Whereas Human Intelligence aims to adapt to new environments by combining different cognitive processes, Artificial Intelligence (AI) builds machines that can mimic human behaviour and perform human-like actions. However, a human brain is analogous and machines are digital. Whereas human intelligence is the ability to think, analyse and apply, AI machines react to given data.
Human intelligence is due to our senses that build cognitive abilities, operating through a dynamic nerve cell network. We can think, we can comprehend complex ideas, and easily solve logical problems. We even adapt to new situations, use knowledge to manipulate our environment and speak and understand multiple languages. How is AI built?
It is “the science and engineering of making intelligent machines, especially intelligent computer programs”. Said John McCarthy, an American cognitive scientist and one of the founders of AI. An important aim of AI is to improve computer functions which are related to human knowledge, for example, reasoning, learning, and problem-solving, Perception and Linguistic Intelligence.
We often create software or devices which solve real-world problems, be it in the health sector or managing traffic easily and accurately. We even create our own personal virtual assistants, such as Cortana, Google Assistant, Siri or build Robots which work in hazardous environments for humans. Gaming, Natural Language Processing, Expert Systems, Machine Learning, Vision Systems, Speech Recognition, Handwriting Recognition are all some great application areas of AI.
AI can be understood in very simple terms. Human brain is a complex network of neurons which use electrical impulses and chemical signals to transmit information between different areas of the brain, and between the brain and rest of the neural network. However, in the computer world, a neural network is a series of algorithms that helps recognize underlying relationships, in a set of data through a process that mimics the way the human brain operates. Hence in AI, neural networks refer to systems of neurons, either organic or artificial in nature. The data of course, comes from various sensors that measure physical quantities similar to the way our five main sensors measure.
Unlike human brain, most basic AI systems are purely reactive, and have the ability neither to form memories nor to use past experiences to inform current decisions. It doesn’t have any concept nor memory of the past though that’s not the end. At a slightly higher level, there are limited memory models. These extract knowledge from previously learned information, facts, stored data or events and are termed machine learning models. As distinct from reactive machines, the limited memory models build basic knowledge by learning from the past and analysing actions or data given to them. These models are built by numerical cycles which expand quickly into more precise models, estimate real time systems and also interpret. Personal virtual assistants like Alexa are all limited memory models. They are also found in many chatbots and self-driving cars.
We often learn from past mistakes. We are innovative. We adapt to changes quickly, we are better at social interaction, we have self-awareness, and we are considerate to others’ emotions, all of which are difficult for AI machines to mimic. They can only learn from information and through regular training. But what we cannot do is, ace a computer in its speed of working with or manipulating numbers and repeating tasks with accuracy.
Advanced models of AI like ‘self-aware’ is where the machines are aware of themselves and perceive their internal states and others’ emotions, behaviours, and acumen. However, this AI is as yet WIP. The day it is fully developed, we will surely witness a robot with human-level consciousness and intelligence. Until that happens, we must make do with Machine learning, a subset of AI and computer science that, focuses on the use of data and algorithms to imitate the way humans learn.
Would a full-blown development of AI spell end of the human race as Stephen hawking predicts, may be farfetched. On the other hand, will we become more productive in future and live a more reasonable life is a question with no easy answers. Apparently, we live in a smart world. Are we now smarting under an overdose of our own smartness?