More information: Janghoon Ock et al, Multimodal language and graph learning of adsorption configuration in catalysis, Nature Machine Intelligence (2024). DOI: 10.1038/s42256-024-00930-7 . On ...

A better understanding of how the human brain represents objects that exist in nature, such as rocks, plants, animals, and so ...

By implementing AI-driven technologies across the claims life cycle and integrating real-time analysis from multiple ...

Embedded and federated machine learning offer several advantages. These include: • Improved Performance: Embedded machine learning can improve performance because the model doesn't have to be ...

Research broadly focuses on In-Sensor Computing, In-Memory Computing, Neuromorphic Computing, Embedded Machine Learning, Machine Learning for Smart Healthcare, and Efficient Multi ... We focus on ...

The future of MML can involve advancements in deep learning, ethical considerations, multimodal reinforcement learning, and interdisciplinary research,” Sumit Ghosh, co-founder and CEO, Chingari ...

SiMa.ai, a Silicon Valley–based startup producing embedded machine learning (ML) system-on-chip (SoC) platforms, today announced that it has raised a $70 million extension funding round as it ...