My columns for PC Pro magazine, posted here six months in arrears for copyright reasons
Monday, 24 August 2020
VIRTUALLY USELESS
THE NUCLEAR OPTION
Dick Pountain/ Idealog307/ 8th February 2020 14:49:23
Those horrific wild-fires in Australia may prove to be the tipping point that gets people to start taking the threat of climate change seriously. Perhaps IT isn’t, at the moment, the industry most responsible for CO₂ emissions, but that’s no reason for complacency. On the plus side IT can save fossil fuel usage, when people email or teleconference rather than travelling: on the minus side, the electrical power consumed by all the world’s social media data centres is very significant and growing (not to mention what’s scoffed up mining cryptocurrencies). IT, along with carbon-reducing measures like switching to electric vehicles, vastly increases the demand for electricity, and I’m not confident that all this demand can realistically be met by renewable solar, wind and tidal sources, which may have now become cheap enough but remain intermittent.
That means that either storage, or some alternative back-up source, is needed to smooth out supply. A gigantic increase in the capacity of battery technologies could bridge that gap, but nothing on a big enough scale looks likely (for reasons I’ve discussed in a previous column). For that reason, and unpopular though it may be, I believe we must keep some nuclear power. It doesn’t mean I admire the current generation of fission reactors, which became unpopular for very good reasons: the huge cost of building them; the huge problem of disposing of their waste; and worst of all, because we’ve realised that human beings just aren’t diligent enough to be put in charge of machines that fail so unsafely. There are other nuclear technologies though that don’t share these drawbacks, but haven’t yet been sufficiently researched to get into production.
For about 50 years I’ve been hopeful for nuclear fusion (and like all fusion fans have been perennially disappointed). However things now really are looking up, thanks to two new lines of research: self-stable magnetic confinement and alpha emission. The first dispenses with those big metal doughnuts and their superconducting external magnets, and replaces them with smoke-rings - rapidly spinning plasma vortices that generate their own confining magnet field. The second, pioneered by Californian company TAE Technologies, seeks to fuse ordinary hydrogen with boron to generate alpha particles (helium nuclei), instead of fusing deuterium and tritium to produce neutrons. Since alpha particles, unlike neutrons, are electrically charged, they can directly induce current in an external conductor without leaving the apparatus. Neutrons must be absorbed into an external fluid to generate heat, which then drives a turbine, but in the process they render the fabric of the whole reactor radio-active, which alpha does not.
The most promising future fission technology is the thorium reactor, in which fission takes place in a molten fluoride salt. Such reactors can be far smaller than uranium ones, small enough to be air-cooled, they produce almost no waste, and they fail safe because fission fizzles out rather than runs wild if anything goes wrong. Distributed widely as local power stations, they could replace the current big central behemoths. That they haven’t caught on is partly due to industry inertia, but also because they currently still need a small amount of uranium 233 as a neutron source, which gets recycled like a catalyst. But now a team of Russian researchers are proposing a hybrid reactor design in which a deuterium-tritium fusion plasma, far too small to generate power itself, is employed instead of uranium to generate the neutrons to drive thorium fission.
A third technology I find encouraging isn’t a power source, but might just revolutionise power transmission. The new field of ‘twistronics’ began in 2018 when an MIT team lead by Pablo Jarillo-Herrero announced a device consisting of two layers of graphene stacked one upon the other, which becomes superconducting if those layers are very slightly twisted to create a moirĂ© pattern between their regular grids of carbon atoms. When you rotate the top layer by exactly 1.1° from the one below, it seems that electrons travelling between the layers are slowed down sufficiently that they pair-up to form the superconducting ‘fluid’, and this happens at around 140°K, way warmer than liquid helium and around halfway to room temperature. Twisted graphene promises a new generation of tools for studying the basis of superconduction: you’ll be able to tweak a system’s properties more or less by turning a knob, rather than having to synthesise a whole new chemical. Such tools should help speed the search for the ultimate prize, a room-temperature superconductor. That’s what we need to pipe electricity generated by solar arrays erected in the world’s hot deserts into our population centres with almost no loss. Graphene itself is unlikely to be such a conductor, but it may be what helps to discover one.
