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5 июля 2021 г. 12:00

Will Computer Vision Make Human Workers Obsolete?

Computer vision is the most recent development in AI. This human-impersonating technology first existed in the 1970s, but it is currently revolutionizing sectors thanks to its expanded capabilities. In fact, you’re probably exposed to computer vision on a daily basis without even recognizing it. Computer vision is all around us, from unlocking your iPhone with facial recognition to Tesla’s autonomous driving feature.

This fascinating branch of computer science aims to imitate the complicated principles of human vision, allowing computers to quickly recognize items and react or make recommendations based on them.

Computer vision had not yet reached its full potential in the past due to a lack of large amounts of visual data and deep learning algorithms. Because of the massive amount of digital photos and video data that we now have access to, computer vision has advanced at an exponential rate in recent years. The recent technological boom has also been fueled by advances in neuroscience and neural network research. Machine-learning algorithms had to be built to duplicate the same neural circuits our brain employs when viewing and processing images in order to duplicate human vision with all of its complexities.

Transcending human capabilities

Computer vision has now surpassed human capabilities, with accuracy growing from 50 percent a decade ago to 99 percent now. Human eyesight is even outperformed by technology since people have biases while processing images, and, unlike computers, humans grow fatigued. Can machine vision truly replace human eyes across so many industries, despite its potentially immense commercial value?

The agricultural industry has made a significant turn toward high-tech, embracing AI to boost overall output. Growers and farmers can receive rapid insights into their operations and enhance profits by using aerial images. Computer vision is used by several Agtech businesses to detect faults in commodities for grading, which decreases post-harvest losses.

Access to this information improves efficiency throughout the agricultural supply chain, allowing for higher returns all year. Manually obtaining this amount of data would be unfeasible, but the success of this type of product is also greatly reliant on individuals. Farmers, traders, and food businesses are all still vital to the agriculture industry’s expansion. Moreover, though AI technology is advanced, it still has weaknesses, and it is vital to have humans deal with machine faults. For the foreseeable future, even as machines take on human jobs, we will be required to assist them through these duties.

The retail industry is being transformed by artificial intelligence, which is automating even the tiniest operations.

And that feature of AI — that it hasn’t been able to do it on its own without our assistance — is constant across industries. Retail has also been altered by computer vision, which has brought old-school brick-and-mortar into the digital age. Retailers are using AI technology to improve customer support and create a more personalized shopping experience.

Some grocery store startups have even created automatic check-out systems that fit right on top of existing trolleys and baskets. Unlike today’s barcode-scanning checkout systems, computer vision can detect each item in the cart on its own, improving the customer experience and lowering expenses. This technology is far less expensive to implement than other options, and it requires very few adjustments to the shop’s atmosphere while also making shopping much more convenient.

However, in-store retail will continue to face competition from the convenience of Internet buying, and in-person retailers will need to maintain their competitive advantage – human interaction. In fact, some customers still prefer brick-and-mortar establishments because they want a more personal buying experience.

While the ease of AI products will draw in more customers, store attendants who can assist clients on the spot will continue to be required for business. You can’t ask a device to show you where an item is physically located in a store.

Machine vision can help retailers streamline their operations in ways that go beyond the in-store customer experience. Even the tiniest operations that were formerly done manually are being automated by AI technology, saving consumers from having to go to a physical store and wait in line for everything. There are now AI-based smartphone assessment technologies that allow consumers to objectively self-grade their device's value for distant trade-ins. The annual market for trade-ins is enormous, with $ 2 billion expected to be returned to customers in 2020.

Computer vision in medicine is saving lives

Computer vision is not just boosting efficiency in medicine; it is also saving lives. Healthcare has been changed by the introduction of machine-learning technology. From waiting rooms to emergency rooms, new technology is assisting doctors in diagnosing, performing procedures, and administering treatment using information that the human eye would easily overlook. Human biases can sometimes impair patient treatment in businesses that rely on human interaction, such as medical care. As a result, automated care may be a viable option for addressing substantial disparities and variability in patients' treatment. This shows how AI technology and people must collaborate in order to obtain the best outcomes.

As we understand more about the science behind the human eye and as massive volumes of data continue to flood our internet world, computer vision is poised to become virtually human - or even better in some circumstances. Experts warn, however, that neuroscience has its limits and that mapping brain networks, let alone having a computer duplicate them, is difficult and unavoidably imperfect. Moreover, computers lack humans' common sense and background knowledge. Although machines are less prone to errors, relying only on them is a mistake. Human intuition still has a lot of value, and until robots can equal it, the two will have to continue to work together.

Source: - https://karenmintonwp.wordpress.com/2021/07/05/will-computer-vision-make-human-workers-obsolete/

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