Many of us interact with computer vision applications every day, from Apple’s Face ID and Tesla Autopilot to the Meta Quest and Google Lens.
Computer vision gives machines the ability to “Perceive” the world like humans do and use that knowledge to augment human efforts.
The potential is immense, and analysts agree: The computer vision market is expected to expand to $9.62 billion according to research from Report Ocean.
Here are three of the biggest trends to keep an eye on in the year ahead – and how organizations can unleash new possibilities through computer vision:
To date, one of the big bottlenecks in the cloud vision space has been the power of computer vision devices.
Because edge devices – think sensors and cameras – haven’t been powerful enough to do their own computation, most of the data processing has had to happen in the cloud.
Thanks to advancements in edge computing, computer vision applications can run real-time data processing and analysis, which is not just reducing energy and bandwidth burdens, but is also improving computation efficiency.
This is a big deal considering that many of the most compelling applications of computer vision rely on ultra-low latency data processing to deliver seamless user experiences.
Rapid advancements in NAND Flash technology have dramatically increased the volume of data that can be stored on the edge devices through SSDs and micro SD cards. Notably, these trends have significant implications for CISOs: Because data is stored locally, edge storage is both more secure and more respectful of end user privacy.
This is critical to bolstering CV adoption amidst a rapidly evolving privacy and data protection landscape. Today, it’s not the lack of technology that’s holding back the development of computer vision applications – it’s the lack of talent.
Nearly 65% of IT executives see the talent shortage as the most significant factor impacting the adoption of new technologies such as computer vision, according to a recent Gartner study.
In particular, consider the rise of low-code and no-code development, which has key implications for advancements in computer vision.
These platforms also empower more people to contribute to the advancement of computer vision. Smart enterprises will embrace privacy as a differentiator. Privacy, once an afterthought for technology companies, has today taken center stage.
As the market learns from Apple’s successes, we’re certain to see more companies differentiate themselves by building privacy into their core value proposition.
Recent surveys have shown that Gen Z, in particular, cares deeply about privacy and wants to do business with brands that have top-notch data privacy and security infrastructure in place.
Because customers are likely to stick with businesses that they trust to protect their personal information, privacy can bolster brand value and long-term customer loyalty.
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