Lattice Blog

Meeting Demand for More Intelligence at the Edge

Meeting Demand for More Intelligence at the Edge

Posted 08/21/2018 by Deepak Boppana

Over recent decades system design has evolved from one processing topology to another, from centralized to distributed architectures and back again in a constant search for the ideal solution.

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AI / Machine Learning

Inferencing Technology Stack Shrinks Time-to-Market for Edge Applications

Posted 06/12/2018 by Deepak Boppana

New Technology Promises to Accelerate Deployment of Machine Learning Inferencing Across Mass Market, Low-power IoT Applications

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Mobile-Influenced FPGAs Going Broad

Mobile-Influenced FPGAs Going Broad

Posted 04/17/2018 by Hussein Osman

The complexity of implementing intelligent Edge solutions is causing many issues for designers, including accommodating devices with new and legacy interfaces in a variety of applications. Some of these applications also require compute engines capable of processing data collected at low power and cost.

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CES 2018

CES 2018: Enter the Era of Intelligent Edge Devices

Posted 01/23/2018 by Elena Champion

Were you impressed by the products and technologies showcased at CES 2018? This year’s event promised to “WHOA” attendees with new gadgets from industry giants and startups alike. From the slightly odd to the “where have you been all of my life” devices, this year’s CES focused on infusing intelligence into as many aspects of our lives as possible.

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Implementation of Artificial Neural Networks at the Edge

Implementation of Artificial Neural Networks at the Edge

Posted 07/05/2017 by Hussein Osman

Imagine private security systems that can differentiate between an intruder and your neighbor’s dog, smart TVs that can scan the room and automatically turn off when no one is present, and cameras that can perform forensic analysis and identify suspicious behavior before a crime occurs. The applications for deploying artificial neural networks at the edge are endless. Coming up with ideas is easy, but getting to the implementation is not that simple.

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