Unleashing the Future of Vision AI: Alif and Edge Impulse Upgrade Edge Deployments with Powerful Computer Vision and Full Support for Nvidia's TAO Toolkit

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Nov 11, 2024, 02:00 ET

Alif Semiconductor hosts a demonstration at Electronica of an AI vision application created using transfer learning in the TAO toolkit, and deployed to an Ensemble MCU via the Edge Impulse platform

PLEASANTON, Calif., Nov. 11, 2024 /PRNewswire/ -- Alif Semiconductor®, a leading global supplier of secure, connected, power efficient Artificial Intelligence and Machine Learning (AI/ML) microcontrollers (MCUs) and fusion processors, along with Edge AI development platform Edge Impulse, today announced a significant breakthrough in implementing AI vision processing on edge microcontrollers. This is achieved through the introduction of full support for Nvidia's TAO model training toolkit on the Ensemble® and Balletto™ MCU families and the Edge Impulse platform.

Unleashing the Future of Vision AI: Alif and Edge Impulse Upgrade Edge Deployments with Powerful Computer Vision and Full Support for Nvidia’s TAO Toolkit

The TAO toolkit has generated considerable enthusiasm among developers of edge AI devices due to its provision of extensive training datasets for common vision processing applications, and its support for transfer learning from pre-trained models. This innovation promises to substantially reduce the cost, time and effort which embedded device OEMs typically invest into model development for AI vision applications.

Until now, deploying TAO-trained models on low-power MCUs for edge applications has been untested and unproven. Now, with the complete integration of Nvidia TAO into its platform, Edge Impulse has established a streamlined process for deploying TAO models on the Alif Ensemble and Balletto families of MCUs and fusion processors. Fully integrated into the Edge Impulse platform, Alif's products feature the Arm® Ethos™-U55, a neural processing unit (NPU) for which Nvidia has optimized the TAO toolkit.

Embedded developers seeking to implement AI vision applications, such as people counting, intruder detection, or robotics, can now utilize the TAO training toolkit and its dataset, confidently deploying either a pre-trained TAO model or a custom model developed through transfer learning via Edge Impulse on Alif Ensemble or Balletto MCUs.

Henrik Flodell, Senior Marketing Director at Alif Semiconductor, stated, "With Alif's AI-optimized MCU ecosystem, high-end embedded vision processing is transitioning from large, expensive microprocessors to next-generation edge MCUs. The integration of the TAO toolkit by Edge Impulse has significantly streamlined the development and deployment of AI vision processing models on Alif MCUs."

Adam Benzion, SVP Partnerships at Edge Impulse, added, "The TAO toolkit accelerates the generation of effective ML models, but it doesn't address the deployment of these models on edge-optimized hardware. Together with Alif, we have solved this challenge by providing a fully integrated workflow from the TAO toolkit's pre-trained models to deployment on Alif edge MCUs."

Attendees can view the Alif/Edge Impulse demonstration of advanced AI vision processing on an Ensemble MCU at Electronica in the Alif Semiconductor booth B4.106 (Munich, Germany, 12-15 November 2024).

To learn more about the Ensemble and Balletto families of edge MCUs and fusion processors, please visit alifsemi.com. To learn more about the Edge Impulse development and deployment platform for AI at the edge, please visit edgeimpulse.com.

About Alif Semiconductor

Alif Semiconductor is the industry-leading supplier of next-generation secure AI/ML-enabled 32-bit microcontrollers. Since 2019, Alif's expanding offering of microcontrollers and fusion processors has been revolutionizing the way developers can create broad, scalable, and connected AI-enabled embedded applications that are genuinely power efficient. Alif Semiconductor is the only choice for power efficient microcontrollers that can handle heavy AI and ML workloads for battery-operated IoT devices. For more information go to https://alifsemi.com/.

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SOURCE Alif Semiconductor