Reality, as we know it, has become fragmented. That’s not necessarily a bad thing so stick with me for a moment. Something becomes fragmented when specific elements within it acquire sufficient weight to exist on their own forming, in the process, entire worlds as deep as the parent they split away from.
Machine learning is a term that’s so widely used in so many different fields of science and technology at the moment that knowing a few things about it will help demystify much of the confusion surrounding it. The questions below form a good basic introduction to the subject.
In the 1967 episode Arena, Captain Kirk is whisked off to a distant planet to battle a creature never encountered before by humans - a Gorn. Even during the somewhat uneven battle between Kirk and the …ahem, evil-looking reptilian creature, there is an instant translator that allows the two species that have never met before to talk to each other.
There is a gap which businesses bridge that can be truly transformative. I figuratively call it “the last mile”. Running a business is a marathon in the fullest sense of the word. It requires preparation, planning, endurance, strategy, skill, focus, smarts and analysis. There has to be a willingness to take the rough with the smooth and still come out ahead.
When the Spinning Jenny was invented the world didn’t change. Yes, many people lost their jobs, the social fabric of the time collapsed for a large segment of the population and a popular, anti-technology movement was formed in the Luddites. But none of that was of a sufficiently large scale or lasted long enough to create a lasting impact.
Machine Learning is slated to be as disruptive and revolutionary as the internet when it was first introduced so it’s time perhaps to visit the subject in as non-technical a manner, as possible, and unpack some of the terms that are conflated when it comes to it. For a quick introduction to machine learning and deep learning (and what the latter means) you should perhaps visit my article on it at Plus Your Business.
In 2016 we hardly need to be told that the web has a truth problem. Facebook is still considering ways to combat fake news, Google is still grappling with veracity in semantic search, experimenting with Knowledge Based Trust (KBT) as a means of ensuring that search is as reliable as possible in its answers.
Whether you are selling soap or news the key to capturing market share lies in the ability to capture attention. The ability to capture attention requires just one ingredient: relevance.