Open up any technology article these days and you will find mention of Artificial Intelligence in one or another shape or form. The reference will either be touting one of the amazing benefits we experience with using AI or it will be a doomsday prediction, highlighting the eventual outcome of our AI overlords ruling over us.
The reality is however, that the majority of the AI that we experience today is actually Machine Learning. A smaller subset of the group of technologies known as AI.
Several definitions have been given by Techemergence. All of which display the common thread of learning from data and providing an improved outcome.
“Machine Learning at its most basic is the practice of using algorithms to parse data, learn from it, and then make a determination or prediction about something in the world.” – Nvidia
“Machine learning is the science of getting computers to act without being explicitly programmed.” – Stanford
“Machine learning is based on algorithms that can learn from data without relying on rules-based programming.”- McKinsey & Co.
“Machine learning algorithms can figure out how to perform important tasks by generalizing from examples.” – University of Washington
“The field of Machine Learning seeks to answer the question “How can we build computer systems that automatically improve with experience, and what are the fundamental laws that govern all learning processes?” – Carnegie Mellon University
So this begs the question of why is this receiving such heightened awareness at the moment? The answer is, machine learning used to be the domain of scientists and academia. This is no longer the case as cloud computing has made this accessible to any company large or small. The tools that have been developed have increased the ease of use of machine learning. As such, it is no longer the sole domain of the scientist but has crossed into the realm of business. Machine learning touches industries spanning from government to education to retail to health care. It can be used by businesses focused on marketing, social media, customer service, driverless cars, and many more. It is now widely regarded by many people in business as a core tool for decision making.
Business applications of machine learning are numerous, but all boil down to one type of use: Processing, sorting, and finding patterns in huge amounts of data that would be impractical for humans to make sense of.
The key to good machine learning is most definitely in the data. One needs not only sufficient data but also good quality data. This is certainly a case of “garbage in = garbage out”
“Machine learning can’t get something from nothing…what it does is get more from less.” – Dr. Pedro Domingo, University of Washington
Even when you have sufficient data, two large issues in machine learning still remain. These involve overfitting (in which the model exhibits bias towards the training data and does not generalize to new data, and/or variance i.e. learns random things when trained on new data) and dimensionality (algorithms with more features work in higher/multiple dimensions, making understanding the data more difficult).
As companies realise that the quality of their data impacts the results they will see from machine learning, they are now redesigning their business processes and data capturing in order to be able to take advantage of this technology in a few years’ time (once they have sufficient data).
Machine learning can provide insights ranging from better traffic flows, to enhanced shopping experiences. The benefits range from saving you money, to saving your life. There is no doubt in my mind that machine learning touches most of us every single day, without us even being aware of it.
If you are new to this realm of machine learning and would like to learn more, catch our next blog post which will have some recommendations for learning more.
Kaskade can assist you on your Machine Learning journey. Why not chat to us today to learn how you can implement a simple solution into your business to receive great returns. For more information or to book a consultation email email@example.com
Kevin Derman is Chief Executive Officer for Kaskade.cloud. He is a Certified AWS Solutions Architect – Associate, Key Note Speaker, and a Human Potential and Technology Evangelist.