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!
The landscape of IoT development is evolving rapidly, and staying ahead requires more than just technical know-how, it demands a strategic shift in how we approach building connected devices.
Discover how no-code/low-code platforms are transforming embedded development by enabling rapid prototyping and deployment with minimal coding. Explore tools like LabVIEW, Node-RED, and XOD that simplify IoT, automation, and industrial system design.
Teams that are looking at alternative programming languages have two options today: Ada and Rust. Both languages raise the bar in terms of safety and security
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.
The ETH spin-off Flink Robotics wants to revolutionize the handling of packages. Its founders Moritz Geilinger and Simon Huber have developed software that allows robots to work together and quickly take on new tasks.
CUDA Cores and Tensor Cores are specialized units within NVIDIA GPUs; the former are designed for a wide range of general GPU tasks, while the latter are specifically optimized to accelerate AI and deep learning through efficient matrix operations.
Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines.
At least 15 billion primary batteries are being disposed of yearly worldwide. The world is getting better at recycling, which is excellent news. However, the bad news is that we are still throwing batteries that are not fully utilized.
Explore the future of connected communities in intelligent cities and underserved regions, highlighting the role of technologies like 5G, AI, and blockchain in enhancing connectivity and promoting inclusive development.
Researchers at EPFL have made a breakthrough in understanding how neural network-based generative models perform against traditional data sampling techniques in complex systems, unveiling both challenges and opportunities for AI's future in data generation.
The method, which combines a ChatGPT-like large language model with information about a protein’s 3D shape, could make it easier and faster to develop better medicines for infectious diseases, cancer, and other conditions.
Explore how IoT revolutionizes remote infrastructure management, enhancing efficiency and resilience with solutions like Particle's M-Series for future-ready connectivity.
In a world where connectivity is king, the choice of SIM form factor plays a crucial role in the success of any deployment from consumer electronics to IoT applications. As a versatile platform Monogoto supports an array of SIM types, tailored to meet specific operational needs and strategic goals.
The micromobility industry is at an exciting crossroads. As cities worldwide strive for smarter, cleaner, and more efficient modes of transportation, the importance of reliable connectivity in the micromobility sector is paramount.
In our digitally connected world, seamless integration and communication between devices are not just conveniences but necessities to ensure the success of businesses, whether just starting out or firmly established.
Improved occupational health and safety can enhance productivity by 46% and boost employee well-being. To address these opportunities, Xsens is launching a crash course on topics like injury risk reduction, regulation compliance, and the positive influence of safer workspaces.
While not every delivery is tracked in ‘real time’ at the parcel level yet, that day will come, particularly for high value or perishable cargoes. Logistics companies looking to improve efficiencies and reduce costs are rapidly adopting cellular IoT and WiFi solutions that support real time location
The upcoming "Machine Learning for Safety Experts" training by SAE and Fraunhofer IKS in Munich on October 22-23, 2024 is a timely initiative. It will address this crucial skill gap and ensure engineers are well-equipped to handle the intricacies of safe Machine Learning applications.