Matthew BoyleSiMa, a leading developer of Machine Learning System on Chip (MLSoC) platforms, has teamed up with CVEDIA and Supermicro to pioneer smart city solutions for embedded edge systems. This collaboration aims to leverage SiMa.ai’s MLSoC platform, combined with CVEDIA’s artificial video analytics expertise and Supermicro’s edge appliances, to empower municipalities with high-performance AI/ML applications at the edge.
Elizabeth Samara-Rubio, Chief Business Officer of SiMa.ai, emphasizes the mission to deliver energy-efficient AI solutions with partners like CVEDIA, facilitating seamless integration and scalability for edge development challenges. CVEDIA’s library of AI-based video analytics solutions promises to enhance performance and cost-effectiveness for applications such as object detection, anomaly detection, and vehicle classification at the edge.
Driving Energy-Efficient Smart City Solutions with SiMa’s MLSoC Platform
Arjan Wijnveen, CEO of CVEDIA, underscores the collaboration’s significance in striking the optimal balance between performance and power, ushering in a new era of AI/ML solutions that advance value-added services and use cases.
SiMa.ai’s MLSoC platform offers scalability and efficiency, enabling multiple AI models to run concurrently with improved accuracy and overhead. This innovation enhances the capacity to handle multiple channels simultaneously while maximizing energy efficiency, setting new benchmarks for performance per watt (FPS/W) in edge computing.
Empowering Smart Cities with AI on SiMa’S Platform: A Collaboration with CVEDIA and Supermicro
Machine learning on a SiMa chip developer. To create smart city solutions for inserted edge systems, ai is working with CVEDIA and Supermicro. The companies will combine CVEDIA’s Artificial video analytics with Supermicro’s edge appliances, incorporating SiMa. ai’s Machine Learning System on Chip ( MLSoC ) platform.
The aim is to enable native municipalities to improve performance and cost of their applications such as object detection, anomaly detection, vehicle classification, and line crossing at the edge.
” SiMa. According to Elizabeth Samara-Rubio, Chief Business Officer of SiMa,” Ai’s mission is to help customers deploy high-performance AI/ML applications at the edge with a large bar for energy efficiency and ease of use with partners.” ai. ” We are pleased to introduce real-time AI/ML partner solution integrations like CVEDIA’s library of trustworthy, cheap AI-based video analytics solutions to the market that will enable customers to easily scale their AI/ML edge development challenges with one platform,” said CVEDIA.
Edge AI: CVEDIA and SiMa Redefine Performance and Efficiency
” Using the expertise of CVEDIA in SiMa and Intelligent Video analytics. We are excited to introduce an cutting-edge AI/ML solution that strikes the ideal balance between performance and power, according to Arjan Wijnveen, CEO of CVEDIA. The collaboration promotes a brand-new era of AI/ML solutions that optimize and scale the use cases and advance value-added services.
SiMa. Ai provides a platform for edge AI that can scale, from transformers to multimodal relational AI. The SiMa. With improved accuracy and overhead, the AI MLSoC enables several AI models to run concurrently on a second camera stream. It is intended to increase the capacity to run multiple channels at once while maximising efficiency by producing the highest frame rates per watt ( FPS/W ).
Driving Smart Cities Forward: SiMa.ai, CVEDIA, and Supermicro Collaborate for Enhanced Edge AI Solution
The collaboration between SiMa.ai, CVEDIA, and Supermicro represents a significant step forward in the realm of smart city solutions for embedded edge systems. By combining SiMa.ai’s MLSoC platform with CVEDIA’s expertise in artificial video analytics and Supermicro’s edge appliances, municipalities can harness high-performance AI/ML applications at the edge with enhanced efficiency and scalability. This partnership not only promises to revolutionize applications such as object detection, anomaly detection, and vehicle classification but also sets new standards for performance per watt in edge computing. As the demand for AI-driven solutions at the edge continues to grow, this collaboration underscores the importance of innovative technologies and strategic partnerships in addressing complex urban challenges and advancing towards a smarter, more connected future.
