“Memristor minds: The future of artificial intelligence”
July 8, 2009 29 Comments
Ever the guardian of my intellectual development, Norm sent me a link to a New Scientist article on memristors, today. I’d never heard of them, but the article was interesting for both good and bad reasons, so I thought I’d share my impressions.
Here’s a short summary: The memristor is apparently a “missing component” in electronics, hypothesized by Leon Chua in 1971, to sit alongside the well known resistor, capacitor and inductor, but at the time it was unknown as a physical device. In the early years of this century, Stan Williams developed a nanoscale device that he believed fit the bill. And then Max di Ventra, a physicist at UCSD, linked this work with some research on a slime mould, which showed that they are capable of “predicting” a future state in a periodic environmental change. He suggested that this is a biophysical equivalent to a memristor. The article then goes on to suggest that neural synapses work the same way, and so this must surely be the big missing insight that has prevented us from understanding the brain and creating artificial intelligence.
But the article troubles me for a couple of reasons and I can’t help thinking there’s a serious problem with the way physicists and mathematicians tend to think about biology. Firstly, here’s a quote from the article:
“To Chua, this all points to a home truth. Despite years of effort, attempts to build an electronic intelligence that can mimic the awesome power of a brain have seen little success. And that might be simply because we were lacking the crucial electronic components – memristors.”
Hmm… So exactly what years of effort would that be, then? VERY few people have ever attempted to “build an electronic intelligence”. We simply don’t do that – we use computers!
Sure, a computer is an electronic device, but the whole damned point of them is that they are machines that can emulate any other machine. So they can emulate memristors too. They don’t actually have to be MADE of them in order to do that – they simply simulate them in code, like they simulate everything else. And I’m sure I’ve many times written code that has a state memory like a memristor. I didn’t know there was a named physical device that works in the same way, and it’s very interesting that there is, because it might give us new analogies and insights. But if I needed something to behave like that I could have coded it any time I wanted to. It’s meaningless to say that we’ve been stuck because we lacked a new type of electronic component. Only a physicist would confuse hardware and software like that! It boggles my mind.
And then I’m a little perplexed about a missing electronic component we DO know about. Maybe someone can help me with this? Chua’s work apparently hypothesized the memristor as a fourth component to add the existing resistor, capacitor and inductor. But where’s the transistor? Isn’t that a fundamental component? It’s a resistor, after a fashion, but surely it’s a fundamental building block in its own right, because it has the ability to allow a voltage to modulate a current – without them almost no electronic circuits would do anything useful!
I hate to say it, but I wonder if that’s a comment on the minds of physicists, too? It’s the transistor (or vacuum tube) that makes the difference between a static circuit, for which the mathematics of physics works well, and a dynamic circuit, for which it doesn’t. The capacitor is a dynamic system too, but only for a moment and then it settles down into something nice and easy to write equations for. It’s only when you add transistors and their consequent ability to generate feedback that the system really starts to dance and sing, and then the equations stop being much use.
The real glaring insight that electronics gives us, in my not-always-terribly-humble opinion, is the realization that sometimes classical science has a bad habit of being obsessed with “quantities” and ignoring or even sometimes denying the existence of “qualities”. Two electronic systems might have precisely the same mass, complexity and constituent substances, for instance, but be wired up in a different arrangement, producing radically different results. The reductionism implicit in much of physics can’t “see” the difference between the two circuits – because it’s something purely qualitative, not quantitative.
It’s the same with the brain. The reason we don’t understand the brain has NOTHING of significance to do with some “missing component”. It has nothing to do with quantum uncertainty or any other reductionistic claptrap. The reason we don’t understand the brain is that we don’t understand the CIRCUIT. We don’t understand the system as a whole. Memories, thoughts, ideas and the Self are not properties of the brain’s components, they are properties of its organisation. It’s very hard to understand organisations – I could easily give you an electronic circuit diagram out of context and it might take you days or weeks to figure out how it works and exactly what it does. But you could know everything you need to know about the properties of its resistors, capacitors, inductors and transistors, and even it’s memristors. You could weigh it and measure it all you liked and it would tell you nothing. Organization is not amenable to understanding using the tools of classical Physics.
Life and mind are qualitiative constructs. Looking for some special elixir vitae is completely missing the point. The article is very interesting and I plan to look up more information. Memristors may well provide a useful analogy that gives us some hints and insights about localised properties of brains, and that may steer us towards making more sense of the circuitry of intelligence. However, to suggest that we’ve got it all wrong because we didn’t have the right component in our toolbox for making our “electronic brains” is just nonsense. Electronic components are the province of physics, but electronic design is not. Synapses may be the province of physics too, but biology is not. Biology is a branch of cybernetics, which has a very different mindset (or did until physicists took it over and turned it into information theory).
P.S. I sort of see why transistors are missing now – at the mathematical level of description of Chua’s work, I guess a transistor is just a resistor, because both of them convert between voltage and current. Time only really enters into the equations as an integral, and the deeply nonlinear consequences of the transistor don’t really apply when you consider it as a single isolated component. But that was my point – once you wire them up into circuits all of this is pretty much irrelevant. It’s circuits that matter for intelligence. Minds are emergent properties of organisations. Looking for a “magic” component is just a modern-day form of vitalism.