NXP eIQ software expands AI edge capabilities

     NXP Semiconductors has announced the addition of two new tools to its eIQ AI and machine learning development software to make it easy to deploy and use AI edges on a variety of edge processors. eIQ Time Series Studio provides automated machine learning workflows that make it easy to develop and deploy time series-based machine learning models on McU-level chips, such as the MCX Series MCU portfolio or the i.MX RT crossover MCU portfolio.

     The GenAI process provides the building blocks for a large language model (LLM) that supports generative AI solutions. Such schemes are used in conjunction with MPUs, such as the NXP i.MX family of application processors, to simplify the deployment of intelligent edges by training LLMS on context-specific data. For example, LLM-equipped appliances are trained in user manuals to communicate with users in natural language, telling them how to use a particular function, perform a particular task, or optimize usage and maintenance.

     Deploying AI at the edge has many benefits, including reduced latency, enhanced user privacy, and reduced energy consumption. The NXP eIQ Toolkit extension significantly simplifies and accelerates the deployment process, giving developers access to a wider range of model types, including generative AI, time series-based models, and vision-based models. In addition, users can deploy models on a variety of edge processors.

     Charles Dachs, senior vice president, Industry and iot general manager, NXP Semiconductors, said: "AI is key to enabling prediction and automation based on user needs, but it must be developed in a way that works for edge deployments. NXP provides just-in-time tools for small AI models on MCUS (such as the MCX family), crossover MCUS like the i.MX RT700, and larger generative AI models running on more powerful devices like the i.MX 95 application processor, giving developers a rich choice of AI models and AI-enabled edge processors. Make edge AI truly available to application developers across all industries."

     NXP has added Generative Artificial Intelligence (GenAI) processes with Retrieval Enhanced Generation (RAG) and fine-tuning and eIQ Time Series Studio to eIQ AI and machine learning development software. To easily deploy and use AI on a variety of edge processors, from small microcontrollers (MCUS) to more powerful large application processors (MPUs)

     Shanghai, China - October 30, 2024 - NXP Semiconductors N.V. today announced the addition of two new tools to its eIQ AI and machine learning development software to make it easy to deploy and use AI edges on a variety of edge processors.eIQ Time Series Studio provides automated machine learning workflows that make it easy to develop and deploy time series-based machine learning models on McU-level chips, such as the MCX Series MCU portfolio or the i.MX RT crossover MCU portfolio.

     The GenAI process provides the building blocks for a large language model (LLM) that supports generative AI solutions. Such schemes are used in conjunction with MPUs, such as the NXP i.MX family of application processors, to simplify the deployment of intelligent edges by training LLMS on context-specific data. For example, LLM-equipped appliances are trained in user manuals to communicate with users in natural language, telling them how to use a particular function, perform a particular task, or optimize usage and maintenance.

     Deploying AI at the edge has many benefits, including reduced latency, enhanced user privacy, and reduced energy consumption. The NXP eIQ Toolkit extension significantly simplifies and accelerates the deployment process, giving developers access to a wider range of model types, including generative AI, time series-based models, and vision-based models. In addition, users can deploy models on a variety of edge processors.

     Charles Dachs, senior vice president, Industry and iot general manager, NXP Semiconductors, said: "AI is key to enabling prediction and automation based on user needs, but it must be developed in a way that works for edge deployments. NXP provides just-in-time tools for small AI models on MCUS (such as the MCX family), crossover MCUS like the i.MX RT700, and larger generative AI models running on more powerful devices like the i.MX 95 application processor, giving developers a rich choice of AI models and AI-enabled edge processors. Make edge AI truly available to application developers across all industries."

     eIQ Time Series Studio simplifies and accelerates the development and deployment of time series-based AI models that support multiple input signals (such as voltage, current, temperature, vibration, pressure, sound, time of flight, and signal combinations) and multimodal sensor fusion. With automated machine learning capabilities, developers can extract meaningful insights from raw time series data to quickly build AI models that meet performance, memory, Flash storage.