The Open Analytics Blog
From platform to product?
Over the past 20 years, we have seen the growth of “platform economies of scale,” which have led to a transformative business environment and changes in global economic wealth. Companies have been typically competing on products. Yet platforms generate move value. Platforms can create multiple revenue streams, while products typically generate just one. Of the
Nimble application framework with cross-platform support
With the release of Megh VAS 100 comes a new addition to the Megh Computing solution stack: the Nimble application framework. Nimble is a fast and lightweight service-based framework for implementing CPU, GPU, and FPGA video analytics pipelines. As illustrated below, Nimble sits on top of Arka, Sira, and Deep Learning Engine (DLE), enabling seamless
Data streaming with Arka runtime APIs
The Arka runtime is Megh’s data streaming framework. Arka enables applications to build custom data pipelines spanning multiple devices and accelerators. Low-level details are abstracted away by Arka’s resource manager, which maps an application’s pipeline request to the pool of available hardware. This technology enables low-latency, low-overhead data streaming over complex functional topologies through Arka’s
Megh’s Deep Learning Engine usages
Video analytics use cases Enterprise users are increasingly interested in implementing complex video analytics use cases that provide business value beyond typical applications. These involve multi-stage models for object detection and image classification with custom trained models that are integrated to solve business problems. Some examples include: Segment Use case Deep learning tasks Retail Cashier-less