AI and ML:
Well known big data author Bernard Marr distinguishes between Artificial Intelligence and Machine Learning in this Forbes.com article from December 2016. He defines Artificial Intelligence as “the broader concept of machines being able to carry out tasks in a way that we would consider “smart” and Machine Learning as “a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves.”
A really compelling implementation of Artificial Intelligence is from a technology vendor named Narrative Science. They specialize in Natural Language Generation (NLG) which is subfield of AI. The solution transforms data into narratives and can be easily integrated into business intelligence solutions such as Qlik. Check out this slick demoand the product can be downloaded in pilot mode for free.
Machine Learning can be further broken down into “supervised machine learning” where the program is trained based on pre-defined examples versus “unsupervised machine learning” where the program is given data and it outputs patterns and relationships. Machine learning also covers areas such as classification, clustering and attribute selection. Check out this summary from Toptal if you are interested in going deeper.
Here are a few familiar and interesting real world examples of Machine Learning:
It’s undeniable that IoT, AI and ML are here to stay. The pace of innovation is staggering and things that seemed impossible just a few years ago can now be demonstrated and implemented with relative ease. My suggestion is embracing this new and exciting wave of technology innovation and seek ways to leverage it for your competitive advantage. Good luck!