Tag: Philosophy

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Cosmography Technology

A Ball Of Blue Flame

English: 42, The Answer to the Ultimate Questi...

I didn’t speak before now about my last exam. The thing is, I’m really not sure how I did.

It felt good. I left the exam hall exhausted, elated, as if I’d given my all.

I just wish I could be sure that my all is the all they wanted.

I have no complaints about the paper. Couldn’t really have been better from my point of view. I was able to avoid the cost analysis question I dearly wanted not to do. It wasn’t a hard one; basically it’s just a sum. The problem was those two words – “cost analysis”. I had to stay alert through a whole exam, and just looking at them makes my eyelids droop.

The systems theory question on the other hand was all too exciting. Yes, seriously. It involved concepts that have interested me for a long time. Visualising the world not as discrete objects but in terms of interacting systems, flows of activity and information. Emergent phenomena – how all the complexity and wonder of life arises out of apparently simple chemistry, or indeed solid matter out of ephemeral probability. The danger with this was that I could easily blow the entire two and a half hours if I got hooked on a wild-eyed Idea.

So I began with the case study question, which retrod a lot of ground we’d covered in our projects. This made it easier, but had the downside that my head was preloaded with too many things I could say. And I think I said too many of them, because I spent over an hour on that one.

Thankfully, next was what’s known as a decision table. These distil a complex decision-making process into a simple table you can look up. You might – as in the example – be a college book shop trying to decide whether to keep some old titles in stock or return them to the publisher. There are a bunch of factors involved, how do you decide? Well here the table shows that if, for example, an edition is no longer current. but has been requested by staff, then the correct response is to keep it. Simplicissimo.

Condition USER RULES
1 2 3 4 5 6 7 8 9 10
Edition Is Still Current N N N Y Y Y Y Y Y Y
Old Edition Requested By Academic Staff N N Y – – – – – – –
Any Copies Sold In Last 3 Months – – – N N Y Y Y Y Y
More Than 15% Of Stock Sold In Last 3 Months – – – – – N N Y Y Y
More Than 20% Of Stock Sold By Mid-Semester – – – – – – – Y N N
Sales Manager Believes Book Will Still Sell N Y – N Y N Y – N Y
Action
Return Remaining Stock X X X
Consider Returning 75% of Remaining Stock X
Keep Remaining Stock X X X X X X

Why is the table so small? Having six conditions, each with two possible values – Yes and No – you’d think it would need (2x2x2x2x2x2=) 64 columns instead of 10. The trick is that some conditions make others redundant. Look at what happens if the Sales Manager decides a book will still sell. Their word goes, making all other considerations moot. By examining the logic in this way you can reduce the table to its essentials.

The problem then is making sure you’ve done it right. Do the rules really cover all possible situations? Could two different, contradictory actions be invoked by the same set of conditions? That latter is particularly significant because tables like these form the basis of computer programs, and when a computer is stuck between two conflicting responses it explodes.

Possibly.

Examining a table for logical consistency sounds scary, but when you boil it down it’s a puzzle not unlike a Sudoku. Having practised, I’d got the knack of solving them visually. Well, simple ones… That saved time which by now I badly needed. I’d left myself barely more than half an hour for all the theory. Things were now officially intense.

So I don’t recall clearly what I wrote… I do know though that somehow I got stuck on aspects of systems theory that bug me. Couldn’t I write a happy answer about the many aspects that I think are cool and interesting? No, apparently I can’t do that.

Really it was one particular lecture slide I was hung up on. This had compared science to the systems approach, contrasting them as analytical versus holistic, qualitative versus quantitative, so on. In other words presenting the systems approach as a counterbalance, even an alternative, to science. That struck me as just wrong; overshooting the holistic and heading into homoeopathic country. Or “needlessly messianic”, as I described it. (Which incidentally was the second entirely pointless Hitch Hikers Guide to the Galaxy reference I found myself slipping into these exams.)

In particular it described science as “reductionist”, which to me is to misunderstand it completely. Sure, science takes things apart and examines the components. But it doesn’t do that to understand the components; rather the objective is to see how they all work together – as a system. As a whole.

