Artificial intelligence (AI), deep learning, and neural networks represent an incredibly exciting and powerful machine learning-based techniques used to solve many real-world problems. For a primer on machine learning, you may want to read this five-part series that I wrote.
While human-like deductive reasoning, inference, and decision-making by a computer is still a long time away, there have been remarkable gains in the application of Artificial intelligence techniques and associated algorithms.
The concepts discussed here are extremely technical, complex, and based on mathematics, statistics, probability theory, physics, signal processing, machine learning, computer science, psychology, linguistics, and neuroscience.
That said, this article is not meant to provide such a technical treatment, but rather to explain these concepts at a level that can be understood by most non-practitioners, and can also serve as a reference or review for technical folks as well.
The primary motivation and driving force for these areas of study, and for developing these techniques further, is that the solutions required to solve certain problems are incredibly complicated, not well understood, nor easy to determine manually.
Increasingly, we rely on these techniques and machine learning to solve these problems for us, without requiring explicit programming instructions. This is critical for two reasons. The first is that we likely wouldn’t be able, or at least know how to write the programs required to model and solve many problems that AI techniques are able to solve. Second, even if we did know how to write the programs, they would be inordinately complex and nearly impossible to get right.
Luckily for us, machine learning and AI algorithms, along with properly selected and prepared training data, are able to do this for us.
So with that, let’s get started!
Artificial Intelligence Overview
In order to define AI, we must first define the concept of intelligence in general. A paraphrased definition based on Wikipedia is:
“Intelligence can be generally described as the ability to perceive information, and retain it as knowledge to be applied towards adaptive behaviors within an environment or context.”
While there are many different definitions of intelligence, they all essentially involve learning, understanding, and the application of the knowledge learned to achieve one or more goals.
It’s therefore a natural extension to say that AI can be described as intelligence exhibited by machines. So what does that mean exactly, when is it useful, and how does it work?