Ensembles like Random Forest, Deep learning algorithms make the matter worst in terms of explaining the outcomes of decision even though these models produce more accurate results. However, there are challenges in this area of explaining predictions or decisions made by machine learning model.
We need to know how they make decisions to trust the systems powered by these models. Machine learning models are used to make the important decisions in critical areas such as medical diagnosis, financial transactions.
Purpose: When Artificial Intelligence is penetrating every walk of our affairs and business, we face enormous challenges and opportunities to adopt this revolution. Finally, some technical challenges and open issues are summarized to fully exploit the benefits of the Internet of intelligence. Moreover, we discuss the critical applications and their integration with the Internet of intelligence paradigm. We then present the layered architecture to characterize the Internet of intelligence systems and discuss the enabling technologies of each layer. Specifically, this paper starts by investigating the evolution of networking paradigms and artificial intelligence (AI), based on which we present the motivations of the Internet of intelligence by demonstrating that networking needs intelligence and intelligence needs networking. This can provide a good foundation for those who are interested to gain insights into the concept of the Internet of intelligence and the key enablers of this emerging networking paradigm. This paper provides an overview of the Internet of intelligence, focusing on motivations, architecture, enabling technologies, applications, and existing challenges.
The Internet of intelligence is conceived as an emerging networking paradigm, which will make intelligence as easy to obtain as information.
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