The facial recognition landscape is rapidly changing. Significant advances in processing power, edge computing, 3D technology, and machine learning are leading to the democratization and commoditization of facial recognition software. They are also leading to increased efforts from larger enterprises to adopt this technology at a rapid pace, even if they don’t recognize the immediate need.
Apple’s iPhoneX launch will ensure that ubiquitous facial recognition on mobile is a certainty, with the expectation of 100% smartphone participation in biometrics by 2020. Technology powerhouses including Google, Microsoft, and Amazon are focusing their efforts on applied technology, reducing costs, and accelerating mass adoption.
These billion dollar entities focus on data collection for training instead of providing the best customer experience when it comes to their face recognition offering. They are explicitly tied up in compliance with GDPR as a cloud service so their face recognition solutions will remain highly restricted and as part of a larger scheme to offer value-add only if you are using their existing services.
The biggest challenge has been preparing for the regulation’s mandate that people in Europe must have control over how their digital data is organized. Google has had to go through each of its services — from Gmail to its Cloud storage services — to comply.
Edge Face Recognition
As we glance into the future of our infrastructure, cameras have become omnipresent. Their inevitable upgrade cycle will incorporate facial recognition technology to combat fraud and personalize experiences. This technology will spread due to the increased scalability of software architectures, advances in 3D technology, and the advent of edge GPUs.
We will witness a shift from cloud-based recognition to edge recognition that can react to faces faster than the capability of human recognition of a face. The result of edge face recognition will be convenience and bespoke experiences in our personal lives, more efficiency with our workforce and safer communities.
Nvidia has partnered with AI developer AnyVision to create facial recognition technology for “smart cities” around the world.
The thesis in the article linked above implies that the increased embedding of facial recognition in devices will reinforce an already popular experience-driven culture. An increased global spend on travel, dining, and other experiences speak to a shift from the consumption of material possessions to the pursuit of the immersive experience.
For startups to remain on the cutting edge they will need to take innovation risks as always. Such as advancing UX with customized experiences that can dynamically reflect and predict a person’s interests in real time.
In addition, offering specialized tools that will simplify facial recognition and enable it for specific use cases will become extremely important in gaining a competitive edge. It is not enough for a company to think only of the software and data collection, they must also embrace the personalization of technology and the consequences associated with it.
The race to be first in face recognition has no clear finish line and while the billion dollar companies of the valley focus on data collection, startups will put their best foot forward with UX, knowing that soon enough that data will be a commodity.