AI at the edge: Powerful devices, greater storage

Artificial Intelligence (AI) is continuing its journey from being a mere pipe dream to a tool used by millions of businesses and consumers across the globe. This technology already has many, varied use cases, which have numerous benefits including improving productivity, enhancing analytics and automating some manual tasks.

AI can be generated at the edge, in the cloud or at data centers. However, technology advancements and innovations will likely embed or put AI directly onto more end devices, like phones, tablets, laptops and sensors. With this will come numerous challenges that businesses must be aware of and address accordingly.

As these technologies come together, they will impact the architecture at the edge, and what is required from data storage. More specifically, they will drive a demand for specialized storage.

Understanding Embedded AI

While embedded AI technology on devices at the edge is relatively new, it is becoming increasingly common and will likely grow rapidly. It’s an exciting concept, as by transitioning away from the network core, embedded AI applications will become even faster and more useful, further enhancing AI’s use cases and capabilities.

Rather than just being a tool individuals can leverage on their devices, embedded AI systems will be able to better interact with the environment, analyze data in real time, make intelligent decisions and perform complex tasks without connectivity or cloud-based computing.

By switching to AI-embedded devices, response times will be shorter, while safety and operational efficiency can be improved. This will be transformational in health care, manufacturing, transport and entertainment. The functions of an AI-powered device can be performed almost instantaneously rather than having a delay by performing computing in the cloud or data center.

Embedded AI in Action

In smart vehicles, embedded AI is being used to detect congestion and obstacles in the road. For self-driving cars, these insights are used to keep passengers safe without input from a human driver. By speeding up the reaction of the AI-enabled vehicle, the automatic braking system is more likely to be approved for road use as it will likely be more responsive to potential hazards on the road.

To read the complete article, visit IoT World Today.