The platform offers dedicated functionality, which can be accessed using SensiML’s development tools. This integration allows developers to reduce development time and maximize the ML capabilities for edge applications.
By leveraging these tools, engineers can efficiently deploy advanced ML models on custom silicon tailored to specific edge use cases, ensuring scalable and effective solutions such as keyword spotting.
Efabless and SensiML have joined forces to deliver an open source enabled hardware and software 
solution for ML edge processing in IoT applications.
SensiML’s AutoML platform enables embedded developers—regardless of their data science experience—to quickly create ultra-efficient sensor inference algorithms that run autonomously on resource-limited edge devices.
Similarly, Efabless equips developers with open-source tools to design optimised custom SoCs without requiring deep expertise in IC design.
Key Features:
● Leverage chipIgnite ML custom silicon platform to achieve faster performance compared to traditional MCU-based solutions. ● Optimized Power Efficiency: Reduce power consumption by 10x, enabling longer battery life. ● Tailored Solutions which allow customisation of a silicon design to meet the specific requirements of your edge ML applications. Profiling and optimization of ML inference workloads can be accomplished in pre-hardware simulation to assist in sizing inference models appropriately. ● A complete development path, from data to silicon, powered by Efabless and SensiML. ● Open-source hardware and software development tools which provide transparency, customisation,and a cost-effective path to ML at the edge.
Efabless has taped out the chipIgnite ML. A design kit will be available for early evaluation starting in November 2024, providing developers with the tools they need to explore and design using the platform. The first shuttle for prototyping is scheduled for April 2025, with full-scale production expected to follow.
For more: www.efabless.com/chipignite-ml
