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Artificial Intelligence and Artificial Perception

Artificial Intelligence (AI) has been a highly researched area in the computer industry for many years. Most people think it will enable machines to think like we do, but did you know it only utilises half the full capability of the human brain?

Basically everyone knows that human brains have a large divide down the middle, giving us a left and right half of the brain. These two halves have bridges sending information between them, but are largely unconnected. Virtually all the capabilities that AI understand are learning-related (e.g machine learning, deep learning, etc.), which only accounts for the left-brain's logical functions and not the right-brain's more creative side. However, the more instinctive right-brain is also important, providing us with essential abilities such as spacial perception and somesthesia. To utilise this otherwise untapped half of the brain, in contrast to Artificial Intelligence, we use Artificial Perception (AP) to cover the right-brain's capabilities.

But why then has AP been mostly overlooked in favour of standard AI for the majority of applications. Well, machines mainly rely on sensors to get their information about the outside world. GPS, depth sesnors, cameras, and the like, have become so accurate they surpass even natural human senses. But we continually undervalue the importance of a machine's ability to provide instinctive perception.

It's similar to how we always believed the future of data processing to be reliant on computer memory and processor power, before we realised the true potential of AI. In other words, data processing has been much faster and more accurate than a human could ever achieve for many years, but most of us never put enough value in a computer's ability to learn. Recently, however, data processing has taken a big leap forward, and anyone working in “big data” will tell you that the reason for this is advances in AI. A similar paradigm shift is likely to occur once it becomes apparent that computers also have the capacity to perceive and understand. It's clear in humans that both halves of the brain complement one another. The more AI develops, the more it will develop a need for advanced AP. For example, image classification is a key AI feature, but we are still sticking to the idea of using 2D images, rather than utilising the full spacial perception of the physical world that humans naturally achieve every day.

As we move forward, it will become apparent that AI is lacking an essential component, and that AP is the component that will fill the void. Instead of developing sensor technology, Kudan purely focuses on algorithms for AP and leads AP technologies through our expertise in computer science and applied mathematics, allowing us to deliver commercial products that will evolve the industry.

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