While the Internet of Things (IoT) is extending its reach in everything from the enterprise to the household, challenges around connectivity, latency, security, scalability and cost are encouraging the drive for edge computing. In the early 2000s, CPUs were in the mainstream. Advancements in the hardware and modules presented GPUs, FPGAs, and now ASICs – specialized chips dedicated to performing one operation. Such hardware evolution, when combined with data analytics at the device level, fuels developments for AI at the edge.
"91% of today’s data is processed in centralized data centers. But by 2023, about 74% of all data will need analysis and action on edge."
A device using edge AI employs AI algorithms locally to process and analyze data on a hardware device. Devices enabled with Edge AI can process data and take independent decisions without a connection. Edge processing makes data more relevant, useful and actionable by improving response times of connected applications. Companies need solutions at breakneck speeds to identify objects, count people in certain areas, ensure quality control in manufacturing and so much more. But the adoption of these technologies is not as easy as plugging devices together.
In this webinar, prepared for IoT and AI adopters, we provide you an insight into what Vision AI at the edge is and why it is the next goldmine. By attending this webinar, you will get to know the components required for edge processing. You will also understand the challenges, opportunities and roadmap in implementing edge AI. In all, through this webinar, you will be better prepared to ride the next technological wave.