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Edge AI

(Washington D.C., U.S.A.)


Edge AI: The Future of AI and Edge Computing


- Overview

Edge AI means that AI software algorithms are processed locally on a hardware device. The algorithms are using data (sensor data or signals) that are created on the device. A device using Edge AI software does not need to be connected in order to work properly, it can process data and take decisions independently without a connection.

AI relies heavily on data transmission and computation of complex machine learning algorithms. Edge computing sets up a new age computing paradigm that moves AI and machine learning to where the data generation and computation actually take place: the network’s edge. The amalgamation of both edge computing and AI gave birth to a new frontier: Edge AI. 

Edge AI allows faster computing and insights, better data security, and efficient control over continuous operation. As a result, it can enhance the performance of AI-enabled applications and keep the operating costs down. Edge AI can also assist AI in overcoming the technological challenges associated with it. 

Edge AI facilitates machine learning, autonomous application of deep learning models, and advanced algorithms on the Internet of Things (IoT) devices itself, away from cloud services.


- Edge AI Is The Next Wave of AI

Edge AI is the next wave of artificial intelligence (AI). detaching the requirement of cloud systems. Edge AI is processing information closer to the users and devices that require it, rather than sending that data for processing in central locations in the cloud.

In the last few years, AI implementations in various companies have changed around the world. As more enterprise-wide efforts dominate, Cloud Computing became an essential component of the AI evolution. As customers spend more time on their devices, businesses increasingly realize the need to bring essential computation onto the device to serve more customers. This is the reason that the Edge Computing market will continue to accelerate in the next few years.


- The Enterprise Distributed Edge and Edge AI

Edge AI and edge computing devices help many industries become more efficient and safer by improving accuracy and reducing human error through automation. Edge AI can significantly improve surveillance and monitoring while reducing the amount of raw data that’s transmitted to the cloud leading to the adoption of edge AI for video surveillance. With the advent of edge AI, ML intelligent camera systems can capture raw data, process, and analyze it using facial recognition to identify persons of interest and suspicious activities that may be occurring directly at the edge. 

We now see industries across the board tapping the potential of these edge computing devices to improve day-to-day life for everyone. Early adopters of edge AI and edge computing technologies include industries such as transportation/driverless vehicles, education, medical/healthcare, agriculture, manufacturing/factories, retail/shopping and video surveillance.



[More to come ...]

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