NXP has expanded its eIQ AI and ML software development environment with two new tools to simplify AI deployment at the edge. The software supports low-latency, energy-efficient, and privacy-focused AI, enabling ML algorithms to run on a range of edge processors, from small MCUs to advanced application processors.
The eIQ Time Series Studio introduces an automated machine learning workflow for efficiently developing and deploying time-series ML models on MCU-class devices, including NXP’s MCX series of MCUs and i.MX RT crossover MCUs. It supports various input signals—voltage, current, temperature, vibration, pressure, sound, and time of flight—as well as multi-modal sensor fusion.
GenAI Flow provides the building blocks for creating Large Language Models (LLMs) that power generative AI applications. With Retrieval Augmented Generation (RAG), it securely fine-tunes models on domain-specific knowledge and private data without exposing sensitive information to the model or processor providers. By linking multiple modules in a single flow, users can customize LLMs for specific tasks and optimize them for edge deployment on MPUs like the i.MX 95 application processor.
To learn more and access the newest version of the eIQ machine learning development environment, click on the product page link below.
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