Tagged with

edge processors

Latest Articles (10+)

Featured

A short guide to understanding the edge neural network design.

Neural Network Architectures at the Edge: Modelling for Energy Efficiency and Machine Learning Performance

Semantic-based neural network ontology for TinyML that faces challenges discovering appropriate combinations and initiating deployment.

An industrial perspective for managing TinyML models and IoT edge devices at scale

Over the last decade, deep neural networks have emerged as the solution to several AI complex applications from speech recognition and object detection to autonomous vehicular systems.

How to simplify the inputs for better neural network performance?

A system with an opto-chemical sensor combined with a battery-free NFC tag of resolution 103 ppm for measuring the CO2 gas concentration in the dead space volume of the facemask

Wearable and Intelligent Face Mask for CO2 monitoring

FaceBit aims to be low-cost, energy-efficient, and easy-to-integrate hardware with rich sensing functionalities– monitors physiological signals

Smart Face Mask Platform in Response to COVID-19 Pandemic

Heterogenous analog in-memory compute architecture integrating 8 RISC-V cores along with an IMC accelerator and depth-wise digital accelerator.

Improvement in Energy Efficiency for Heavy DNN Workloads on Edge Devices

A rich line-up of speakers discuss the trends and challenges of the industry.

From AI and beyond: Highlights of the Linley Fall Processor Conference 2021

Supporting smart audio innovation.

The Knowles AISonic™ Hardware Grant

Utilizing audio edge processors for efficient execution of Machine Learning Tasks.

An engineer's guide to deploying machine learning in smart devices using audio edge processors

A closer look at the recent market trends and audio technologies that enhance the functionalities of TWS devices.

TWS Evolution: What is next in True Wireless Audio?

Making the leap from “Smart” to “Useful”. Smart home devices will continue to increase their utility as the challenges of audio source classification are solved by audio edge processors specifically designed for advanced audio and machine learning applications.

Enhancing the utility of Audio AI in everyday devices using Audio Source Classification

#4 of our 'Voice of Innovation' fireside chat series, in which Syntiant CEO Kurt Busch talks with Andreas Urschitz Division President Power & Sensor Systems at Infineon.

Fireside Chat With Andreas Urschitz from Infineon

Supporting the next generation of audio and IoT products.

Knowles Hardware Grant

Dedicated audio edge processors with machine learning will deliver increasingly natural communication experiences.

Audio edge processors deliver sublime context-aware communication experiences

Wevolver 2022