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Edge AI: Making smart choices for smarter devices
We explore the benefits of Edge AI and how to get started.
The Edge AI Software market is forecast to grow from $355 million in 2018 to $1.12 trillion dollars by 2023. Edge AI is the combination of Edge Computing and Artificial Intelligence. Machine Learning (ML) algorithms are processed locally on an edge device rather than in the cloud or remote data centre.
The algorithms use the data generated by the devices themselves, enabling them to make decisions in a matter of milliseconds. There are almost no limits to the potential uses of Edge AI from smart vehicles, homes, devices, building, cities, manufacturing and more.
Transferring data to the cloud and back to the device takes time. Edge AI eliminates the latency, particularly important for applications that require much quicker response times, such as in smart vehicles.
With less data moving back and forth to the cloud, there are less chances of data being hacked. Using a closed network makes this even harder for criminals to crack.
Edge AI enables almost real-time analytics, taking a fraction of a second. For time critical situations this can be crucial and potentially lifesaving.
With the growth in connected IoT devices expected to generate 79.4ZB of data in 2025, Edge AI will ensure there isn’t a hold-up when it comes to data transfer, ensuring scalability.
In this rapidly evolving landscape, understanding the trade-offs between the many opportunities is essential. We can support you whatever your current stage of development.
Our experience of designing and developing edge devices for the home and other environments, can help you navigate the technology landscape from chip to cloud. This experience includes:
Our thoughts, ideas and views as well as in-depth technical papers. Explore our insights and deliver your secure connected devices and systems to market faster.
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