few decades.  (I have past personal experience of the online vitriol which ignorant pure mathematicians can unleash on those who dare to suggest that computer science might involve the application of ideas from philosophy, economics, sociology or ecology.) 
So here’s my story:  Computer Science is the love-child of Pure Mathematics and Philosophy
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Alan Turing

Yesterday, I reported on the restoration of the world’s oldest, still-working modern computer.  Last night, British Prime Minister Gordon Brown apologized for the country’s treatment of Alan Turing, computer pioneer.  In the words of Brown’s statement:

Turing was a quite brilliant mathematician, most famous for his work on breaking the German Enigma codes. It is no exaggeration to say that, without his outstanding contribution, the history of World War Two could well have been very different. He truly was one of those individuals we can point to whose unique contribution helped to turn the tide of war. The debt of gratitude he is owed makes it all the more horrifying, therefore, that he was treated so inhumanely. In 1952, he was convicted of ‘gross indecency’ – in effect, tried for being gay. His sentence – and he was faced with the miserable choice of this or prison – was chemical castration by a series of injections of female hormones. He took his own life just two years later.”

It might be considered that this apology required no courage of Brown.

This is not the case.  Until very recently, and perhaps still today, there were people who disparaged and belittled Turing’s contribution to computer science and computer engineering.  The conventional academic wisdom is that he was only good at the abstract theory and at the formal mathematizing (as in his “schoolboy essay” proposing a test to distinguish human from machine interlocuters), and not good for anything practical.   This belief is false.  As the philosopher and historian  B. Jack Copeland has shown, Turing was actively and intimately involved in the design and construction work (mechanical & electrical) of creating the machines developed at Bletchley Park during WWII, the computing machines which enabled Britain to crack the communications codes used by the Germans.

Turing-2004-Poster

Perhaps, like myself, you imagine this revision to conventional wisdom would be uncontroversial.  Sadly, not.  On 5 June 2004, I attended a symposium in Cottonopolis to commemorate the 50th anniversary of Turing’s death.  At this symposium, Copeland played a recording of an oral-history interview with engineer Tom Kilburn (1921-2001), first head of the first Department of Computer Science in Britain (at the University of Manchester), and also one of the pioneers of modern computing.   Kilburn and Turing had worked together in Manchester after WW II.  The audience heard Kilburn stress to his interviewer that what he learnt from Turing about the design and creation of computers was all high-level (ie, abstract) and not very much, indeed only about 30 minutes worth of conversation.  Copeland then produced evidence (from signing-in books) that Kilburn had attended a restricted, invitation-only, multi-week, full-time course on the design and engineering of computers which Turing had presented at the National Physical Laboratories shortly after the end of WW II, a course organized by the British Ministry of Defence to share some of the learnings of the Bletchley Park people in designing, building and operating computers.   If Turing had so little of practical relevance to contribute to Kilburn’s work, why then, one wonders, would Kilburn have turned up each day to his course.

That these issues were still fresh in the minds of some people was shown by the Q&A session at the end of Copeland’s presentation.  Several elderly members of the audience, clearly supporters of Kilburn, took strident and emotive issue with Copeland’s argument, with one of them even claiming that Turing had contributed nothing to the development of computing.   I repeat: this took place in Manchester 50 years after Turing’s death!    Clearly there were people who did not like Turing, or in some way had been offended by him, and who were still extremely upset about it half a century later.  They were still trying to belittle his contribution and his practical skills, despite the factual evidence to the contrary.

I applaud Gordon Brown’s courage in officially apologizing to Alan Turing, an apology which at least ensures the historical record is set straight for what our modern society owes this man.

POSTSCRIPT #1 (2009-10-01): The year 2012 will be a centenary year of celebration of Alan Turing.

POSTSCRIPT #2 (2011-11-18):  It should also be noted, concerning Mr Brown’s statement, that Turing died from eating an apple laced with cyanide.  He was apparently in the habit of eating an apple each day.   These two facts are not, by themselves, sufficient evidence to support a claim that he took his own life.

POSTSCRIPT #3 (2013-02-15):  I am not the only person to have questioned the coroner’s official verdict that Turing committed suicide.    The BBC reports that Jack Copeland notes that the police never actually tested the apple found beside Turing’s body for traces of cyanide, so it is quite possible it had no traces.     The possibility remains that he died from an accidental inhalation of cyanide or that he was deliberately poisoned.   Given the evidence, the only rational verdict is an open one.

