Bundle designed for ML developers to rapidly evaluate, prototype, and demonstrate computer vision edge ML applications with increased performance
SiMa.ai, the machine learning software-driven company with purpose-built hardware to deploy AIML applications at the edge, announced the launch of a new SiMa.ai MLSoC Development Kit with our latest release of SiMa.ai Palette software. The MLSoC Development Kit empowers developers to compile and evaluate their machine learning (ML) models in hours and create proof-of-concept use cases in days. The development kit operates as a stand-alone platform for demonstrations and seamlessly transforms into a PCIe card for effortless integration into desktop and industrial PCs.
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Developers will reduce their ML model evaluation effort to allocate more time to enhance their models. The Palette 1.1 software provides real time Key Performance Indicators (KPIs) that help developers make iterative improvements to their pipelines. When the pipeline meets functional requirements, the developer can optimize their implementations based on GStreamer for production deployments. Edge ML processing power is scaled via PCIe in deployed PCs and servers to expand multi-camera, real time streaming capacity.
Out of the box, the kit includes a development board, Palette 1.1 software, and essential cables. The development kit provides options for a pre-configured e-con Systems ethernet camera, SiMa led onsite or virtual service that is tailored to meet the needs of developers at any stage of their edge ML development journey. ML developers can use the development kit for many use cases such as people detection, tracking and human pose estimation. For example, the people detection use case addresses occupational safety to ensure workers comply with protective equipment requirements.
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“SiMa.ai is focused on delivering an out of box solution that elevates the ML developer user experience,” said Elizabeth Samara-Rubio, Chief Business Officer at SiMa.ai. “Helping them innovate and deploy models to production in less time.”
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