Artificial Intelligence (AI) is the hot topic of the moment in technology, and the driving force behind most of the big technological breakthroughs of recent years.
In fact, with all of the breathless hype we hear about it today, it’s easy to forget that AI isn’t anything all that new. Throughout the last century, it has moved out of the domain of science fiction and into the real world. The theory and the fundamental computer science which makes it possible has been around for decades.
Since the dawn of computing in the early 20th century, scientists and engineers have understood that the eventual aim is to build machines capable of thinking and learning in the way that the human brain – the most sophisticated decision-making system in the known universe – does.
Today’s cutting-edge deep learning using artificial neural networks are the current state-of-the-art, but there have been many milestones along the road which have made it possible. Here’s my rundown of those that are generally considered to be the most significant.
1637 – Descartes breaks down the difference
Long before robots were even a feature of science fiction, scientist and philosopher Rene Descartes pondered the possibility that machines would one day think and make decisions. While he erroneously decided that they would never be able to talk like humans, he did identify a division between machines which might one day learn about performing one specific task, and those which might be able to adapt to any job. Today, these two fields are known as specialized and general AI. In many ways, he set the stage for the challenge of creating AI.
1956 – The Dartmouth Conference
With the emergence of ideas such as neural networks and machine learning, Dartmouth College professor John McCarthy coined the term “artificial intelligence” and organized an intensive summer workshop bringing together leading experts in the field.
During the brainstorming session, attempts were made to lay down a framework to allow academic exploration and development of “thinking” machines to begin. Many fields which are fundamental to today’s cutting-edge AI, including natural language processing, computer vision, and neural networks, were part of the agenda.
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