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Artificial intelligence (AI) broadly refers to any human-like behavior displayed by a machine or system. In AI’s most basic form, computers are programmed to “mimic” human behavior using extensive data from past examples of similar behavior. This can range from recognizing differences between a cat and a bird to performing complex activities in a manufacturing facility.
Whether you are talking about deep learning, strategic thinking, or another species of AI, the foundation of its use is in situations that require lightning-fast responses. With AI, machines can work efficiently and analyze vast amounts of data in the blink of an eye, solving problems through supervised, unsupervised, or reinforced learning.
Artificial intelligence is classified into two main categories: AI that’s based on functionality and AI that’s based on capabilities.
Reactive Machine – This AI has no memory power and does not have the ability to learn from past actions. IBM’s Deep Blue is in this category.
Limited Theory – With the addition of memory, this AI uses past information to make better decisions. Common applications like GPS location apps fall into this category.
Theory of Mind – This AI is still being developed, with the goal of its having a very deep understanding of human minds.
Self-Aware AI – This AI, which could understand and evoke human emotions as well as have its own, is still only hypothetical.
Artificial Narrow Intelligence (ANI) – A system that performs narrowly defined programmed tasks. This AI has a combination of reactive and limited memory. Most of today’s AI applications are in this category.
Artificial General Intelligence (AGI) – This AI is capable of training, learning, understanding, and performing like a human.
Artificial Super Intelligence (ASI) – This AI performs tasks better than humans due to its superior data processing, memory, and decision-making abilities. No real-world examples exist today.
The relationship between artificial intelligence, machine learning, and deep learning
Artificial intelligence is a branch of computer science that seeks to simulate human intelligence in a machine. AI systems are powered by algorithms, using techniques such as machine learning and deep learning to demonstrate “intelligent” behavior.
A computer “learns” when its software is able to successfully predict and react to unfolding scenarios based on previous outcomes. Machine learning refers to the process by which computers develop pattern recognition, or the ability to continuously learn from and make predictions based on data, and can make adjustments without being specifically programmed to do so. A form of artificial intelligence, machine learning effectively automates the process of analytical model-building and allows machines to adapt to new scenarios independently.
Deep learning is a subset of machine learning that has demonstrated significantly superior performance to some traditional machine learning approaches. Deep learning utilizes a combination of multi-layer artificial neural networks and data- and compute-intensive training, inspired by our latest understanding of human brain behavior. This approach has become so effective it’s even begun to surpass human abilities in many areas, such as image and speech recognition and natural language processing.
