You might have heard people talk about artificial intelligence and machine learning when they talk about advancements in technology. It can be helpful to understand more about what they mean and what is the difference between them. It’s also beneficial to know how they work in relation to business applications.
Understanding the two concepts and how they could propel your business towards future success is critical. Here, ebb3 take a look at the difference between artificial intelligence and machine learning.
What is Artificial Intelligence (AI)?
Artificial intelligence is often recognised as human-like intelligence exhibited by a machine, including a computer or robot. This kind of technology allows a machine to mimic human abilities, including making decisions and solving problems. For a long time, artificial intelligence was something that was fantasised about in films, and now it is something that is used every day.
One of the best-known definitions of artificial intelligence comes from a former Dean of the School of Computer Science at Carnegie Mellon University. He declared AI to be “the science and engineering of making computers behave in ways that until recently, we thought required human intelligence.”
AI has become recognisable for being a developing and moving target that is aspirational for computers to have capabilities that humans possess, but machines do not. AI is now a term that covers the numerous technological advances that have become part of our daily lives. Machine Learning (ML) is one of the advances covered under the AI umbrella. AI is also a definition that evolves and grows as our ability to move technology forward grows. Cutting edge technology is only cutting edge until something better replaces it.
What is Machine Learning (ML)?
Tom Mitchell, a computer scientist and machine learning pioneer, defined machine learning as “the study of computer algorithms that allow computer programmes to automatically improve through experience”. With that in mind, machine learning is the process of examining and comparing datasets to find common patterns and nuances. ML is one way of allowing AI achievement and has become recognised as a branch of AI as a result.
Machine learning is split into three main areas, each of which can be invaluable to a business’ processes and operations. The first is supervised learning algorithms, which try to model relationships and dependencies between the input features and the target prediction output. The machine then uses what it learns to predict output values for new data.
The second area is unsupervised learning algorithms, which tend to be used in descriptive modelling and pattern detection as they do not have labels on the output categories or the data.
The third and final area is reinforcement learning, which uses environmental observations to take actions that minimise risk. The machine will constantly learn from its environment through iterations, such as a computer beating a human playing a computer game.
MI concerns itself with neural networks and deep learning in a way that aims to mimic how the human brain works. Of course, there are essential differences, but it is undoubtedly technology that hasn’t yet reached its full potential, and you will undoubtedly hear people talk about ML and AI for some time yet!
How Businesses are adopting AI and ML
AI and ML are fuelling immersive technology growth to assist businesses to realise massive productivity gains. Cost savings can be made, and customer experiences enhanced as machines seek to reduce the human element behind many processes. VDI/Workspace multi-purpose platforms enable digital transformations, which are sure to become key to business success no matter the industry you operate within.
