Deep learning, artificial intelligence and machine learning, what’s the difference? All three terms are increasingly used in business, sometimes (albeit incorrectly) interchangeably. Business, technology and the effective use of data are big news with an explosion of interest in all things AI over the past few years. So how can you cover the basics and have an intelligent conversation about it? We give you the skinny.
Artificial Intelligence (AI)
AI was the forerunner to machine learning and deep learning. Birthed at the Dartmouth Conferences in 1956 by computer scientists. The original scientists coined the term to describe scenarios where computers were tasked with problem solving normally associated with human intelligence. Think of AI as the trunk of our technology tree, closely followed by the branches of machine learning.
Examples of AI: Drones, computer diagnosis, IBM’s Watson (more on that little fella in another blog), search engines.
Machine learning
Machine learning uses algorithms to ingest data, learn from it and make predictions. Machines are able to consume large amounts of data, to learn at a rate that far outstrips human learning. Way back in 1959, Arthur Samuel described machine learning as “The field of study that gives computers the ability to learn without being explicitly programmed.”
Examples of machine learning: Image tagging, spam filters, data mining, video games and robotics.
Deep Learning
The leaves on our tech tree and responsible for quantum leaps in the field. Deep learning, sometimes called deep neural networks, is quite literally changing our world. This is another approach using algorithms originating from the early machine learning. Now the vanguard, deep learning was inspired by and modelled on the advances and discoveries of neural networking within the human brain. It didn’t stop there. Scientists layered neural networks to include massive data assimilation and autonomous self teaching. That’s right, they’re teaching themselves.
Examples of deep learning: Used by MIT to predict the future, Google’s voice recognition, the navigation of self driving cars, precision medicine, Siri, Alexa, Google translate, image recognition.
