Amid this shift, Interview Kickstart has introduced an advanced machine learning and agentic AI program designed to help ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

The intersection of artificial intelligence (AI) with nanophotonics has received tremendous interests because of its potential to solve the most challenging problems in both areas. In photonics, ...

The integration of machine learning techniques into microstructure design and the prediction of material properties has ushered in a transformative era for materials science. By leveraging advanced ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...

Industrial automation is entering a new era with physical AI, where machine learning meets real-world motion control. AI-driven robotics and digital twins are closing the gap between simulation and ...

Heavy machinery is entering a new phase where hydraulics, electronics and embedded software are engineered as one integrated system. Using model-based systems engineering (MBSE) as a framework to ...