Deploying Amber: Edge-Based, Real-Time Anomaly Detection on Intel CPUs

In an era where operational efficiency and early anomaly detection are paramount, traditional AI approaches often fall short due to their dependency on supervised learning and the need for extensive labeled data. Enter Amber, Boon Logic’s flagship product powered by the cutting-edge Nano algorithm. This unsupervised machine learning solution redefines anomaly detection by learning the normal operating states of machines and processes in real-time, without the need for pre-labeled data or time-intensive training. In this webinar, we will dive into how Amber, leveraging the Nano algorithm, outpaces conventional methods by achieving 1000x faster training and inference—running exclusively on Intel processors without requiring cloud-support or additional accelerators like GPUs or FPGAs. Attendees will gain insights into Amber’s deployment capabilities, including real-world examples where it has successfully predicted critical failures well in advance, and integrations in auxiliary software stacks including visual inspection and embedded devices.