eIQ^® ML Software Development Environment

The NXP^® eIQ^® machine learning (ML) software development environment enables the use of ML algorithms on NXP EdgeVerse^™ microcontrollers and microprocessors, including i.MX RT crossover MCUs, and i.MX family application processors. eIQ ML software includes a ML workflow tool called eIQ Toolkit, along with inference engines, neural network compilers and optimized libraries. This software leverages open-source and proprietary technologies and is fully integrated into our MCUXpresso SDK and Yocto development environments, allowing you to develop complete system-level applications with ease.

Deploy Generative AI to the Edge Faster

Automate your Large Language Models (LLM) for generative AI solutions. When used with i.MX applications processors, these solutions make it easier to deploy intelligence to the edge by training LLMs on specific contextual data.

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Machine Learning Workflow Tools

eIQ Toolkit

Designed to make it easier for developers to build and optimize AI/ML applications and solutions on NXP Products
Supports Bring your own data (BYOD) and Bring your own model (BYOM) development flows with graphical UI and command-line host tools

eIQ Time Series Studio New

End-to-end development tool to build edge AI models for time series data modalities
Automated machine learning streamlines the workflow, reducing complexity and accelerating model training and optimization for anomaly detection, classification and regression models

eIQ Extensions

eIQ NVIDIA TAO Toolkit integration brings pre-trained vision AI models to NXP's EdgeVerse Processors
eIQ Model Watermarking Technology to protect intellectual property and detect copying

eIQ GenAI Flow New

eIQ GenAI Flow provides developers with access to the building blocks of generative AI applications. Users can test different LLMs and fine tune models on their private data sources with Retrieval Augmented Generation (RAG)

AI and Machine Learning Training Academy

On-demand training modules to help you with your ML application development.

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Design Resources

Application Code Hub

Application Example Software

The Application Code Hub (ACH) repository enables engineers to easily find software examples, code snippets, application software packs and demos developed by our experts.

eIQ Model Zoo

Machine Learning Models

The NXP eIQ® Model Zoo offers pre-trained models for a variety of domains and tasks that are ready to be deployed on supported products.

Machine Learning Goes Mainstream - eIQ ML Software Development Environment

Video

NXP’s eIQ Machine Learning software development platform makes Machine Learning at the edge possible for all levels of developers - from those just getting started, to the ML experts.® NN for object detection acceleration.

eIQ Automotive AI Enablement

eIQ Auto deep learning (DL) toolkit enables developers to introduce DL algorithms into their applications and to continue satisfying automotive standards.

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Additional Documents

The Age of Edge Machine Learning Democratization

Discover five key factors developers need to consider when choosing a processing solution for their edge ML projects in this whitepaper from ABI Research.

Handwritten Digit Recognition Using TensorFlow Lite Micro on i.MX RT Devices

This application note focuses on handwritten digit recognition on embedded systems through deep learning, using i.MX RT MCUs, MCUXpresso SDK and eIQ technology.

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eIQ Machine Learning (ML) Software Development Environment

eIQ software leverages inference engines, neural network compilers, optimized libraries and open-source technology allowing AI and ML enablement on edge nodes.

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Enabling eIQ Core NPU Delegates for i.MX Android Applications

This Application Note describes the deployment of the eIQ’s LiteRT inference engine (formerly known as TensorFlow Lite), with NPU acceleration support on Android OS for i.MX Applications Processors.