[ Dick Pountain ain’t scared of no nucular radiashun]
TO A DIFFERENT DRUMMER
Dick Pountain/ Idealog 306/ January 6th 2020
My Christmas present to myself this year was a guitar, an Ibanez AS73 Artcore. This isn't meant to replace my vintage MIJ Strat but rather to complement it in a jazzier direction. 50-odd years ago I fell in love with blues, ragtime and country finger-picking, then slowly gravitated toward jazz via Jim Hall and Joe Pass, then to current Americana-fusionists like Bill Frisell, Charlie Hunter and Julian Lage (none of whom I'm anywhere near skillwise). It's a long time since I was in a band and I play mostly for amusement, but can't escape the fact that all those idols all work best in a trio format, with drums and bass. My rig does include Hofner violin bass, drum machine and looper pedal to record and replay accompaniments, and I have toyed with apps like Band-in-a-Box, or playing along to Spotify tracks, but find none of these really satisfactory -- too rigid, no feedback. Well, I've mentioned before in this column my project to create human-sounding music by wholly programmatic means. The latest version, which I've named 'Algorhythmics', is written in Python and is getting pretty powerful. I wonder, could I use it to write myself a robot trio?
Algorhythmics starts out using native MIDI format, by treating pitch, time, duration and volume data as four seperate streams, each represented by a list of ASCII characters. In raw form this data just sounds like a hellish digital musical-box, and the challenge is to devise algorithms that inject structure, texture, variation and expression. I've had to employ five levels of quasi-random variation to achieve something that sounds remotely human. The first level composes the data lists themselves by manipulating, duplicating, reversing, reflecting and seeding with randomness. The second level employs two variables I call 'arp' (for arpeggio) and 'exp' (for expression) that alter the way notes from different MIDI tracks overlap to control legato and staccato. A third level produces tune structure by writing functions called 'motifs' to encapsulate short tune fragments, which can then be assembled like Lego blocks into bigger tunes with noticeably repeating themes. Motifs alone aren't enough though: if you stare at wallpaper with a seemingly random pattern, you'll invariably notice where it starts to repeat, and the ear has this same ability to spot (and become bored by) literal repetition. Level four has a function called 'vary' that subtly alters the motifs inside a loop at each pass, and applies tables of chord/scale relations (gleaned from online jazz tutorials and a book on Bartok's composing methods) to harmonise the fragments. Level five is the outer loop that generates the MIDI output, in which blocks of motifs are switched on and off under algorithmic control, like genes being expressed in a string of DNA.
So my robot jazz trio is a Python program called TriBot that generates improvised MIDI accompaniments -- for Acoustic Bass and General MIDI drum kit -- and plays them into my Marshall amplifier. The third player is of course me, plugged in on guitar. The General MIDI drum kit feels a bit too sparse, so I introduced an extra drum track using ethnic instruments like Woodblock, Taiko Drum and Melodic Tom. Tribot lets me choose tempo, key, and scale (major, minor, bop, blues, chromatic, various modes) through an Android menu interface, and my two robot colleagues will improvise away until halted. QPython lets me save new Tribot versions as clickable Android apps, so I can fiddle with its internal works as ongoing research.
It's still only a partial solution, because although drummer and bass player 'listen' to one another -- they have access to the same pitch and rhythm data -- they can't 'hear' me and I can only follow them. In one sense this is fair enough as it's what I'd experience playing alongside much better live musicians. At brisk tempos Tribot sounds like a Weather Report tribute band on crystal meth, which makes for a good workout. But my ideal would be what Bill Frisell described in this 1996 interview with a Japanese magazine (https://youtu.be/tKn5VeLAz4Y, at 47:27), a trio that improvise all together, leaving 'space' for each other. That's possible in theory, using a MIDI guitar like a Parker or a MIDI pickup for my Artcore. I'd need to make Tribot work in real-time -- it currently saves MIDI to an intermediate file -- then merge in my guitar's output translated back into Algorhythmic data format, so drummer and bass could 'hear' me too and adjust their playing to fit. A final magnificent fantasy would be to extend TriBot so it controlled an animated video of cartoon musicians. I won't have sufficient steam left to do either, maybe I'll learn more just trying to keep up with my robots...
