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

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, ...

The transformative power of technology has embarked on an exciting phase. Artificial intelligence (AI) and machine learning (ML) are becoming more thoroughly integrated into business operations, ...

Recent advancements in machine learning have significantly impacted the domain of high-speed electronic systems. By leveraging state‐of‐the‐art algorithms and novel network architectures, researchers ...

Machine learning workloads require large datasets, while machine learning workflows require high data throughput. We can optimize the data pipeline to achieve both. Machine learning (ML) workloads ...

Machine learning is a subfield of artificial intelligence which gives computers an ability to learn from data in an iterative manner using different techniques. Our aim here being to learn and predict ...

Many people have begun experimenting with using machine learning in embedded systems as the two technologies have become more prominent in today’s society. That approach allows for overcoming many of ...

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 ...