Computer vision is a rapidly growing field with vast applications poised to revolutionize the world around us.

The technology enables computers and systems to interpret and understand digital images, videos, and other visual inputs by using intelligent algorithms — and take actions or make recommendations based on that information.

Even today, computer vision is used for a variety of applications, ranging from Apple’s Face ID and Tesla Autopilot to the Meta Quest and Google Lens.

This trend is set to continue, and it is estimated that the computer vision market will be worth $41.11 billion by 2030, registering a compound annual growth rate (CAGR) of 16.0% from 2020 to 2030, according to recent research.

As the adoption of computer vision systems finds momentum, here are the biggest trends in the field to keep an eye on and benefit from.

1. Faster and More Efficient Edge Computing Storage

Cloud storage has been a game-changer for computer vision but it has not come without some challenges.

Edge devices, such as sensors and cameras, have been limited with regard to their computational power, making data processing in the cloud more of a necessity. This has resulted in high energy and network bandwidth consumption, leading to ballooning costs.

However, recent advances in edge computing have led to the invention of faster, cheaper, and more efficient edge computing storage.

Improved edge computing storage makes it possible for computer vision applications to run real-time data processing and analysis. This improves the efficiency of computation, reduces energy use and bandwidth burdens, and enhances user experiences.

With these improvements, data can be stored securely and respect personal privacy, making it a critical factor in bolstering computer vision adoption.

2. Upskilling Employees to Overcome Talent Shortages

Many companies face a talent shortage as they try to find skilled professionals with experience in computer vision.

According to a recent Gartner study, nearly 65% of IT executives see the talent shortage as the most significant factor affecting the introduction of new technologies such as CV.

Companies that want to overcome this challenge can focus on upskilling their workforce to keep up with the latest technologies. Low-code and no-code development platforms can help reduce the complexity of building and deploying computer vision applications.

These platforms use intuitive graphical user interfaces (GUIs), visual programming, and pre-built templates to enable business professionals, citizen developers, and novices to create solutions more rapidly.

This, in turn, will allow highly-skilled talent to work on more complicated problems, while others can develop and deploy simple applications.

The emergence of platforms such as Apple Create ML, Google AutoML, Clarifai, obviously.ai, and viso.ai has made it possible even for developers with limited machine learning expertise to train high-quality models specific to their business needs.

3. Embrace Privacy as a Differentiator

Privacy is now a critical aspect of technology that many companies are actively addressing.

Apple is a great example of a business that has used privacy features to create a strategic competitive edge around its product ecosystem, much to Facebook’s disapproval. This trend is not exclusive to Apple, however, as many other businesses are also implementing privacy protocols to enhance customer loyalty.

Recent surveys show that Gen Z cares deeply about privacy and seeks to work with brands that have excellent data privacy and security infrastructure.

Privacy-focused businesses can command higher prices for their products and services, while customers can develop a long-lasting trust and loyalty towards brands that protect their personal information.

All in all, the future of computer vision looks promising, and many businesses will have to adjust to these changes to remain competitive.

With faster and more efficient edge computing storage, upskilling of employees, and embracing privacy as a new enterprise differentiator, businesses can maintain their competitive edge, driving growth and future success.

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