The unlikeliest of moments and sources can lead to remarkable moments of resourceful innovation for those who view the world through the lens of “This could…”
Japanese consumers love variety. There are over 300 flavors of Kit Kat for sale: Apricot Jelly, Green Tea, Pumpkin Cheesecake, Ginger Ale, Cherry Blossom, and a whole lot more. The same breadth of choice is expected baked goods.
Do you like Yakisoba noodles? You’ll be able to buy a Yakisoba Pan in your local bakery consisting of noodles fried together with meat and cabbage nestled in a mini hot dog bun. Whatever the food or flavor, there will be a version of it in a bun for sale at a bakery – fresh, ready to go, no wrapper to get in the way.
The hundreds of varieties of baked goods, however, presents a considerable challenge to the cashier at checkout. No wrapper means no bar code. No bar code means that when it comes time to pay, cashiers have to try and match each pastry to one of the hundreds of items on their price sheet, examining each one individually. This caused long lines, frequent errors, and unsanitary conditions as clerks had to handle each item while matching it to an image.
Programmer Hisashi Kambe saw an opportunity to make the checkout process more efficient and hands-free. His company, BRAIN Co., Ltd., had already pioneered a number of technologies related to computers “seeing” in different ways. He set himself the task of developing a program that would enable a computer to identify each of the hundreds of pastries on offer at a bakery automatically.
It wasn’t an easy task. Countless algorithms were created to deal with every imaginable variable – partially squashed or broken pastries, changing dimensions by filling spilling out at the side, a darker hue from being slightly over-baked, and on and on. It took five years of singular focus on the problem before the system was able to scan a seemingly infinite array bread products with 98 percent accuracy.
In 2013, reports The New Yorker, “BakeryScan launched as a real product. Today, it costs about 20,000 dollars. Andersen Bakery, one of BRAIN’s biggest customers, has deployed the system in hundreds of bakeries … Employees are more relaxed and can talk to customers; lines have been virtually eliminated. At first, BakeryScan’s performance wasn’t perfect. But the BRAIN team included a feedback mechanism: when the system isn’t confident, it draws a yellow or red contour around a pastry instead of a green one; it then asks the operator to choose from a small set of best guesses or to specify the item manually. In this way, BakeryScan learns.”
Jump forward a few years to 2017 when a doctor at the Louis Pasteur Center for Medical Research in Kyoto saw a feature about BakeryScan on TV. The doctor’s experience in cancer cell research connected something – when he say BakeryScan at work on TV, he thought to himself that cancer cells look a little like bread under the microscope. That’s when the breakthrough realization came:
“This could be used to scan and identify cancer cells.”
“He contacted BRAIN,” writes James Somers in The New Yorker, “and the company agreed to begin developing a version of BakeryScan for pathologists. They had already built a framework for finding interesting features in images; they’d already built tools allowing human experts to give the program feedback. Now, instead of identifying powdered sugar or bacon, their system would take a microscope slide of a urinary cell and identify and measure its nucleus.”
The doctor became a catalyst for unlocking the extra abilities of the technology behind BakeryScan. It was an act of resourceful innovation that revealed the untapped potential of the source technology.
It also showed the power of having an open mind to spot opportunity. If the doctor had been locked into “This is” thinking when watching the television segment on BakeryScan, the technology would still only be used to scan bakery items. But, as noted, the technology contained a scanning framework and feedback mechanism that allowed it to be applied to, and learn from, a new visual arena – cancer cells.
With this unlocking of the system’s additional potential, it opened the company’s perspective of what else it might be capable of. As The New Yorker writes:
“BRAIN began adapting BakeryScan to other domains and calling the core technology AI-Scan. AI-Scan algorithms have since been used to distinguish pills in hospitals, to count the number of people in an eighteenth-century ukiyo-e woodblock print, and to label the charms and amulets for sale in shrines. One company has used it to automatically detect incorrectly wired bolts in jet-engine parts.”James Somers in The New Yorker
There is additional capacity and new opportunities lying dormant in almost every system, object, or service we encounter. Discovering this extra potential – being part of a moment of resourceful innovation – requires nothing more than changing the words we use when observing things.
“This is…” keeps things locked in doing exactly what they currently do. “This could…” opens the door to infinite possibilities.
Like this article? You’ll love the book This Could… a guide for innovators, makers, and everyone wanting to do more with what they already have to be part of resourceful innovation.
“A masterclass in the art of possibility.” – Fiona Luis