Rtn Nikhil S Gurjar, President of Consulting Connoisseurs, the top management consulting firm, speaks of how organizations end up with faulty implementations of Machine Learning, Artificial Intelligence and Artificial Neural Network systems and how these need to be corrected procedurally.
The most common issues in such implementations is the absence of an understanding of the logic. Most situations can be easily solved if we eliminate the clutter of logic. Known logic elements and relationship types are important in this case (linear, quadratic, exponential, timelag, etc.). Modeling and simulation helps systems steer clear of this clutter.
The second is the schema that is being used. Often times, inadequate measurements lead to poor results. For instance, a fever is a symptom for multiple diseases. Hence, one needs to incorporate other parameters while deciding the usage of an automated differential diagnosis program.
Lastly, the architecture of the system needs to be proper to understand future use and the way data is handled.Modeling and simulation methods help optimize these elements, thereby reducing costs, improving efficacy and ensuring quicker RoI. For more details contact us.