Maxim Dupont

The shift to localized intelligence transforms industries from manufacturing to healthcare, where split-second decisions based on accurate AI models can mean the difference between safety and disaster. Organizations leverage on-premises processing to instantly analyze visual information, reducing their reliance on cloud infrastructure. This speeds up response times, which is important

Neural Processing Units (NPUs) are specialized hardware accelerators designed to handle the unique computational demands of AI workloads, particularly those involving deep learning. Unlike traditional CPUs or GPUs, NPUs are optimized for matrix operations, low-precision arithmetic, and parallel data processing, making them highly efficient for inference and training tasks. Their

Machine learning teams spend most of their time training on unstructured data instead of building models. As a result, industries striving for autonomy need intelligent approaches to data processing. We are seeing a shift in how AI applications process information. Modern solutions now analyze and classify input data directly on

In the development of intelligent retrieval systems, much of the focus has traditionally been on teaching models what to look for, using examples that represent relevant, ideal outcomes. Equally important yet often underutilized is showing models what not to retrieve, which relies on negative examples to define the boundaries of

Federated learning offers a powerful solution for privacy-preserving data annotation by enabling decentralized labeling without transferring raw data to a central server. Instead of aggregating raw data, federated learning relies on secure aggregation techniques that combine model updates from multiple sources to prevent any party from accessing individual contributions. A

In 2025, the demand for intelligent, autonomous decision-making on low-power endpoints continues to reshape the landscape of edge computing. AI models are no longer confined to cloud infrastructure; they're now embedded within millions of IoT devices, from smart cameras to wearable health monitors. To ensure these devices operate