Elon Musk, CEO of Tesla Motors, is creating cleaner, smarter cars but they can't yet take the place of humans behind the wheel. Picture / AP
Another Tesla has crashed because the driver thought its self-driving technology could actually drive the car. As we read all the stories about magical technology and then use the hyped-up products, we ought to keep in mind that the "magic" hits the market long before they live up to their promise, which in some cases they will never do. If it's new, don't expect it to work as advertised.
The Tesla in Beijing, in Autopilot mode, hit the side of an illegally parked car and kept going until driver Luo Zhen - who had taken his hands off the steering wheel - manually stopped it. The US$7500 ($10,420) repair bill was probably a tough way for Luo to learn that when he read and heard about self-driving cars, or even when he watched Tesla's Autopilot video (which tells drivers to grip the wheel at all times but shows the Model S changing lanes, taking curves and parking itself), he was essentially reading and watching sci-fi.

Nor was Microsoft really misleading customers about the ability of its Skype Translator to live-translate between Mandarin and English. It can do that when you speak slowly and clearly, avoiding complicated subjects and sentence structures, the way people do in the promotional videos.I'm not going to accuse Tesla of false advertising, as many did after Autopilot led to a fatal crash. The technology can do what the video shows it doing, but it can't do it in every situation, and that's why the automaker's warning about holding on to the wheel is clearly articulated.
But a Tesla cannot drive itself better than an experienced human driver can drive it. Skype Translator cannot really handle normal conversation the way even a middling simultaneous translator could. Nor can "big data" predict election outcomes or real-world economic phenomena better than traditional tools. And Pokemon Go isn't quite augmented reality.
It's sad but true, whatever you think you're hearing from starry-eyed tech writers, Silicon Valley marketers or even chief executives.
For example, when Apple boss Tim Cook said during the latest earnings call that "machine learning enables Siri to understand words as well as the intent behind them", it was a forward-looking statement, not a promise to tomorrow's iPhone buyers; 98 per cent of iPhone users have tried Siri, but only about 30 per cent use it with any regularity - precisely because they expected more from it before it could match those expectations, and that's the way it's going to stay for some time.
Two years ago, when much-hyped 3-D printing was proving a bit kludgier than neophytes drawn by the promise of magic expected, its inventor, Charles Hull, said this in an interview: "Most of the stuff they talk about will happen someday - eventually. But there's the here-and-now and the near-term future, where a lot of that stuff is definitely hype and won't happen."
"Most of the stuff" and "eventually" are the keywords. We don't know for sure whether, let alone when, autonomous-driving technology will fully replace humans, or whether machine translation will work as well as the human kind.
We often pay to serve as testers for technology that is going exciting places for the engineers who develop it. And we expect instant gratification, though intuitively, we should understand there's no such thing in engineering. They don't really deceive us: The warnings are always there for those who are willing to listen, and the makers and the hypers are rarely the same people.
It's difficult for laymen to resist the hype. We want to believe in miracles, and we often don't admit to ourselves that the tech we buy into isn't quite miraculous, that despite being extremely advanced and unimaginable just a decade or two ago, the gap between it and pure magic is often bigger than the distance already covered.
For those who need a reality check, though, there's a convenient tool: the "Hype Cycle", developed by tech research firm Gartner. Technologies aren't brought to market when they can fully deliver on their promise but when they are at what Gartner calls the "Peak of Inflated Expectations". Almost exactly a year ago, the company released its 2015 Hype Curve. At the top: autonomous vehicles, speech-to-speech translation and machine learning. Marketers figure the top of that cycle is the best time to offer tech to the masses. People who expect magic get disappointed, and the technology falls into the "Trough of Disillusionment".
But the good news is that at least some of the technologies then make it up the "Slope of Enlightenment" to the "Plateau of Productivity".
Enterprise 3-D printing was halfway to the plateau from the trough a year ago, according to Gartner. Virtual reality was just climbing out of the trough.
This doesn't mean we shouldn't buy new tech when it's being overhyped. But it does mean that we shouldn't expect much from it. I feel privileged to play with the early implementations of big dreams, even if they never come to fruition.

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