Everybody is talking about machine learning and artificial intelligence. But what does this really mean and how do you find your way through the haze of buzzwords to start finding real value?
The buzz might be recent, but AI and machine learning are old news. In fact, in Pamela McCorduck’s book “Machines Who Think” (1979) she dates first mentions of AI back to the Ancient Greeks. Specifically, in 850BC in the poem “The Iliad” Homer writes about a Hephaestus, the god of fire, who was left crippled and cast out of Olympus. To survive on Earth, Hephaestus created artificial life to help him walk and find food.
As the field of mathematics developed over the centuries many applications were considered, however it was not until Alan Turing kicked off the computer age in the 1940s that artificial intelligence and machine learning most obviously moved out of mythology and into practice.
Turning wrote papers on “Intelligent Machinery” (1945) and “Computing Machinery and Intelligence” (1950), however the term “artificial intelligence” was not used until 1956 by American computer scientist John McCarthy when hosting a conference. Three years later in 1959, it is believed computer gaming pioneer Arthur Samuel coined the term “machine learning” in a paper about checkers
So, what’s with all the talk?
Looking at Google trends data, the number of people searching for “machine learning” has increased tenfold in the last ten years. Machine learning and artificial intelligence may not be new news, but in recent times they are clearly stirring up a buzz.
Companies have more data than ever before and in the age of the Internet of Things it just keeps growing. In fact, LinkedIn gains 120 new professionals every minute of every day and Google processes 40,000 searches every second.
Big data has become a byproduct of doing business. Processes and legal requirements can mean this huge volume of data needs to be stored and managed, which can be expensive and tiresome. Especially when not done properly.
But data doesn’t need to be an expensive waste product
With machine learning, data scientists can combine the power of computer programming and mathematics to create algorithms which sift through the haze of data to find actionable insight.
At Analytics8 our Advanced Analytics team doesn’t use the term “machine learning” just because we like the buzz. We use it to describe the tools, mathematics and methodologies that we employ to find patterns and predictors in data. That’s because we believe the buzz around machine learning isn’t being stirred up by the science, it’s the business value and insight that it drives.
For example, building a customer attrition model is fun, but useless unless the business can leverage the model to reduce attrition and increase customer stickiness. This could be through insights which drive decisions or automated actions. For example, a discount coupon which is triggered when a customer has been inactive for a number of days.
Stop talking, start doing
When the business value is put to the forefront, machine learning can turn data from a by-product to a strong source of incremental revenue. This means companies who employ machine learning and creative uses of cutting-edge technology are put at an advantage compared to their competitors.
To stay competitive, now is time to start thinking about ways (or more ways) you can leverage machine learning to gain value from your data.
Whether you have a well-managed data lake or feel like you are drowning with no idea where to begin, Analytics8 can help you to use machine learning to start driving value immediately. But the only way to get going is to stop worrying about the buzz and start letting your data do the talking – through the power of machine learning.
At Analytics8 our data scientists work closely with our data integration specialists so that we process and prepare your data to get started as quickly as possible.
We can help you to determine how machine learning could drive your business value, while ensuring we design the right methodology, testing and measurements for the greatest chance of success.
With a solid strategy and a will to get going, leveraging machine learning will take your organisation out of the haze of buzzwords and into a world of data driven value.
About the author: Lara Scharenguivel is a senior consultant in our Advanced Analytics team. Lara is a creative, insights-driven, data and analytics specialist with over 10 years’ experience leveraging data to drive business decisions. Lara has experience across multiple industries including airlines, education, finance and banking, and has worked on numerous high-profile bankruptcy litigations following the 2008 financial crisis. Lara’s latest post: Personalisation at scale.
Are you ready to maximise the value of your data, and leverage it to make meaningful business decisions? Talk to one of our Advanced Analytics consultants today.