Advanced wearable devices enable the wearer to track their BP around the clock, without having to attend their health professional or grapple with a clunky home BP monitor.
Advanced wearable devices enable the wearer to track their BP around the clock, without having to attend their health professional or grapple with a clunky home BP monitor.
Learn how agnostic systems like Awentia's No-Data Vision Foundation Model addresses key barriers to AI adoption such as data dependency, cost, and complexity across industries like agriculture, robotics and manufacturing.
This article explores TPU vs GPU differences in architecture, performance, energy efficiency, cost, and practical implementation, helping engineers and designers choose the right accelerator for AI workloads today!
From simple sensor control to connected, intelligent devices, embedded systems often outgrow a single MCU. Pairing an MCU with Linux adds power and flexibility, but also introduces communication challenges, dual development workflows, and increasing software complexity.
This article explores how automated CI/CD pipelines replace fragile manual build processes with reproducible, auditable workflows that improve compliance, reduce defects, and accelerate development in regulated embedded systems
Mario Mauerer, maxon's Global Business Development Manager, Robotics, discusses what it takes for robotic deployments to be successful in complex real-world environments.
Join Prof. Fei Chen as he explores advanced bimanual manipulation and teleoperation techniques shaping the future of intelligent human-like robots in this expert-led robotics session.
Advanced wearable devices enable the wearer to track their BP around the clock, without having to attend their health professional or grapple with a clunky home BP monitor.
Learn how agnostic systems like Awentia's No-Data Vision Foundation Model addresses key barriers to AI adoption such as data dependency, cost, and complexity across industries like agriculture, robotics and manufacturing.
This article is for everyone who’s – at least – slightly worried about what will happen to their deployed NB-IoT devices in the US, or abroad. Let’s explore the potential scenarios and actionable mitigation plans to minimize risks.
EPFL researchers have developed 4M, a next-generation, open-sourced framework for training versatile and scalable multimodal foundation models that go beyond language.
The nRF54L series from Nordic Semiconductor provides a versatile, ultra-low-power SoC toolkit for IoT developers, enabling enhanced battery life, seamless connectivity, and faster prototyping, positioning it as the foundation for next-generation IoT development.
GPUs excel in parallel processing for graphics and AI training with scalability, while NPUs focus on low-latency AI inference on edge devices, enhancing privacy by processing data locally. Together, they complement each other in addressing different stages of AI workloads efficiently.
The “PRoC3S” method helps an LLM create a viable action plan by testing each step in a simulation. This strategy could eventually aid in-home robots to complete more ambiguous chore requests.
Researchers at Stanford Engineering have developed an AI-trained model to accurately recreate the hand movements of elite-level pianists and the physical stresses they endure while playing.
According to , the global AI robotics market will reach $17 billion in 2024 and will keep growing by 24% annually. Today, robots deliver packages, conduct geological surveys, and entertain visitors of parks and exhibitions – however, that’s not the limit of their abilities.
A team of Caltech researchers has developed an analogous algorithm for autonomous robots—a planning and decision-making control system that helps freely moving robots determine the best movements to make as they navigate the real world.
AI in the IoT also needs to be performed as close to the sensors as possible, all the way to the edge, on increasingly capable devices in terms of compute power.