What if a computer could let us “feel” the texture of a fabric before we buy clothes online? Or gives us a whiff — or even a taste — of a meal we’re thinking of preparing? That’s pretty game-changing stuff. And, it’s also within the realm of possibility in the next 5 years, according to IBM’s list of technologies it thinks are on the cusp of adoption.
Every year IBM polls its R&D braintrust about what technologies that may have “been at the hairy edge before but are now closer to the scalp,” IBM fellow and VP of innovation Bernie Meyerson told me recently. This year those “closer-to-the-scalp” technologies converge around computers’ growing ability to handle richer, more diverse data and churn out more valuable output — such as the feel of cloth, the smell or taste of food. The general premise is that these sensory and cognitive technologies will convert computers from glorified calculators into true thinking machines.
So, without further ado, here’s IBM’s sixth annual 5 in 5 technology picks.
1: Computers with a sense of touch
Even people who love shopping online say that it’s hard to get a good read on the finished product from a digital image alone. Most of us want to feel the fabric before we buy a big-ticket item. So what if you could sample that cashmere coat from your cell phone before adding it to your shopping cart? Texture data fed into a machine’s piezoelectric drivers can re-create vibrations and temperature on a touch screen can simulate that feel, Meyerson said. “Imagine you have very fine pixels and that each can be heated and vibrated to mimic the sensation of the cloth,” he said.
Some of this capability is available now in rudimentary form in computer games where the controller shakes to indicate an on-screen car collision.
2: Seeing the forest, not just the trees
If you have to rasterize an image in order to analyze it, any sort of correlation will take a long time. If the computer can instead really see and understand that image for what it represents — say, a child, as opposed to a bunch of pixels — it can accelerate the whole process of analysis. That in turn will make the parsing of things like medical images and traffic video much faster. The difference here is between the computer viewing an image and understanding that image without having to break it down into myriad components. That’s the way humans deal with the world. Computers could monitor scanned images of a person over time to watch for and detect changes that indicate a health condition before it gets too serious for example.
3: Hearing the whole story
Just as computers need to see images as whole entities, IBM thinks they also need to hear total sounds — ambient noise, words, music, a lot of inputs to get the full story. “It’s not necessarily just hearing words, hearing is also background noise … if a cell phone caller is in a car with an engine running at 2,000 rpm, you might even be able to tell if the driver is stuck in traffic or moving smoothly,” Meyerson said.
By embedding sensors in flood prone areas, this technology could warn users based on what it’s learned from past sounds, as to whether a mud slide is likely. Computers could also likewise learn based on past experience when a baby’s cry is due to a wet diaper, teething, or something more serious.
4: Digitized taste buds
IBM’s brainiacs think that machines will increasingly be able to taste things — like chocolate or eggplant – and figure out why people do or don’t like that taste. As Kevin Fitchard, GigaOM’s resident foodie, recently reported, some of this is happening now. For example, researcher and app developer Foodpairing
“has broken down flavor to its molecular components and has compiled databases that can match the flavor of those ingredients against other completely different ingredients. By compiling “foodpairing trees” its technology can identify vegetable or seafood ingredients that reinforce the flavor of different meats, or in some cases, can act as a substitute for a meat entirely.”
This understanding of the chemical elements of food could help people get healthier by subbing in something that tastes like milk chocolate but is better for them.
5: A nose that knows
Breath analysis can do more than keep drunk drivers off the road. What if your smartphone could tell from your breath that you’re about to get a cold? It’s conceivable that your doctor would be able to diagnose you remotely based on that information and prescribe treatment. This technology could also sniff out minuscule amounts of environmental toxins before they hit critical mass, which could have broad public health ramifications.
And then there’s just the quality of life aspect. “You can paint chemical sensors on a surface and when they detect a pattern, they give off a smell — you could make a rich paint with all sorts of sensors that mimic things that you like,” Meyerson said.
So, how’s IBM doing as a sooth sayer?
Since I’m still waiting for the jet packs we were promised decades ago, I’m skeptical about technology predictions, but IBM’s list provides a good starting point to track tech progress and priorities. It’s also fun to grade its prognostication skills.
Looking at last year’s 5 in 5 predictions, it’s fair to say there are hits and misses. For example, last year it said junk mail will get so targeted it will actually cease to be junk at all. If that’s happening, I’m not seeing it.
Another 2011 prediction was we’d get much better at capturing and using wasted kinetic energy – from people walking, riding bikes,from running water etc. There is early traction there. Los Angeles is testing advanced flywheel technology as a way to reap wasted energy from braking trains and re-apply it when trains accelerate. And Pavegen is building sidewalk tiles designed to capture energy from walking pedestrians.
Taking the longer view, looking at IBM’s inaugural list in 2006, it does better. It was on the money with its call that people would be able to access healthcare remotely. There are lots of tele-radiology options and doctors can even perform surgery remotely. IBM also predicted real-time speech translation now exemplified by products like Samsung’s Galaxy speech translation. Meyerson admits to some less successful calls — especially one about hydrogen-powered vehicles — but he’s pretty happy overall with IBM’s effort.
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