Holism is right there in science. To claim otherwise is to traduce humanity’s most important philosophical tool for one’s own obscure – or obscurantist – motives.

OK I didn’t say that last sentence, thank God. I was having a bit of a head rush but I still knew better than to condemn the subject I was being examined in as an evil conspiracy. I’m not doing English lit any more. And I don’t think that of course. What I hope I managed to convey is that I find systems theory attractive, but at the same time worry that this very attractiveness may make it dangerous. Is it a useful way of looking at the world, or a friend to fuzzy thinking? Well, I’m not sure – but I want it to be useful.

Maybe my suspicions were refreshing, maybe I’ll be marked down for insufficient imbibing of the Kool-Aid. In short, yet again I am certain that I either (a) did a really good exam or (b) plunged off the cliff in a ball of blue flame. One or the other.

At least it’s not dull.

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Cosmography

When It’s Over

Human skin structure
Safety

Now that she’s gone, I have lost my reason. I don’t mean I’m mad. I’m angry and bitter, sure, but not unbalanced. I mean that when we were together, life made more sense. Don’t get me wrong, it wasn’t living my life for her. Heaven forfend. Nor “our future together”, or anything so cute. But I was part of something that was better than myself alone, something that transcended my limitations.

I hate to call it “the relationship”. It seemed far more concrete to me than such a vague term can convey, even if it existed only in our heads (only in mine?). What I’m talking about is an emotional reassurance. The knowledge that someone knew you very, very well – and yet somehow wanted to be with you anyway. The simple touch of human skin coming between you and the abyss. To cross the frontiers of that skin, escape the bonds of individuality, discover the relief of trust.

It wasn’t all security. No. It was challenge too. But that’s a good combination. When someone smart thinks you’re smart, expects the best of you, criticizes you cogently, it brings out your best. It didn’t change my life overnight, no. But over a year it informed every decision in a positive way. Why not do this? Why not set that goal? I felt both motivated and secure enough to look at the future again.

So now. When I think of doing something, the unexpected question comes. What for? Wasn’t there a reason once? The logic of my life escapes me for a moment. I don’t know why I’m doing anything. I survive, of course. And I know objectively that things will be better one day. But right now I feel betrayed, abandoned, imprisoned. Condemned to the oubliette of memory, the echo chamber of self. The walls close in.

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Cosmography Humour

Paddywackery – or, How Comics Changed My Life

The local shop I mentioned is a goldmine. Today I found that they sell a thing called paddywack. As a dog food. What the…?

It turns out the original meaning of “paddywack” is the large ligament that runs down the back of a grazing animal’s neck. The word is from the Old English paxwax, meaning something like “hair grow”. Because longer hair grows along the neck ridge of some animals, perhaps? By being highly elastic, this ligament makes it easier for the beast to raise its head. When dried, it makes a chewy treat for dogs.

So a whole other meaning for a word I thought of merely as a mild ethnic slur – that at least was my impression since childhood, when a strip of the same name in the British Comic Cheeky Weekly used to encourage readers to send in their Irish jokes. The whole comic indeed was packed with race and gender stereotype gags – and what’s worse, pointlessly awful puns. Such were the 1970s; vertiginous now to see that stuff again.

I didn’t find most of this funny even as a child. And yet, I liked the comic. It had a vivacity you didn’t see before, it messed with conventions and introduced elements of metafiction. Each issue had a single framing story, with characters commenting on the other strips, even moving in and out of them. And I guess it helped that it featured a sexy crossing guard called Lily Pop; I was getting to that sort of age. If Barry Cryer had written a kids’ comic – albeit on a bad day – it might have come out something like this.

Now that I look this stuff up I’m reminded that Cheeky Weekly had an even weirder progenitor, Krazy comic. I don’t think most of the strips in Krazy worked really. As the name suggests it was self-consciously way-out and wacky, and kids are quite sensitive to straining for effect. What compensated were the interstitial gags packed into it – comments between panels or as background graffiti, flick-book animations in corners. It was aiming I think to be something like a junior Mad magazine.

