​​ AI and computer vision

Computer vision in the context of AI technologies is one of the fields of artificial intelligence. Its purpose is to extract information from various visual data (including videos, photos, pictures, etc.) and to make decisions or provide recommendations based on the information obtained. Classical artificial intelligence is what teaches a computer to think, and thanks to computer vision they can see. Collectively, this vision enables observation and understanding.

In general, computer vision operates similarly to human vision, but the human eye is more sophisticated — we can assess what we see in context, distinguish objects, see their distance, the presence of movement, and any irregularities (irregularities). And scientists are now working to teach this to machines as well. Cameras, data sets, and algorithms are being used for this purpose.

Already, computer vision is being actively used in various sectors of human life, from energy to automotive engineering. And this area of AI is now actively developing and growing. Let’s look at a few examples of the use of computer vision:

IBM used computer vision to create unique clips for a golf tournament. Based on the algorithms developed and the data collected, AI recognized the key and highlights of the bouts, delivering them as special personalized videos to fans.

Google uses computer vision in its popular Translator app: the user points their phone camera at text and receives an instant translation into the language they want.

Computer vision systems are used extensively by developers of drones. They are used to identify other road users, signs, changing road conditions, and other visual information.

Artificial intelligence systems with computer vision are already being used in manufacturing. They enable manufacturers to detect potential defects or flaws in products before they reach the market. This is very relevant, especially when it comes to large-scale projects such as cars.