For the data-centered, insights are everything - improving
efficiency, profitability and increasing revenue - ultimately
giving your organization a competitive edge. Data is the key
to unlocking insights driving automation. The challenge for
many organizations is finding the resources that best enable
their Analytics and AI strategy in the midst of all the noise
that exists today.
Let's begin with what AI means and what it means to
businesses. AI is the simulation of human intelligence by
computer systems. And increasingly, in a wide range of
industries, organizations are using AI to increase business
AI is implemented in two phases - Training or model
development, which is the process whereby data scientists
develop and optimize models with a curated dataset - and
inferencing, which is applying a trained model to new data
to derive insights and enable automation.
Here is where the other two buzzwords of Machine Learning
and Deep Learning come into the picture. While they seem
to be used alongside AI, and sometimes even
synonymously, each of these terms has a specific meaning,
a connotation, and a business case.