Although it only has a presence in handful of major U.S. cities, AmazonGo stores could signifying the dawn of a “cashierless future”. as an example, Zippin, a cashierless tech provider has announced that it raised $12 million to expand its presence in stores and AmazonGo plans to go even bigger and open supermarkets throughout this year.
The technology behind cashierless stores — computer vision — is a sector of AI that trains computers to interpret and understand the visual world. Such technology has the potential to influence other industries beyond grocery, from healthcare to autonomous cars.
Pat Ryan, executive VP of enterprise architecture at digital tech consultancy SPR, tells Digital Journal about the history of computer vision and how it is set to shape a variety of industries.
Digital Journal: What is computer vision technology?
Pat Ryan: Computer vision technology allows a computer to see the contents and structure of an image. The technology is a set of algorithms that allow a computer to take a matrix of numbers and apply transformations and mathematical operations to find patterns and then translate those patterns into something we recognize.
The saying goes, “a picture is worth a thousand words” and by one study that is about the right number of words for an article or blog to do well. So how can we create a single image to convey the content of an entire article for a person to understand? We as humans are wired to see and understand the story being told in an image — but for a computer to extract that kind of meaning is very difficult.
Computer vision technology allows a computer to identify objects in an image such as a car, an animal or a person and can also provide context about what is happening in the picture.
DJ: How popular is this concept becoming?
Ryan: Images and videos are the primary way information is exchanged. It is said that people retain 80% of what they see and 20% of what they read. In my opinion, computer vision is the most popular and important set of technologies that will drive the most change going forward. And when you add machine learning and deep learning to computer vision the potential for change in how we interact with the world changes.
DJ: How is security built-in?
Ryan:In regards to the underlying algorithms that make up computer vision — there is no security built in. AI and computer vision are the tools used to create the applications we use. It is the applications that are created that need to seriously consider security.
DJ: What industries are currently adopting computer vision?
Ryan:It might be easier to ask which industries are not adopting computer vision technology. Some examples of industries using this technology include companies using computer vision to adjudicate claims or doctors and hospitals using computer vision to aid in reading X Rays. Retail stores also use computer vision to monitor customers and assist in inventory control. There are so many ways this technology can be implemented and useful across all types of industries.
DJ: Which industries are likely to take up the technology?
Ryan:Every industry will be adopting and using computer vision. The obvious industries are transportation and health care because industries like these rely on traditional human vision capability. Less obvious industries are those that can use imagery outside the human boundaries.
Keep in mind that when we talk about computer vision, we naturally think that we are talking about vision as we know it. But vision for a computer is much different. As humans, we generally do not see thermal imaging, or reflections from radio waves, but a computer with the right sensors can see these and this will allow for new applications like seeing through walls.
DJ: How will computer vision advance?
Ryan:Computer vision can be used for great good or great harm. I anticipate this technology will advance along both lines. For example, we should expect computer vision to be used for mass surveillance while in public places. However, we should also expect computer vision to advance the state of medicine to detect disease in its earliest stages. We should also expect this technology to see things that humans cannot, and translate that into something we can understand and that will in turn open up new worlds to us.
