AI and Machine Learning
For as long as I can remember, IT Sales has always been about three words: Product, Product, Product. Technology was evolving at such a rapid pace, that you didn’t even have to wait for something to be End of Life anymore because the new shiny product did “oh so many.
As Robotic Process Automation (RPA)/Artificial Intelligence (AI) technology continues to progress both in capability and scope, businesses are expanding their use beyond MainFrame/Legacy/Desktop/Web Applications into the realm of Citrix/Virtualized environments in an effort to offset costs whilst increasing productivity. However, every RPA Developer who has created an automation in a.
Talk to a machine learning expert about implementing anything and they will say, we need to “train” the system first. What they usually mean is that the system will be fed known inputs and outputs and once trained considerably the model should be able to predict an output, given an.
Machine learning and Artificial Intelligence are rapidly moving from the realm of research to business and consumer application to power critical functions of businesses like Google, Facebook, and Amazon. AI can generally be defined as “software that perceives its environment and adapts to new information, predicts outcomes to make decisions.
Machine learning and AI are very rapidly moving from the realm of research to business and consumer applications. It already powers many critical functions of large business like Google, Facebook and Amazon. AI can generally be defined as “software that perceives its environment and adapts to new information, predicts outcomes to make.
An undeniable fact is that every company is trying to find a quick, straightforward way to get an edge in their market. While there are a lot of solutions claiming to have the “Silver Bullet” of seamless automation, the major holdup, even more then money, is the sheer amount of time.