AI has become ubiquitous today from personal devices to enterprise applications, you see them everywhere. The advent of IoT clubbed with rising demand for data privacy, low power, low latency, and bandwidth constraints has increasingly pushed for AI models to be running at the edge instead of the cloud.
With new-age technologies, customers now have higher expectations from their vehicles than ever before. Many are more concerned with in-car interfaces than with aesthetics or engine power. The majority of drivers desire a vehicle that makes their lives easier and supports their favorite smartphone apps.
Machine Vision has exploded in popularity in recent years, particularly in the manufacturing industry. Companies can profit from the technology's enhanced flexibility, decreased product faults, and improved overall production quality. The ability of a machine to acquire images, evaluate them, interpret (the situation), and then respond appropriately is known as Machine Vision.
With new-age technologies like the Internet of Things, Machine Learning, and Artificial Intelligence, companies are reimagining and creating intelligent multimedia applications by merging physical reality and digital information in innovative ways. A multimedia solution involves audio/video codec, image/audio/video processing, edge/cloud applications, and in a few cases AR/VR as well. This blog will talk about the software infrastructure involved for an embedded video processor core in any multimedia solution.
Edge AI is the combination of edge computing and edge intelligence to run machine learning tasks directly on end devices. It generally consists of an in-built microprocessor and sensors, while the data processing task is completed locally and stored at the edge node end. The implementation of machine learning models in edge AI will decrease the latency rate and improve the network bandwidth.
Private, public, or hybrid, cloud solutions for any business domain are designed to provide the freedom to grow and security for the organization and customer data.
This article will provide a high-level overview of how verification of any SOM or any carrier card we call a development kit, need to go through different verification and validation before handing off new solutions to end-user as per their product requirement and how they can contribute to the success of any automated testing process.