AI on EDGE -The future of Artificial Intelligence.

EDGE AI

In recent years, applications of artificial intelligence have improved in various organizations worldwide. With more corporate activities at work, cloud computing became a central part of AI evolution. As customers use their devices for longer, companies become more aware of the need to bring essential computing to the device to serve more customers.This is why in the next few years the market for edge computers will continue to accelerate.The marketing of the Edge Computing is projected at 1,12 trillion by 2023.

Edge AI means that AI algorithms are being processed locally on a hardware device. Algorithms use data (sensor data or signals) that are generated on the device.The device that uses Edge AI does not need to be connected in order to work properly, it can process data and make decisions independently without a connection.To use Edge AI, you need a device that includes a microprocessor and a sensor.

Machine learning Algorithms running on embedded system

As u can see above, what you’re seeing now is the Edge AI where machine learning algorithms are run locally on hardware devices or embedded systems compared to servers. Depending on the AI application and device category, there are different hardware options for performing AI edge processing such as CPUs , GPUs, ASICs, FPGAs and SoC accelerators.

Why is Edge AI important?

Edge AI will allow real-time operations, including data creation, decision-making and action where milliseconds matter. Real-time operations are important for self-driving cars, robots and many other areas. Reducing power consumption and thus improving battery life is of great importance for wearable devices. Edge AI will reduce the cost of data communication because less data will be transmitted. By processing data locally, you can avoid the problem of streaming and storing a lot of data to the cloud that makes you vulnerable from a privacy point of view

Edge AI is the NEXT Wave of AI !!

In the last few years, the implementation of artificial intelligence in different companies has changed around the world. As more enterprise-wide efforts dominate, cloud computing has become a key component of AI evolution. As customers spend more time on their devices, businesses are increasingly aware of the need to bring essential computing to the device to serve more customers. That is why the Edge Computing market will continue to accelerate in the coming years. Edge Computing is projected to reach 1,12 trillion in marketing by 2023.

Large cloud companies are offering Edge Computing services to prepare for this. Intel and Udacity have just launched their program to train 1 million developers worldwide.

According to Gartner, 91% of today’s data is processed in centralized data centers. But by 2022, about 74% of all data will need analysis and action on the edge.

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