AI is everywhere. It’s in our homes, our mobile phones and of course, our search engines.
With Google confirming the rollout of its AI system RankBrain in 2016, the time has come for us in the digital marketing industry to acquaint ourselves with AI – we can’t beat the machines guys, so we better join them.
This article will cover some useful buzzwords that will no-doubt become increasingly prolific as the age of AI ushers in.
You’ve heard this word floating around for years but be honest, do you (and I’m talking to the non-techy professionals in the industry) actually know what one is?
An algorithm is a set of rules or a formula for solving a problem by performing a sequence of predetermined instructions. In a search engine’s case (such as Google) the algorithm is used to determine the most relevant webpages for a particular search based on a closely guarded formula that know one knows apart from us at it Works Media (I’m only joshing ya! But we do have a pretty good idea…).
Fuelling the AI explosion is ‘Big Data’. We now produce more data in one minute than we did from the beginning of time to year 2000. Now let that sink in for a second. Big Data is a term used to describe how we analyse these huge volumes of data in order turn information into useable knowledge. Businesses are using Big Data to better understand and predict customer behaviour as well as improve business processes.
The ability of machines to perform tasks in a way that we would consider ‘smart’. Until the field progresses, the applications of AI that we commonly see today are classed as ‘Narrow AI’ i.e. technologies that can perform specific tasks as well as (or even better than) a human. For instance, face recognition on Facebook is Narrow AI, whereas ‘General AI’ is the equivalent to Star Wars’ C-3PO. But where does this intelligence come from? Machine learning.
A form of AI in which machines are given access to data and then teach themselves. So, rather than manually coding software routines with a specific set of instructions to accomplish a particular task, the machine is ‘taught’ using large amounts of data and algorithms to do the task itself.