Various companies across almost every industry have been applying AI to solve complex problems and create more personalised experiences.

John McCarthy coined the term artificial intelligence back in 1956. However, it wasn’t until the ImageNet dataset collection that the field made a tremendous leap.

ImageNet originally had an academic objective to collect and map out a dataset of objects. It rapidly evolved into an annual challenge where teams would compete using algorithms to accurately recognise images.

In 2012, there was a defining moment – a team of researchers from the University of Toronto participated in the competition and submitted Alexnet – a deep convolutional neural network architecture that significantly outperformed the competition in identifying images.

The competition is seen as a primary catalyst in the field of AI. Since then, the application of AI has expanded to areas such as computer vision, natural language processing, voice recognition, among others.

In our daily routines, it is pretty easy to spot where artificial intelligence is at work. For example, Facebook and its image-tagging feature, recognising particular people, or Netflix’s highly predictive algorithm used to provide the film recommendations.

To gain more insights and understanding into artificial intelligence, we must first define what AI is. Afterward, we can distinguish it from other related terms such as machine learning (ML), neural networks (NN) and deep learning (DL).