AI GLOSSARY

Deep Learning

Deep learning refers to a particular type of modelling within machine learning whereby multi-layered neural networks are used to solve tasks. These deep neural networks can automatically learn representations from raw data, making them highly effective for tasks such as image recognition, natural language processing, and speech analysis.

Deep learning models have driven significant advancements in AI due to their ability to handle high-dimensional data and achieve state-of-the-art results in various applications. Deep learning began to take off in the mid-2000s, with a significant breakthrough around 2012. A key moment was when a deep neural network called AlexNet won the ImageNet Large Scale Visual Recognition Challenge (ILSVRC) in 2012 by a large margin. The use of GPUs to accelerate the training of deep networks played a critical role in this success.

Since then, deep learning has rapidly advanced, driven by the availability of large datasets, increased computational power, and improvements in neural network architectures.