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To run neural networks efficiently at the edge on mobile, IoT, and other embedded devices, developers strive to optimize their machine learning (ML) models' size and complexity while taking advantage of hardware acceleration for inference. For these types of devices, long battery life and thermal control are essential, and performance is often measured on a per-watt basis. Optimized ML models can help achieve these goals by reducing computations, memory traffic, latency, and storage requirements while making more efficient use of the hardware.
How many times have you said, “If I had a drone with 5G, seven-camera concurrency, 8K video and 15 TOPS of processing, I could . . .”
Whatever you’ve told yourself you could do with features like those on a drone, you can stop wishing it and start inventing it. The Qualcomm Flight™ RB5 5G drone reference design is now available for pre-order from ModalAI.
Introduction
Open Radio Access Networks (Open RAN) is a hot topic in the cellular industry. It involves the development of interoperable open hardware, software, and interfaces for wireless cellular networks. The time seems to have come for traditional cellular network operators to look at new ways to spur innovation, adopt interoperability, and lower costs. In this blog post, we’ll look at the fundamentals of Open RAN that developers should be aware of, what is driving its adoption, the trends driving growth, and how current leadership is helping to deliver success.
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