Services Category: AI/ML

Qualcomm® QRB5165 – A Game-changer for Next-gen IoAT Device
Blog
Nikunj Patel

Qualcomm® QRB5165 – A Game-changer for Next-gen IoAT Device

AI-enabled Internet of Autonomous Things (IoAT) devices including autonomous machines, vehicles, robots, and drones can think for themselves using capabilities like machine learning, computer vision, and self-governing navigation – thanks to hardware innovations. Let’s see how power-packed robotics-specific Qualcomm® QRB5165, eInfochips Edge Labs, and Aikri portfolio can be game-changers for developing these Autonomous Things (AuT) devices for a wide array of applications across industries – from manufacturing and logistics to retail and healthcare.

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AI/ML Engineering Services
Brochure
eicnew

AI-ML Engineering Services-Brochure

Brochure – AI adoption is increasing across retail, manufacturing, medical devices, transportation and logistics, smart cities, utilities and consumer electronics….

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AIoT in Smart Water Management
Blog
Nirupam Kulkarni

AIoT in Smart Water Management

Effective water management, conservation, and equitable access to water are key to sustainable development across the globe. Governments and regulatory authorities worldwide have defined action plans for achieving UN’s collective sustainable development goal 6 (SDG6) – ensuring water and sanitation for all. It covers systems for smart metering, equipment monitoring for distribution, purification, heating, and cooling. Digital technologies like IoT, AI/ML, Cloud, and mobility are seen as key enablers in designing and monitoring the systems for achieving this goal.

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Building Intelligent Audio Systems- Audio Feature Extraction using Machine Learning
Blog
Rhishikesh Agashe

Building Intelligent Audio Systems- Audio Feature Extraction using Machine Learning

Given the recent trends in machine learning and deep learning, we have tried to give a high-level overview of how digital signal processing, machine learning, and deep learning algorithms can go hand-in-hand to categorize or draw inferences from audio signals. Audio-specific neural network models can also be built using signal processing, machine learning, and deep learning (neural networks) algorithms. In this blog will see how to build Intelligent Audio Systems, Audio Feature Extraction using Machine Learning.

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