SiMa in Hindi means edge, which is what SiMa.ai has brought to the embedded edge market by integrating machine learning on an SoC.
The edge computing market has witnessed an exponential increase in demand post the Covid pandemic. A recent study by Markets and Markets Research reported that the embedded edge market is expected to reach $101.3 billion by 2027 at a CAGR of 17.8%. The hardware segment is expected to largely contribute to this growth.
The challenge faced by this exponential growth is the complexity of integrating edge computing applications and platforms with the existing architecture. The classic system-on-chip (SoC) companies need to adopt machine learning (ML) to meet the rising demands of computing performance and cost.
This is where San Jose based startup SiMa.ai enters the picture with its purpose-built platform, which deploys effortless ML and scaling at the edge for computer vision applications at very low power. Born in India, founder Krishna Rangasayee led a semiconductor business at Xilinx, worth more than $25 billion, for 18 years, before deciding to propel the world into a new era of disruptive semiconductor technologies.
The machine learning company has come up with the industry’s first software-centric purpose-built Machine Learning System-on-a-Chip (MLSoC) platform focused on computer vision applications.
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