Top 3 Computer Vision Trends to Watch in 2023
Join senior executives in San Francisco on July 11-12 to learn how leaders are integrating and optimizing AI investments for success. Find out more
Many of us interact with computer vision applications on a daily basis, from Apple's Face ID and Tesla Autopilot to MetaQuest and Google Lens. Computer vision gives machines the ability to "see" the world the way humans do and use that knowledge to augment human efforts. The potential is immense and analysts agree: the computer vision market is expected to reach $9.62 billion according to research from Report Ocean.
Here are three of the top trends to watch in the coming year, and how businesses can unlock new possibilities with computer vision.
Faster, Cheaper, and More Efficient Edge Computing Storage Will Accelerate CV ApplicationsTo date, one of the major bottlenecks in cloud vision is the power of computer vision devices. Since peripheral devices — think sensors and cameras — haven't been powerful enough to perform their own calculations, most data processing has had to be done in the cloud. The result: inflated costs due to high network bandwidth and power consumption.
We are finally seeing this change. Thanks to advancements in edge computing, computer vision applications can perform real-time data processing and analysis, which not only reduces power and bandwidth loads, but also improves the computational efficiency. That's a big deal given that many of computer vision's most compelling applications rely on ultra-low latency data processing to deliver smooth user experiences.
EventTransform 2023
Join us in San Francisco on July 11-12, where senior executives will discuss how they've integrated and optimized AI investments for success and avoided common pitfalls.
Register nowIn addition, we are also seeing some exciting advances in edge storage. Rapid advances in NAND Flash technology have dramatically increased the volume of data that can be stored on peripheral devices via SSDs and micro SD cards.
In particular, these trends have important 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 boost CV adoption in a rapidly changing privacy and data protection landscape. (More on this below.)
Today, it's not a lack of technology that's holding back the development of computer vision applications: it's a lack of talent.
According to a recent study by Gartner, nearly 65% of IT managers consider the shortage of talent as the most important factor impacting the adoption of new technologies such as computer vision. In response, I think we'll start to see more organizations overcome their talent shortage by focusing on upskilling their existing workforce to use the latest technology.
In particular, consider the...
Join senior executives in San Francisco on July 11-12 to learn how leaders are integrating and optimizing AI investments for success. Find out more
Many of us interact with computer vision applications on a daily basis, from Apple's Face ID and Tesla Autopilot to MetaQuest and Google Lens. Computer vision gives machines the ability to "see" the world the way humans do and use that knowledge to augment human efforts. The potential is immense and analysts agree: the computer vision market is expected to reach $9.62 billion according to research from Report Ocean.
Here are three of the top trends to watch in the coming year, and how businesses can unlock new possibilities with computer vision.
Faster, Cheaper, and More Efficient Edge Computing Storage Will Accelerate CV ApplicationsTo date, one of the major bottlenecks in cloud vision is the power of computer vision devices. Since peripheral devices — think sensors and cameras — haven't been powerful enough to perform their own calculations, most data processing has had to be done in the cloud. The result: inflated costs due to high network bandwidth and power consumption.
We are finally seeing this change. Thanks to advancements in edge computing, computer vision applications can perform real-time data processing and analysis, which not only reduces power and bandwidth loads, but also improves the computational efficiency. That's a big deal given that many of computer vision's most compelling applications rely on ultra-low latency data processing to deliver smooth user experiences.
EventTransform 2023
Join us in San Francisco on July 11-12, where senior executives will discuss how they've integrated and optimized AI investments for success and avoided common pitfalls.
Register nowIn addition, we are also seeing some exciting advances in edge storage. Rapid advances in NAND Flash technology have dramatically increased the volume of data that can be stored on peripheral devices via SSDs and micro SD cards.
In particular, these trends have important 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 boost CV adoption in a rapidly changing privacy and data protection landscape. (More on this below.)
Today, it's not a lack of technology that's holding back the development of computer vision applications: it's a lack of talent.
According to a recent study by Gartner, nearly 65% of IT managers consider the shortage of talent as the most important factor impacting the adoption of new technologies such as computer vision. In response, I think we'll start to see more organizations overcome their talent shortage by focusing on upskilling their existing workforce to use the latest technology.
In particular, consider the...
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