Can you predict the success of a new technology by how much buzz it gets?
The tech industry has a habit of getting ahead of itself.
An idea comes along, investors talk it up, the media catches wind…suddenly, the thing is plastered on every front page and home page, ink on the patent application still drying. Before you can mutter the word ‘disruptive,’ though, doubt slowly creeps in, backlashers begin their backlash, and the bubble is burst.
The people at Gartner, a Connecticut-based research and consulting firm, spend a lot of their time thinking about that cycle. They put out a chart each year, in fact, called the Hype Cycle, that tries to measure what stage different technologies are in, and how fast they’ll move through those stages.
“The shape of the curve, if you can imagine it, it rises up like a mountain peak in the beginning to describe the fact that this technology is quite exciting,” says Hung LeHong, an analyst at Gartner.
This first phase of the Hype Cycle is called the “innovation trigger.” On the upward slope, you’ll find not-quite-yet-household-name technologies like bioacoustic sensing and volumetric displays.
Another, human augmentation, is also still flying under the radar, but won’t be for long.
“Since the age of 21, instead of seeing color, I can hear color,” says artist Neil Harbisson, on stage during a TED talk in June 2012.
Born colorblind, he wears a prosthetic device called an eyeborg that detects light wavelengths and transforms them into sound.
“It is a color sensor that detects the color frequency in front of me, and sends this frequency to a chip installed in the back of my head, and I hear the color in front of me through the bone, through bone conduction,” he says.
His senses of sight and hearing swirl around in his head like a symphony. Red, orange and yellow produce a tone higher up the scale, while blues sit down low.
“When I started to dream in color, is when I felt the software and my brain had united.”
The growing buzz for simulated organs
A little higher up on the “innovation trigger” slope sits the concept of biochips. Gartner defines these as the merging of semiconductors with biology. Think: simulated organs.
“So this is the size of a memory stick or a rubber eraser, and then if you look closer, actually, you see these individual micro-fabricated channels, in which we grow human cells,” says University of Pennsylvania engineering professor Dan Huh.
Inside his lab, he shows off his “lung-on-a-chip” device. Using a syringe, Huh keeps cells alive with a mixture of nutrients and oxygen. The unit doesn’t function like an actual lung, but it can serve as an avatar for air sacs within a lung. The chip is clear, and made of the same material as contact lenses.
“Because the device is flexible, we can compress or stretch the whole device to mimic [an] asthma attack,” he says.
By recreating constricted airways, pharmaceutical companies could use the lung-on-a-chip to test the next generation of asthma drugs in a controlled setting, rather than on animals or in petri dishes. Huh is also working on chip-based replicas of other human organs including eyes and placentas.
There’s real potential here, and that means, according to Gartner’s chart, the technology will soon slide into the next part of the hype cycle, called the “Peak of Inflated Expectations.”
Right now, that dubious honor of unrelenting but undeserved spotlight falls on the so-called ‘Internet of Things.’ On the chart, it is right at the apex of hype.
Dan Frommer, tech editor for the digital news site Quartz, explains that IoT is the idea of connecting everyday objects to the internet.
“The jokes are always about things like connected toasters or connected refrigerators,” says Frommer. “You know, when you think about it, a connected refrigerator isn’t actually a horrible idea. How many times are you at the grocery store and wondering, ‘What’s actually in my fridge right now? Do we have yogurt or not?”‘
Gartner argues all the chatter about futuristic refrigerators isn’t actually a good thing for futuristic refrigerators, since the technology simply isn’t mature yet. When you are at the “Peak of Inflated Expectations,” it’s like everyone is trying to jump on a bandwagon that can’t handle the weight.
Frommer says he tries to get his reporters to tamp down hype for new products, but he still does, more or less, like the concept of the Hype Cycle.
“Sure, I think it is an interesting document. It isn’t something that I necessarily sit around waiting for,” he says.
Overhyping the hype?
It’s unclear who does eagerly await this chart’s update each year, though the safe bet is billionaires. Hung LeHong says most who buy the $7,500 version of the Hype Cycle report, which includes detailed analysis of each innovation, are entrepreneurs, large companies, and perhaps hedge funds.
People actually doing the groundfloor research and development, the grunt work, may simply glance at the one-page synopsis found for free online.
And if they did, expect a few broken hearts when they learn their once-hot technology has now passed through the peak of inflated expectations. Next up is the downward slide of hype Gartner calls the “Trough of Disillusionment.”
Like a B-list celebrity, technologies down in this deep valley may linger for years, their buzz reduced to a fading echo.
Venture capital and media have moved on. All that’s left are the true believers, working to refine and improve the concept; to develop the second and third generation versions that will someday provide real-world benefit.
“We perceive there being negative hype in the marketplace today for cloud computing,” says LeHong.
Along with the cloud, Gartner thinks big data and virtual reality are also experiencing growing pains.
They need not worry, however: the sun will soon peek through on the horizon.
“Then of course, there is a third phase, in which it crawls out of that deep valley and levels off,” explains LeHong. “And at that point, that’s where industry, enterprises, government, consumers, get a very good grasp of where this technology works, and I guess, even more importantly, where it doesn’t work.”
This part of the cycle is divided into two sections: the “Slope of Enlightenment,” home right now to technologies including 3D scanners and gesture control, and then the final leg, the “Plateau of Productivity.” Reaching the plateau is the equivalent of becoming a household staple, and “speech recognition technology” has the “Plateau of Productivity” all to itself on the latest Hype Cycle.
“Microphone On. Press Alt-Tab. Move Mouse Up,” commands Eliot Spindel. “Mouse Double click. New paragraph.”
An accident at home in 1985 left Spindel a quadriplegic, so being able to talk to his computer, and have it understand him, is crucial. Twenty years ago, still working to restart his life, he decided to learn how to write software code.
“But at the time I had to have somebody type for me, because I had no way to input into a computer,” he says. “So I would basically dictate, and you would type. Very frustrating.”
This is right when the first versions of speech recognition software were released. It was revolutionary, he says, especially for people living with physical disabilities. It just didn’t work all that well.
“Like you would say: Today…is…Tuesday…period. Now you can just say: Today is Tuesday, period,” he says.
The technology has come so far since the mid-90s that Spindel now does back-end website work independently for a few non-profits out of his residence at Inglis, a facility for people with disabilities in Philadelphia.
Watching him code, though, it still appears slower than being able to type.
“That’s hard to say, before my injury I was a two-finger kind of guy. So definitely not much speed there,” he says.
Speech recognition is now more than simply controlling your mouse and keyboard with your voice. Apple’s Siri and Google’s voice search use algorithms to interpret, to learn, and ideally, predict our queries.
That used to be hype. It was inflated expectation. Today it’s real.
Gartner, by the way, doesn’t always nail that evolution. One big miss in recent times were tablets, which the chart predicted would take much longer to reach enlightenment than they did.
This is not a perfect science, but the Hype Cycle is a good visual reminder that innovators and their ideas rarely have a smooth journey on the road to commercialization. They face ups and downs, peaks and troughs, as they snake their way toward success.