Edge Impulse incorporates Nvidia TAO Toolkit for edge AI; partners with AWS

By integrating this functionality, developers can harness the Edge Impulse platform to create production-ready AI applications that can smoothly deploy on various edge devices. Edge Impulse streamlines the deployment process, saving valuable time on extensive code writing. Moreover, the models can be optimized to perform efficiently on edge devices, leading to enhanced performance and optimal resource utilization.

“This collaboration is a significant boon to our customers, who will now have access to state-of-the-art machine learning research and model architectures from Nvidia,” says Jan Jongboom, the co-founder and chief technology officer of Edge Impulse.

The Nvidia TAO toolkit 5.0 has an extensive collection of over 100 Nvidia-optimized model architectures. These models serve as a starting point for developers, allowing them to optimize the models according to their proprietary data.

Moreover, company executives say the platform facilitates efficient data collection from various edge devices, empowering customers to maximize their outcomes even with limited data. The auto-labeling tool provided by Edge Impulse further improves data quality, streamlining the development process and maximizing the potential of the models.

The latest version of the Nvidia TAO toolkit features a software framework designed to enhance the development of vision AI models. According to the company, embracing a low-code approach simplifies the intricacies of developing AI models for computer vision tasks. This approach not only accelerates progress but also makes it more straightforward.

Enterprise AI development gets a boost as Edge Impulse partners with AWS

Edge Impulse announced its collaboration with AWS under the AWS Independent Software Vendor (ISV) Accelerate Program in a separate announcement. As part of this partnership, Edge Impulse will receive technical support and resources from AWS.

Edge Impulse will receive go-to-market support from Amazon Web Services, enabling the company to effectively market and promote its solutions to a broader audience of AWS customers. Moreover, the co-selling opportunities will grant Edge Impulse access to the AWS Sales Organization, and this collaboration will improve Edge Impulse’s reach and sales prospects within the AWS ecosystem, the company says.

Company executives say the collaboration between Edge Impulse and AWS offers enterprises a versatile platform to develop a wide range of applications that integrate embedded machine learning. Moreover, the seamless integration process of Edge Impulse into embedded systems allows companies to incorporate machine learning models into their devices, eliminating the need for complex AI coding.

“We’ll be able to leverage AWS’s expertise in cloud computing and machine learning to accelerate innovation in AI at the edge and support businesses in developing powerful new applications,” says Zach Shelby, the chief executive officer of Edge Impulse.

In a recent collaboration, Infineon Technologies AG joined forces with Edge Impulse to access essential development tools for creating and implementing embedded machine learning on edge AI microcontrollers. The partnership targets Infineon’s PSoC 63 Bluetooth LE MCU.

Article Topics

AI/ML  |  AWS  |  edge AI  |  Edge Impulse  |  IoT  |  Nvidia  |  TinyML