Artificial Intelligence (AI) is wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry. Artificial Intelligence refers to the phenomenon where a machine acts as a blueprint of the human mind, by being able to understand, analyze, and learn from data through specially designed algorithms. Artificially intelligent machines can remember human behavior patterns and adapt according to their preferences.
The major concepts closely related to AI that you will come across over the course of our discussion are machine learning, deep learning and natural language processing (NLP). Let’s make sense of these before we move on.Machine Learning (ML) involves teaching machines about important concepts via examples by means of big data that needs to be structured (in machine language) for the machines to understand. This is all done by feeding them the right algorithms.Deep Learning is a step ahead of ML, meaning it learns through representation but the data does not need to be structured for it to make sense of it. This is due to the artificial neural networks that are inspired by the human neural structure. Natural Language Processing (NLP) is a linguistic tool in computer science. It enables machines to read and interpret human language. NLP allows an automatic translation of human language data and enables two entities (computers and humans) who speak different languages to interact.Now that you are equipped with the terminologies, let’s delve into examples of artificial intelligence and how they work.
Less than a decade after breaking the Nazi encryption machine Enigma and helping the Allied Forces win World War II, mathematician Alan Turing changed history a second time with a simple question: "Can machines think?"
Turing's paper "Computing Machinery and Intelligence" (1950), and it's subsequent Turing Test, established the fundamental goal and vision of artificial intelligence.
The major limitation in defining AI as simply "building machines that are intelligent" is that it doesn't actually explain what artificial intelligence is? What makes a machine intelligent?
In their groundbreaking textbook Artificial Intelligence: A Modern Approach, authors Stuart Russell and Peter Norvig approach the question by unifying their work around the theme of intelligent agents in machines. With this in mind, AI is "the study of agents that receive percepts from the environment and perform actions." (Russel and Norvig viii)
Norvig and Russell go on to explore four different approaches that have historically defined the field of AI:
- Thinking humanly
- Thinking rationally
- Acting humanly
- Acting rationally
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