Artificial intelligence (AI) and machine learning have quite the reputation. Despite the science fiction association, many believe that every organization from the largest to the most local are turning over processes and decisions to AI. ZDNet brought this information to our attention in their article, “‘Learning’ is still the operative word in machine learning initiatives.”
This just simply is not true. Many are still trying to figure out how AI and machine learning can fit into their operations. Companies may be increasing their investments in machine learning and machine learning development, but, for the most part, are still in the early learning stages.
While companies are increasing their machine learning investments, challenges ranging from model deployment to scaling and testing persist. Data science teams need to be able to deploy their work as quickly as possible to prevent their insights from being overcome by events. Models and data change quickly, as do market opportunities.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
