Most approaches to machine learning-based inverse design require large amounts of simulation or experimental data, which are costly and time-consuming, especially for microscale and nonlinear systems.

Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

In social platforms, artificial intelligence is more than automation—it’s the invisible architecture that defines how ...

Manufacturing execution systems (MES) generate mountains of data. Deciphering the data, however, often consumes hours daily.

Machine learning is found in data analytics, rapid processing ... image generators, and design software. These tools allow users to input parameters and generate creative outputs, providing ...

GridFree AI has secured $5 million in funding to fast-track the deployment of modular artificial intelligence data centres, signalling a significant shift in how computational infrastructure will be ...

Power-hungry GPUs and other AI chips are reshaping the power electronics that convert and distribute electricity around data centers ... in design and engineering. Machine learning does not ...

In theory, if employees can learn AI at work, they will then be able to apply those skills to their own tasks, which will ...

Laser-based metal processing enables the automated and precise production of complex components, whether for the automotive industry or for medicine. However, conventional methods require time- and ...