For our final blog in this series about the myths and misconceptions surrounding machine learning, we’re looking at how machine learning can set your business up for long-term success. And to do that, we all need to lay to rest a misconception that’s all too often attached to machine learning -- the belief that machine learning technologies will naturally improve as we throw more data at it. This isn’t the case. Not at all.In reality, this is almost always the opposite of the truth, as we see in the report “Shatter the Seven Myths of Machine Learning,” by Kjell Carlsson, Ph.D. of Forrester Research, a leading advisory and research firm that works with business and technology leaders. The report, which we’re offering at no cost, shows how your business’ AI efforts can’t rely on machine learning to do the work itself.If left unattended, learning models are likely to become less accurate over time. That’s why you have to retrain your machine learning models as months and years go by and as your business grows, your goals change, and your customers’ needs evolve. Sure, your machine learning model may work for a while, but it will soon become, as the report says, “frozen in time when it is deployed and will inevitably degrade.”