The power of cloud computing has developed from data centers to the edge of networks. This edge is becoming as important as organizations across all industries which are dealing with large amounts of data, more complex operations, and more competitive markets. To meet business needs, hyperscale cloud providers, IT companies, and connectivity providers are transforming to edge computing and edge intelligence.
As communication between connected devices generates a huge amount of data, these need to be quickly processed and executed. It is reported that over 20 billion Internet of Things connected devices have already been installed. And this is predicted to reach 75.44 billion by 2025.
Edge computing comes out as a new model in bringing decentralized computing power as close as possible to the origin of the data. This allows a networking architecture to close the distance between connected devices and the cloud. With the advancement and the integration of AI, it is now approaching the intelligent edge, which communicates, generates, and assesses data in near real-time.
Powering Intelligent Edge Innovation
As innovations in cloud computing have got so much attention from the industry, the advancements at the edge are also becoming remarkable. As the deployment of the intelligent cloud and intelligent edge application patterns are now giving new ways for businesses to interact with digital information and the physical and digital worlds for greater benefit and customer innovation.
With the help of a database management system, the intelligent edge can help with network performance, minimization of threats through security approach, improve accuracy, and maintain compliance through consistent app development across cloud and edge. This also helps the businesses to gain clearer visibility into their physical operations with the help of AI to handle more high-demand tasks autonomously.
Intelligent Edge – The Future of AI
AI technology has already taken someplace, and it will soon be everywhere. Its applications in recent years have improved vastly, transforming from smartphones to personal assistants and recommendation systems to video/audio surveillance. The adoption of AI is a key enabler of edge networks. With the increase in chips that are specialized and optimized to run AI and ML tasks are moving into edge appliances. The combination of specialized chips and AI capabilities makes the edge intelligent.
