How can you monitor data in 810 billion photos?
Have you been watching the epic Planet Earth 2 from the BBC?
If so, you'll have been amazed at the roving drone that filmed billions of locusts in Madagascar.
How about the jaw-dropping footage of a starving lioness trying to take down a giraffe at full chat?
You were there. Almost. The images were simply stunning.
Combine them with some 810 billion photos taken worldwide every year and add CCTV images, maps, drones and spatial sensors then there is more imagery than humans can ever hope to monitor or organise.
But is there?
Automated searching of photos, video and even live scenes are vital to locate the 'needle’ of relevant content from this visual haystack.
The ability to identify visual cues has tremendous implications for the retail sector, crime prevention, medical procedures and more. Recognising the important developments in this area, global research consultants Frost & Sullivan produced a report on the opportunities in visual search.
The beauty of visual search in Scotland
There are a number of Scottish companies making important developments in AI and machine learning, two essential components for visual search. These developments often begin in the highly specialised departments of Scottish universities such as Edinburgh University and Dundee University.
For example, Scotland has its own pioneer in mobile visual search – Mobile Acuity, a spin-out from Edinburgh University’s AI department. AI skills are an essential resource as visual search depends on the underlying, leading-edge techniques of machine learning and computer vision.
Glasgow is using facial recognition for crime prevention as part of its £24m future city initiative, and Edinburgh-based Toshiba Medical Visualization Systems specialises in automated scanning of medical imaging and has launched a postgraduate research practice with Dundee University
The Shazam of shopping
The retail sector is the first sector to take commercial advantage of artificial intelligence (AI) applied to unstructured visual data. Amazon encourages consumers to scan real-world objects and locate the associated products online using its Firefly phone app.
Start-ups like Toronto-based Slyce describe their solution as ‘the Shazam of Shopping’. The company’s apps recognise products from smartphone cameras, web images and physical product tags and direct the consumer to the closest match in the retailer’s catalogue, or to a range of similar products for browsing. Neiman Marcus, an American department store, is already using Slyce technology in its mobile ecommerce app.
By moving consumers quickly from their initial interest in a product to final purchase online, visual search removes the clunky text search stage and should reduce ‘abandoned basket’ syndrome.
Visual search will transform business processes
Cost is becoming less of a barrier as leaders in the field make their AI tools more affordable. Google, for example, recently made its machine learning libraries available as open source, and Microsoft offers machine learning as a service on its Azure platform.
Access to training data may be more of a challenge. There will be opportunities for data aggregators in specialist domains, supplying validated, high quality data via an as-a-service business model.
Solution providers that can build massive scale and accurate visual search will be in a strong position to add value that competitors cannot easily replicate. Customers in many sectors will quickly realise the benefits in automated operations, new services, and deeper engagement with consumers.