Obama the policy-wonk

Andrew Sprung, over at XPOSTFACTOID, has a powerful deconstruction of the myth that Barack Obama does not do detail.   Of course he does, as has been evident – from the start of his Presidential campaign 33 months ago – to anyone who actually listens to what he says.  Why has the myth persisted?  Partly, I think it is laziness:  it is easier to repeat a cliche than to listen and think for oneself. Partly, I think it is right-wing spin:  his enemies think they can paint him as an airhead, as some tried to paint Tony Blair (remember “Bambi”?).

Switch WITCH

The Guardian today carries a story about an effort at the UK National Musem of Computing at Bletchley Park to install and restore the world’s oldest working modern electric computer, the Harwell Dekatron Computer (aka the WITCH, pictured here), built originally for the UK Atomic Energy Research Establishment at Harwell in 1951.  The restoration is being done by UK Computer Conservation Society.
Note:  The Guardian claims this to be the world’s oldest working computer.  I am sure there are older “computers” still working elsewhere, if we assume a computer is a programmable device.  At late as 1985, in Harare, I saw at work in factories programmable textile and brush-making machinery which had been built in Britain more than a century earlier.
WITCH Computer

“One of the things that attracted us to the project was that it was built from standard off-the-shelf Post Office components, of which we have a stock built up for Colossus,” says Frazer. “And we have some former Post Office engineers who can do that sort of wiring.”
Frazer says he can imagine the machine’s three designers – Ted Cooke-Yarborough, Dick Barnes and Gurney Thomas – going to the stores with a list and saying: “We’d like these to build a computer, please.”
Dick Barnes, now a sprightly 88, says: “We had to build [the machine] from our existing resources or we might not have been allowed to build it at all. The relay controls came about because that was my background: during the war I had produced single-purpose calculating devices using relays. We knew it wasn’t going to be a fast computer, but it was designed to fulfil a real need at a time when the sole computing resources were hand-turned desk calculators.”

Bonuses yet again

Alex Goodall, over at A Swift Blow to the Head, has written another angry post about the bonuses paid to financial sector staff. I’ve been in several minds about responding, since my views seem to be decidedly minority ones in our present environment, and because there seems to be so much anger abroad on this topic.  But so much that is written and said, including by intelligent, reasonable people such as Alex, mis-understands the topic, that I feel a response is again needed.  It behooves none of us to make policy on the basis of anger and ignorance.
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Computing-as-interaction

In its brief history, computer science has enjoyed several different metaphors for the notion of computation.  From the time of Charles Babbage in the nineteenth century until the mid-1960s, most people thought of computation as calculation, or the manipulation of numbers.  Indeed, the English word “computer” was originally used to describe a person undertaking arithmetical calculations.  With widespread digital storage and processing of non-numerical information from the 1960s onwards, computation was re-conceptualized more generally as information processing, or the manipulation of numerical-, text-, audio- or video-data.  This metaphor is probably still the prevailing view among people who are not computer scientists.  From the late 1970s, with the development of various forms of machine intelligence, such as expert systems, a yet more general metaphor of computation as cognition, or the manipulation of ideas, became widespread, at least among computer scientists.  The fruits of this metaphor have been realized, for example, in the advanced artificial intelligence technologies which have now been a standard part of desktop computer operating systems since the mid-1990s.  Windows95, for example, included a Bayesnet for automated diagnosis of printer faults.
With the growth of the Internet and the Web over the last two decades, we have reached a position where a new metaphor for computation is required:  computation as interaction, or the joint manipulation of ideas and actions. In this metaphor, computation is something which happens by and through the communications which computational entities have with one another.  Cognition and intelligent behaviour is not something which a computer does on its own, or not merely that, but is something which arises through its interactions with other intelligent computers to which is connected.  The network is the computer, in SUN’s famous phrase.  This viewpoint is a radical reconceptualization of the notion of computation.
coveral3roadmap
In this new metaphor, computation is an activity which is inherently social, rather than solitary, and this view leads to a new ways of conceiving, designing, developing and managing computational systems.  One example of the influence of this viewpoint, is the model of software as a service, for example in Service Oriented Architectures.  In this model, applications are no longer “compiled together” in order to function on one machine (single user applications), or distributed applications managed by a single organization (such as most of today’s Intranet applications), but instead are societies of components:

