Neural network trained using a diverse dataset outperforms conventionally trained algorithms

Artificially intelligent neural networks, trained by images and videos available on the internet, can recognize faces, objects, and more. But there’s a serious drawback. Teaching machine learning algorithms how to identify people or items by relying solely on the visual library of faces and objects found online underrepresents socioeconomic and demographic groups.

Interactive cyber-physical human: Generating contact-rich whole-body motions

Performing human-like motions that involve multiple contacts is challenging for robots. In this regard, a researcher has envisioned an interactive cyber-physical human (iCPH) platform with complementary humanoid (physical twin) and simulation (digital twin) elements. iCPH combines human measurement data, musculoskeletal analysis, and machine learning for data collection and augmentation. As a result, iCPH can understand, …