[ Dick Pountain recommends you watch this 5 minute video, https://youtu.be/t-ReVx3QttA, before reading this column ]
FIRST CATCH YOUR GOAT
A QUANTUM OF SOLACE?
Dick Pountain/ Idealog304/ 3rd Nov 2019
When Google announced, on Oct 24th, that it has achieved 'quantum supremacy' -- that is, has performed a calculation on a quantum computer faster than any conventional computer could ever do -- I was forcefully reminded that quantum computing is a subject I've been avoiding in this column for 25 years. That prompted a further realisation that it's because I'm sceptical of the claims that have been made. I should hasten to add that I'm not sceptical about quantum mechanics per se (though I do veer closer to Einstein than to Bohr, am more impressed by Carver Mead's Collective Electrodynamics than by Copenhagen, and find 'many worlds' frankly ludicrous). Nor am I sceptical of the theory of quantum computation itself, though the last time I wrote about it was in Byte in 1997. No, what I'm sceptical of are the pragmatic engineering prospects for its timely implementation.
The last 60 years saw our world transformed by a new industrial revolution in electronics, gifting us the internet, the smartphone, Google searches and Wikipedia, Alexa and Oyster cards. The pace of that revolution was never uniform but accelerated to a fantastic extent from the early 1960s thanks to the invention of CMOS, the Complementary Metal-Oxide-Semiconductor fabrication process. CMOS had a property shared by few other technologies, namely that it became much, much cheaper and faster the smaller you made it, resulting in 'Moore's Law', that doubling of power and halving of cost every two years that's only now showing any sign of levelling off. That's how you got a smartphone as powerful as a '90s supercomputer in your pocket. CMOS is a solid-state process where electrons whizz around metal tracks deposited on treated silicon, which makes it amenable to easy duplication by what amounts to a form of printing.
You'll have seen pictures of Google's Sycamore quantum computer that may have achieved 'supremacy' (though IBM is disputing it). It looks more like a microbrewery than a computer. Its 56 quantum bits are indeed solid state, but they're superconductors that work at microwave frequencies and near absolute zero immersed in liquid helium. The quantum superpositions upon which computation depends collapse at higher temperatures and in the presence of radio noise, and there's no prospect that such an implementation could ever achieve the benign scaling properties of CMOS. Admittedly a single qubit can in theory do the work of millions of CMOS bits, but the algorithms that need to be devised to exploit that advantage are non-intuitive and opaque, the results of computation are difficult to extract correctly and will require novel error-correction techniques that are as yet unknown and may not exist. It's not years but decades, or more, from practicality.
Given this enormous difficulty, why is so much investment going into quantum computing right now? Thanks to two classes of problem that are provenly intractable on conventional computers, but of great interest to extremely wealthy sponsors. The first is the cracking of public-key encryption, a high priority for the world's intelligence agencies which therefore receives defence funds. The second is the protein-folding problem in biochemistry. Chains of hundreds of amino-acids that constitute enzymes can fold and link to themselves in a myriad different ways, only one of which will produce the proper behaviour of that enzyme, and that behaviour is the target for synthetic drugs. Big Pharma would love a quantum computer that could simulate such folding in real time, like a CAD/CAM system for designing monoclonal antibodies.
What worries me is that the hype surrounding quantum computing is of just the sort that's guaranteed to bewitch technologically-illerate politicians, and it may be resulting in poor allocation of computer science funding. The protein folding problem is an extreme example of the class of optimisation problems -- others are involved in banking, transport routing, storage allocation, product pricing and so on -- all of which are of enormous commercial importance and have been subject to much research effort. For example twenty years ago constraint solving was one very promising line of study. When faced with an intractably large number of possibilities, apply and propagate constraints to severely prune the tree of possibilities rather than trying to traverse it all. The promise of quantum computers is precisely that, assuming you could assemble enough qubits, they could indeed just test all the branches, thanks to superposition. In recent years the flow of constraint satisfaction papers seems to have dwindled: is this because the field has struck an actual impass, or because the chimera of imminent quantum computers is diverting effort? Perhaps a hybrid approach to these sorts of problem might be more productive, say hardware assistance for constraint solving, plus deep learning, plus analog architectures, and anticipating shared quantum servers as one, fairly distant, prospect rather than the only bet.
