Machine Learning Applications for Smarter, More Efficient Devices
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Datacenter AI -
Consumer Devices -
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Industrial -
Mobile AI
Scalable AI Inference with Traditional ML and DL Models
Google’s Axion CPU, powered by Arm Neoverse, accelerates AI inference at scale across a diverse set of workloads. From structured data models like XGBoost, to natural language processing (NLP) with BERT, and computer vision using ResNet50, Axion showcases Arm’s performance leadership across both classical machine learning and deep learning use cases.
Explore how Google optimized inference for BERT (NLP), XGBoost (tabular data), and ResNet-50 (computer vision) using Arm-based Axion CPUs—delivering performance, efficiency, and scalability for enterprise AI.
Voice Interfaces Powered by On-Device ML
Arm enables natural voice interaction in memory- and power-constrained consumer devices by running ML models on-device—enhancing privacy, reducing latency, and eliminating the need for constant cloud connectivity.
Learn how Sensory developed private, responsive voice assistants using Arm ML technology.
Smarter Home Automation With Edge Machine Learning
Arm-based ML powers real-time, local processing for smart home devices, enabling features like facial recognition, motion detection, and intelligent climate control— without sending data to the cloud.
See how Grovety uses Arm technology to build intelligent, visual edge devices that enhance security and responsiveness at home.
Predictive Maintenance With Machine Learning
Arm ML solutions enable industrial devices to monitor sensors and predict failures before they happen—reducing downtime, extending equipment life, and improving operational efficiency.
Discover how the Arm-based from Raspberry Pi 5 supports real-time analytics and predictive maintenance in industrial environments.
Generative and Traditional AI on Mobile
Arm processors support both generative and traditional AI tasks directly on mobile devices, enabling features like content summarization and intelligent assistants—all while preserving privacy and minimizing latency.
Learn how Arm enables on-device generative AI experiences, such as real-time voice and text summarization, on mobile CPUs.
Latest News and Resources
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CPU Inference
Arm KleidiCV Accelerates Computer Vision by 4x
KleidiCV integration with OpenCV helps developers achieve up to four times performance uplift for computer vision applications on mobile.
Learning Paths
Learn ML With Arm
Access hands-on tutorials, labs, and Learning Paths to build your ML skills using Arm-based platforms and tools.
ML Resources
Get Started With ML on Arm Cortex-M Devices
Explore a step-by-step guide for building and deploying ML models on resource-constrained embedded devices using Cortex-M processors.
Dummies Guide
Looking to Add ML to Your Device?
Explore platform configuration, hardware, software, and ecosystem significance. Grasp the basics of ML, explore opportunities and challenges, and learn how to get started.
Podcast
Using Technology to Track and Protect Wildlife
Explore how traditional ML and sensor technology are helping researchers monitor animal behavior in the wild—advancing conservation through smarter, data-driven insights.
Podcast
AI for Wildlife Conservation
Learn how AI models, from traditional ML to DL, are enabling more effective wildlife conservation through pattern recognition, predictive modeling, and real-time analysis.
AI from Edge to Cloud
Future of AI Processing: Heterogeneous Compute
With insights from AWS, Meta, and Samsung, this MIT Technology Review research report explores how a new compute paradigm can deliver seamless AI experiences.