  • These components are viewed as providing services to one another rather than being compiled together.  They may not all have been designed together or even by the same software development team; they may be created, operate and de-commissioned according to different timescales; they may enter and leave different societies at different times and for different reasons; and they may form coalitions or virtual organizations with one another to achieve particular temporary objectives.  Examples are automated procurement systems comprising all the companies connected along a supply chain, or service creation and service delivery platforms for dynamic provision of value-added telecommunications services.
  • The components and their services may be owned and managed by different organizations, and thus have access to different information sources, have different objectives, have conflicting preferences, and be subject to different policies or regulations regarding information collection, storage and dissemination.  Health care management systems spanning multiple hospitals or automated resource allocation systems, such as Grid systems, are examples here.
  • The components are not necessarily activated by human users but may also carry out actions in an automated and co-ordinated manner when certain conditions hold true.  These pre-conditions may themselves be distributed across components, so that action by one component requires prior co-ordination and agreement with other components.  Simple multi-party database commit protocols are examples of this, but significantly more complex co-ordination and negotiation protocols have been studied and deployed, for example in utility computing systems and in ad hoc wireless networks.
  • Intelligent, automated components may even undertake self-assembly of software and systems, to enable adaptation or response to changing external or internal circumstances.  An example is the creation of on-the-fly coalitions in automated supply-chain systems in order to exploit dynamic commercial opportunities.  Such systems resemble those of the natural world and human societies much more than they do the example arithmetical calculations  programs typically taught in Fortran classes, and so ideas from biology, ecology, statistical physics, sociology, and economics play an increasingly important role in computer science.

How should we exploit this new metaphor of computation as a social activity, as interaction between intelligent and independent entities, adapting and co-evolving with one another?  The answer, many people believe, lies with agent technologies.  An agent is a computer programme capable of flexible and autonomous action in a dynamic environment, usually an environment containing other agents.  In this abstraction, we have software entities called agents, encapsulated, autonomous and intelligent, and we have demarcated the society in which they operate, a multi-agent system.  Agent-based computing concerns the theoretical and practical working through of the details of this simple two-level abstraction.
Reference:
Text edited slightly from the Executive Summary of:
M. Luck, P. McBurney, S. Willmott and O. Shehory [2005]: The AgentLink III Agent Technology Roadmap. AgentLink III, the European Co-ordination Action for Agent-Based Computing, Southampton, UK.

Social forecasting: Doppio Software

Five years ago, back in the antediluvian era of Web 2.0 (the web as enabler and facilitator of social networks), we had the idea of  social-network forecasting.  We developed a product to enable a group of people to share and aggregate their forecasts of something, via the web.  Because reducing greenhouse gases were also becoming flavour-du-jour, we applied these ideas to social forecasts of the price for the European Union’s carbon emission permits, in a nifty product we called Prophets-360.  Sadly, due mainly to poor regulatory design of the European carbon emission market, supply greatly outstripped demand for emissions permits, and the price of permits fell quickly and has mostly stayed fallen.  A flat curve is not difficult to predict, and certainly there was little value in comparing one person’s forecast with that of another.  Our venture was also felled.

But now the second generation of social networking forecasting tools has arrived.  I see that a French start-up, Doppio Software, has recently launched publicly.   They appear to have a product which has several advantages over ours:

  • Doppio Software is focused on forecasting demand along a supply chain.  This means the forecasting objective is very tactical, not the long-term strategic forecasting that CO2 emission permit prices became.   In the present economic climate, short-term tactical success is certainly more compelling to business customers than even looking five years hence.
  • The relevant social network for a supply chain is a much stronger community of interest than the amorphous groups we had in mind for Prophets-360.  Firstly, this community already exists (for each chain), and does not need to be created.  Secondly, the members of the community by definition have differential access to information, on the basis of their different positions up and down the chain.  Thirdly, although the interests of the partners in a supply chain are not identical, these interests are mutually-reinforcing:  everyone in the chain benefits if the chain itself is more successful at forecasting throughput.
  • In addition, Team Doppio (the Doppiogangers?) appear to have included a very compelling value-add:  their own automated modeling of causal relationships between the target demand variables of each client and general macro-economic variables, using  semantic-web data and qualitative modeling technologies from AI.  Only the largest manufacturing companies can afford their own econometricians, and such people will normally only be able to hand-craft models for the most important variables.  There are few companies IMO who would not benefit from Doppio’s offer here.

Of course, I’ve not seen the Doppio interface and a lot will hinge on its ease-of-use (as with all software aimed at business users).  But this offer appears to be very sophisticated, well-crafted and compelling, combining social network forecasting, intelligent causal modeling and semantic web technologies.

Well done, Team Doppio!  I wish you every success with this product!

PS:  I have just learnt that “doppio” means “double”, which makes it a very apposite name for this application – forecasts considered by many people, across their human network.  Neat!  (2009-09-16)

Article in The Observer (UK) about Doppio 2009-09-06 here. And here is an AFP TV news story (2009-09-15) about Doppio co-founder, Edouard d’Archimbaud.  Another co-founder is Benjamin Haycraft.