THE SKINNER BOX
Dick Pountain/ Idealog 303/ 4th October 2019 10:27:48
We live in paranoid times, and at least part of that paranoia is being provoked by advances in technology. New techniques of surveillance and prediction cut two ways: they can be used to prevent crime and to predict illness, but they can also be abused for social control and political repression – which of these one sees as more important is becoming a matter of high controversy. Those recent street demonstrations in Hong Kong highlighted the way that sophisticated facial recognition tech, when combined with CCTV built into special lamp-posts can enable a state to track and arrest individuals at will.
But the potential problems go way further than this, which is merely an extension of current law-enforcement technology. Huge advances in AI and Deep Learning are making it possible to refine thise more subtle means of social control often referred to as ‘nudging’. To nudge means getting people to do what you want them to do, or what is deemed good for them, not by direct coercion but by clever choice of defaults that exploit people’s natural biases and laziness (both of which we understand better than ever before thanks to the ground-breaking psychological research of Daniel Kahneman and Amos Tversky).
The arguments for and against nudging involve some subtle philosophical principles, which I’ll try to explain as painlessly as possible. Getting people to do “what’s good for them” raises several questions: who decides what’s good; is their decision correct; even if it is, do we have the right to impose it, what about free will? Liberal democracy (which is what we still do just about have, certainly compared to Russia or China) depends upon citizens being capable of making free decisions about matters important to the conduct of their own lives, but what if advertising, or addiction, or those intrinsic defects of human reasoning that Kahneman uncovered, so distort their reckoning as to make them no longer meaningfully free – what if they’re behaving in ways contrary to their own expressed interests and injurious to their health? Examples of such behaviours, and the success with which we’ve dealt with them, might be compulsory seat belts in cars (success), crash helmets for motorcyclists (success), smoking bans (partial success), US gun control (total failure).
Such control is called “paternalism”, and some degree of it is necessary to the operation of the state in complex modern societies, wherever the stakes are sufficiently high (as with smoking) and the costs of imposition, in both money and offended freedom, are sufficiently low. However there are libertarian critics who reject any sort of paternalism at all, while an in-between position, "libertarian paternalism", claims that the state has no right to impose but may only nudge people toward correct decisions, for example over opting-in versus opting-out of various kinds of agreement – mobile phone contracts, warranties, mortgages, privacy agreements. People are lazy and will usually go with the default option, careful choice of which can nudge rather than compel them to the desired decision.
The thing is, advances in AI are already enormously amplifying the opportunities for nudging, to a paranoia-inducing degree. The nastiest thing I saw at the recent AI conference in King’s Cross was an app that reads shoppers’ emotional states using facial analysis and then
raises or lowers the price of items offered to them on-the-fly! Or how about Ctrl-Lab’s app that non-invasively reads your intention to move a cursor (last week Facebook bought the firm). Since vocal chords are muscles too, that non-invasive approach might conceivably be extended with even deeper learning to predict your speech intentions, the voice in your head, your thoughts…
I avoid both extremes in such arguments about paternalism. I do believe that climate crisis is real and that we’ll need to modify human behaviour a lot in order to survive, so any help will be useful. On the other hand I was once an editor at Oz magazine and something of a libertarian rebel-rouser in the ‘60s. In a recent Guardian interview, the acerbic comedy writer Chris Morris (‘Brass Eye’, ‘Four Lions’) described meeting an AA man who showed him the monitoring kit in his van that recorded his driving habits. Morris asked “Isn’t that creepy?” but the man replied “Not really. My daughter’s just passed her driving test and I’ve got half-price insurance for her. A black box recorder in her car and camera on the dashboard measures exactly how she drives and her facial movements. As long as she stays within the parameters set by the insurance company, her premium stays low.” This sort of super-nudge comes uncomfortably close to China’s punitive Social Credit system: Morris called it a “Skinner Box”, after the American behaviourist BF Skinner who used one to condition his rats…
TURNING THE AIR BLUE
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