Avance en los Robots de Próxima Generación y las Soluciones de IA en el Edge

General-purpose humanoid robots are designed to adapt quickly to human-centric environments, handling tedious or physically demanding tasks. They are now being used in factories and healthcare facilities to assist humans and address labor shortages.

Training AI models is often hampered by limited or expensive real-world data. Synthetic data, generated through simulations or AI, can significantly reduce training time and costs while improving model performance.

Virtual facilities, including factories, warehouses and distribution centers, semiconductor fabs, and data centers, unlock new possibilities for the world’s heavy industries, allowing them to design,simulate, operate, and optimize their assets and processes—entirely virtually.

In a future where factories, retail spaces, and public areas operate efficiently and safely, multi-camera tracking uses hundreds of cameras to accurately monitor and manage large areas by following objects and measuring activity.

Traditional video analytics use fixed models limited to detecting predefined objects. Generative AI and foundation models enable more complex, broad perception and contextual understanding, creating smarter video analytics AI agents.

Physical AI-powered robots must autonomously sense, plan, and perform complex tasks in dynamic environments. A "sim-first" approach, using robot simulation in digital environments, is essential for training and validating these systems before deployment.