Looking at future AI trends
The majority of industry leaders are now aware of the limitations of centralized ML as discussed in the next section.
The limitation of centralized ML
When looking at the future of AI, it is important to first know the fact that many companies today are struggling to extract intelligence and obtain insight from the data they possess. More than half of the data that organizations and companies have collected is usually not used. Traditional approaches to machine learning and data science need data to be organized and consolidated into data lakes and stores in advance of analyzing and training ML models. You need to duplicate and move the data, which will result in delays in realizing and delivering the value of the intelligence extracted from the data, together with certain operational risks and complexities.
In addition, most of the data generated by enterprise companies will be created and processed outside a traditional centralized data center...
