Siemens’ Post

Transfere learning to get any task or process faster optimized

Thanks for sharing 👍

Während der Pandemie habe ich ja in der Produktion ausgeholfen und ich fand die automatisierten Prozesse echt faszinierend. Und heute schau ich ab und zu vorbei und bin jedesmal überrascht von dem Tempo der Weiterentwicklung.

This is a Smart take

Training robots in virtual environments is a great example of AI driving efficiency while keeping humans at the center of innovation.

The integration of AI, simulation, and digital twins in robot training is a significant breakthrough. By leveraging these technologies, robots can learn and adapt at an unprecedented pace, bridging the gap between theory and practice through the Sim2Real approach. This method accelerates training, reduces costs, and enhances efficiency. The concept of "robot schools" in the industrial metaverse is noteworthy. These virtual environments allow robots to practice tasks and develop problem-solving skills in a highly realistic setting. This approach enables robots to acquire complex skills quickly, making them invaluable assets in diverse industries. The future of automation looks promising, with robots poised to collaborate safely with humans. Moreover, the use of synthetic data and digital twins addresses data scarcity issues in AI training. By simulating real-world conditions, robots can be prepared for various scenarios, ensuring adaptability and responsiveness. This technology is transforming robot training and redefining industrial automation and sustainability. As we move forward, AI and digital twins will play a pivotal role in shaping the future of manufacturing. 🙏

A bold idea here

As an industry professional, I find this technology truly advanced. 👍

As an ME major, and more specifically, Manufacturing and Production Engineering student, I have learned a great deal from this article — an exciting future ahead!