What is Artificial Intelligence?
AI is a field of computing that focuses on systems which can perform tasks that typically, or previously, required human intelligence to complete: learning, problem-solving, decision-making, perception, creativity and social engagement.
Often the terms AI and Machine Learning (ML) are used interchangeably. While they are closely aligned, the core difference is that AI is based on the general idea of a machine that can mimic human intelligence, whereas Machine Learning leverages data and observed patterns, specifically with the aim to teach a machine how to perform tasks and provide results.
Arguably, the earliest body of work in AI was undertaken by British mathematician and computer scientist, Alan Turing, in the mid-20th century. The ‘Turing Machine’ concept described an abstract computing machine moving through its limitless memory, learning and predicting from previous patterns. While this may be considerably different to the software hitting the market today, the concept of a machine that is able to learn, modify or improve without being explicitly programmed to do so, is the essence of all AI.
The rise of AI
While the idea of AI may have existed for nearly a century, the more widely recognised applications of AI and Machine Learning techniques were developed around a couple of decades ago. At the time, computing power and storage was an extremely expensive commodity meaning that high-powered computing could mainly only be explored by professionals in the computing field and those with access to specialist machines. As the prevalence of devices and internet connection skyrocketed in the late 90s and early 2000s, and the cost of processing and data storage dropped, the ability to handle big data sets within the average professional or even personal computer environment became more of a reality.
This coupled with developments in sensor technology, which enabled better data collection and situation awareness, an increase in data available online, and the rise of cloud and edge computing methods, saw a simultaneous increase in the need to process more data, faster, and a desire to have machines take on the burden of many human activities.