And I think this in turn may have been partly inspired by the comic that influenced me the most – Sparky. It was not an outstanding example perhaps, but it had one thing that really got me: the flat-out metafiction of a strip about the people who supposedly created the comic. They were in it… But making it… In it… The contradictions beguiled my mind. My own first comic strip, started I think while I was still 11, was pretty much a straight rip-off of this idea, and it must be at least partly responsible for a lifelong fascination with philosophical concepts like self-referentiality, recursion and nested realities. My mature (?) comic strip work rarely resisted opportunities to tell stories within stories – or indeed, stories within each other. My first long strip, which was also my degree dissertation, took place within a reality that only existed in the mind of God – but within which, God existed.

Come on, I was in college.

Well that turned into an unexpected ramble; from doggy treats to comic theology. It seems though that in the process I’ve accidentally written a response to this lovely blog post by Lisa “SwearyLady” McInerney. Yeah, comics were an important early influence in my life. For me it’s Gödel, Escher, Bach, and The Sparky People.

Categories
Cosmography Technology

This Is Your Brain On Screen

IBM has a really interesting – and just slightly scary – plan. In cooperation with Switzerland’s École Polytechnique Fédérale de Lausanne, they want to simulate the human brain.

They’re building a computer model. This is not the same thing as Artificial Intelligence (AI), programming a machine to act human. That would be a ‘top down’ approach; trying to understand how the mind works by looking at what it does. Instead this is ‘bottom up’, simulating the nuts and bolts of the brain, its biological wiring, its cells, even its molecules.

Which is quite an undertaking – in fact it is hard to exaggerate how big the task is. The brain is often described as the most complex thing in the known universe. Complexity is a thing that’s difficult to define but easy to perceive. Looking into the back of a TV, you’re instantly aware that it’s more complex than say a food mixer. Basically it looks more tricky to fix. The parts are small, numerous, and connected together in many different ways. Perhaps that’s the most intiuitive shorthand measure of complexity – the number of different ways that the parts of something interconnect. The human brain has far more connected parts than any other thing known, certainly more than any computer. Even Japan’s Earth Simulator, built to model the climate of the entire planet, is nothing compared to the brain of an average person.

It’s no surprise therefore that they aren’t trying to do the whole thing at once, or anything approaching that. They are starting with the best bit though: the neocortex (also called the cerebrum), the outside layer of the brain that’s most recent in evolutionary terms. It’s not unique to us, but it is far more developed in humans than in any other animal and appears to be responsible for what we experience as thought.

Even alone though, this is still far too complex for current technology to tackle. All they’re hoping to simulate right now is what’s known as a neocortical column. This can be described as a single ‘circuit’ of the brain, one of its processing units. The whole neocortex contains about a million of these. And for the moment at least, they only plan to model it on the level of its cells; to get down to the molecules that make up the cells will take vastly more computational power again. Yet even this is an immensely ambitious target. To model just one circuit of the brain in this (relatively) simple way will require four whole modules of Blue Gene – the technology IBM used to take the title of world’s fastest supercomputer back from the Earth Simulator.

So how far are we then from modelling the whole brain? Well assuming this first stage succeeds – it won’t be easy – all they really need to do is scale it up. Vastly. These four Blue Gene racks would fit in a normal kitchen. Four million? They would take up a golf course, and require the energy of five medium-sized power stations.

When you consider that your actual brain fits inside your head and runs reasonably well on sandwiches and cups of tea, you realise what a gap there is between nature’s technology and our own.

What’s the point then in going to all this trouble when a brain can be made much more cheaply using just two humans? If the object were to create machines that think, this would clearly be a madly inefficient way to go about it. But that’s not the object. The fact is we know amazingly little about how our own brains work. Simulating a part of one, even a solitary neocortical circuit, will teach us so much about what is really going on in there. Modelling allows you to find out why something is the way it is, because it can show you what would happen if it were different. The beneficial applications of that are obvious; as we see how it works, we gain greater insight into why it fails – what causes schizophrenia, Alzheimer’s, autism, the things that plague our minds.

But though it’s always good when research has palpable benefits, I think we need no  such excuse when it comes to researching the structure and function of the brain. To know ones own mind – that is surely a philosophical imperative.

(For more fun with human brains, see the comic strip)