AI: A Multi-Dimensional Breakdown

by Mitchell Lane

Artificial Intelligence (AI) is a field of computer science that explores machines learning, thinking, acting and solving problems humans naturally excel at. Well, that’s one way of defining it, however there are a ton of definitions. This post will explore some of the ways we define AI.

At a broader level, AI also encompasses knowledge representation, perception, optimisation, self organising systems, and complex algorithms based on genetics, evolution and survival of the fittest. Furthermore, AI draws inspiration from other natural systems like human organ operation, and other forms of intelligence such as animal, herd, and swarm intelligence to uniquely solve problems.

 

AI is…

Weak, which is more commonly known as ‘Narrow AI’. It focuses on solving a single narrow task. It addresses specific application areas such as playing strategic games, language translation, self-driving vehicles, and image recognition.

Strong, which is sometimes called ‘Artificial General Intelligence’. It refers to a future AI system that exhibits intelligent behavior at least as advanced as a person across the full range of cognitive tasks. This definition doesn’t give any thoughts to the system exhibiting consciousness (which it may inherit or evolve to have!)

 

We want AI to...

Think like a human: We take inspiration from the the massive distributed connectedness of the human brain and neuron firing mechanism, as the biological basis for neural networks, cognitive architectures, bayesian inference and massively parallel processing.

Act like a human: To see and understand real world entities, and how they relate to each other through video capturing and computer vision techniques. To communicate in human language, understanding people’s intentions and emotions through natural language processing techniques. Also the ability to store knowledge, reason with it, and continuously learn.

Think rationally: Solving problems through inductive or deductive logical reasoning. Inferring a good solution to a constrained problem with multiple circumstances and outcomes. Also, optimising a decision to get maximum benefit from it, for instance, what is the best next move I can make in this chess game?

Act rationally: Embodying a rational, intelligent system into an agent or robot that can use it’s own sensor data to achieve goals through perception, planning, reasoning, learning, communicating, decision-making, and acting.  

 

AI is about…

 

Major areas of AI research and solutions include...

 

AI approaches follow one of five main mindsets

 

This is just a few different dimensions to view A.I. We use a number of these ways to think about A.I, and to explain to our clients what it all is. Some ways resonate better with certain people. For me, I like to think of A.I through the five different mindsets. I’m a bit of an evolutionary as my research is in the field of Particle Swarm Optimisation (an Evolutionary Computation method based on swarm intelligence). However, I think the future of A.I will use more and more ideas from the combination of connective, evolutionary and bayesian AI.

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