Embedded AI - Algorithm, Model, and Hardware
With the rapid increase in the rate of data generation and acquisition it has become increasingly important to have embedded and edge devices run AI models for executing specific tasks. Artificial Intelligence driven embedded products are being introduced across the industry segments at a rapid pace to enable the analysis of locally captured data.
Embedding AI/ML complex algorithms on constrained devices affect the embedded design in terms of time latency and power consumption. Embedded AI is highly responsive, provides precise insights and trends, reduces the turnaround time to analyze captured data, while minimizing privacy and security threats.
Download Whitepaper