How AlphaGo Illustrates the “Warm Bath And Ice Bucket” View of Technology ProgressReading Time: 4 minutes
Remember the last time you took a bath or shower and it started lukewarm but you gradually warmed it by adding more hot water, until it reached a temperature so hot you could never have got into it at the start? Isn’t it strange how we can be immune to subtle, slow changes all around us?
Then there’s the other extreme – the ice bucket experience, where you’re abruptly plunged into something so dramatically different you can’t think of anything else.
The warm bath and the ice bucket: that’s how technology progresses, too.
As an example of the warm bath, you could point to the improvements in computing power in PCs and smartphones. Every year, they’re faster. You don’t notice how much better until you have to use an old device. (Or, of course, upgrade from a years-old device to a brand new one. These days, the effect is less visible on PCs than smartphones.)
Warm enough yet?
Another, less familiar, example is the burgeoning field of artificial intelligence (also known as machine learning, deep learning, neural networks, expert systems and so on). AI has been the “next big thing” for decades; the burden of expectation was so great it couldn’t meet them. Where, in the year 2001, was HAL, the talking sentient computer from 1968’s film 2001?
And yet, bit by bit, AI has been improving. I realised something was going on two years ago when I wrote a story about an app called Jetpac which could examine Instagram photos and determine whether the people in it were happy, grumpy, and so on.
To do that, Jetpac analysed 100 million photos and was able to determine whether those in it were wearing lipstick (so must be “glammed up”), had moustaches, etc.
A fun story, but it was the underlying technology, which Pete Warden, then CTO at Jetpac, explained to me that made me realise AI was back on the agenda again. He had used a neural network (which mimics, in machine form, the way neurons in the brain work: certain stimuli are reinforced, others are de-emphasised, in a learning process) to do the analysis.
It wasn’t surprising when eight months later Google bought Jetpac. The fit with Google’s broader AI drive was so obvious.
Where’s that tech now? Almost certainly powering the recognition system in Google Photos. Isn’t the Photos recognition system clever? But equally, isn’t it so obviously a progression from the face recognition we’ve seen in apps for years? The temperature is rising.
In fact, the AI temperature is now so high that this week we may witness a key event: a machine winning against a human at one of the subtlest board games ever. AlphaGo, an AI program developed at Google’s Deepmind in London, learned how to play the Chinese game Go at a professional level – and then beat Europe’s best player 5-0. On Wednesday – Tuesday night in the US – AlphaGo takes on Lee Sedol, the game’s top player. (If you haven’t played Go (most people in the West haven’t) let me put it like this: it makes chess look crowded and trivial: the board has four times more points than a chessboard, and the number of possible moves is far, far larger.)
AlphaGo isn’t like Deep Blue; it isn’t programmed just to play Go. Instead, it has a “learning” system which was tuned to play Go by working through millions of games and learning what outcomes were best. It could probably learn to win at chess. The core program learned to play video games.
This is the warming bath: how did we get to the point where computers could learn to beat the best player in the world at a game where intuition and “feel” are seen as essential?
The ice bucket
By contrast, some technologies are ice baths – so dramatically different from what has gone before they upend our expectations. Virtual reality (VR) fits this well. Immersive VR is an utterly different experience from what has gone before and the potential for creating new ways of interacting are what have so many people excited about it.
To people who haven’t tried it, VR tends to be “that thing where you wear the stupid helmet”. But that’s because they haven’t experienced the ice bucket. In the past, trains were a similarly disjunctive experience, able to travel at absurd speeds. There were even fears that the velocity would make passengers’ bodies fly apart.
Are there other “ice bucket” technology examples? The original iPhone was a shock to pretty much everyone, even though the technologies it contained (notably the multi-touch screen) were already known. From January 2007, Google’s Android team sidelined their work on a BlackBerry-like device and focussed instead on a multi-touch product.
Your preference doesn’t matter
Ice buckets change the game abruptly; warm baths surround us and raise the temperature so we can’t imagine life before them. There’s no way to pick which is “better” – and we don’t get to pick anyway, because they happen quite independently of our wishes or expectations. But in truth, there are more warm baths than ice buckets. The gradual improvement of smartphone screens, battery life, chip speeds, mobile reception, mobile speeds, design improvements – they’re all slow improvements which you don’t notice until you don’t have them. For dramatic change, though, the ice bucket beats the lot.
Moment of truth
There’s an instant as you first experience a splash of water when you don’t know whether it’s hot or cold. The match between Lee Sedol and AlphaGo could be like that: an odd mixture of hot and cold, a “where were you when…?” moment. Garry Kasparov’s loss to Deep Blue in 1997 was an iconic moment, remembered by many. It has taken nearly 20 years for a computer program to be able to challenge the top human in Go, which tells you about the gap in complexity between the two games. Fewer people understand Go than chess; but everyone understands winning and losing. Computing’s advance is bringing us a moment when the ice bucket comes from a warm bath.
• The first match between AlphaGo and Lee Sedol starts at 1pm Seoul time on Wednesday (4am GMT Wednesday, 11pm EST Tuesday, 8pm PST Tuesday). The match will last up to four hours. It can be viewed on Youtube; there will be commentary (which might not mean much to non-Go players) at Gogame.