Artificial intelligence vision silicon company Ambarella is partnering with Amazon Web Services to allow AWS customers to use the tech giant’s services to train machine learning models and run them on devices equipped with Ambarella’s CVflow AI vision chip.
According to Ambarella, developers previously had to manually optimize machine learning models for devices based on the company’s AI vision system on chip (SOC), a step that could add delays and errors to the app development process.
In an announcement, the companies said they collaborated to simplify the process by integrating the Ambarella toolchain with the Amazon SageMaker Neo cloud service.
Now, developers can bring trained models to Amazon SageMaker Neo and automatically optimize the model for Ambarella’s CVflow-powered SoCs, the companies said.
Using MXNet, TensorFlow, PyTorch or XGBoost, customers can train the model using Amazon SageMaker in the cloud or their local machine. The model can be uploaded to customer accounts and SageMaker can be used again to optimize the model for Ambarella SoCs with the ability to choose CV25, CV22 or CV2.
SageMaker Neo compiles the trained model into an executable made for Ambarella’s CVflow neural network accelerator. A series of optimizations are applied that can make the model run up to two tiems faster on the Ambaraella SoC, and customers can download the compiled model and deploy it to their fleet of Ambarella-equipped devices.
Optimized models run in the Amazon SageMaker Neo runtime purpose-built for Ambarella SoCs and for the Ambarella SDK. SafeMaker Neo occupies less than 10 times the disk and memory of TensorFlow, MXnet or PyTorch, Ambarella said.
“Ambarella is in mass production today with CVflow AI vision processors for the home monitoring, enterprise video security, and automotive markets,” said Chris Day, vice president of marketing and business development for Ambarella. “The ability to select an Ambarella SoC and compile a trained ML model with a single click is a powerful tool that makes it possible for our customers to rapidly bring the next generation of AI-enabled products to market.”