Figure 1. Schematic diagram of the overall workflow of physical embedding machine learning force field: including high-order isovariant models, physical knowledge-guided adaptive bond length sampling ...

Why it’s important not to over-engineer. Equipped with suitable hardware, IDEs, development tools and kits, frameworks, datasets, and open-source models, engineers can develop ML/AI-enabled, ...

How embedded AI hardware reliability is handled in the defense and aerospace fields. How that reliability is assured and tested. With artificial intelligence progressing into areas as diverse as ...

Covering one of the fast-growing fields at the intersection of AI and embedded systems, the course will focus on designing efficient ML systems that are optimised for resource-constrained computing ...