Embedded applications extract the best power-performance trade-off from digital signal processors (DSPs) by making extensive use of vectorized execution. Rather than handwriting the many customized ...

After joining FactSet in 2008 as a software engineer and rising through the ranks over 17 years—most recently serving as CTO—Kate Stepp stepped into her latest role, chief AI officer, this March.

Combining cutting-edge proprietary technologies and enhanced manufacturing, TG4070 is positioned as a novel vaccine relevant to multiple tumor types TG4070, the second candidate from the myvac® platfo ...

Even though traditional databases now support vector types, vector-native databases have the edge for AI development. Here’s how to choose. AI is turning the idea of a database on its head.

The financial sector is heavily data driven. Every day, trillions of data is generated by the global financial system; these data sets are the bedrock of the financial system since they support a ...

Abstract: Deep learning technologies have significantly advanced object information extraction from remote sensing data in recent years, achieving broad application across various industrial sectors.

This article shows a simple example of a loop that was not vectorized by the Intel® C++ Compiler due to possible data dependencies, but which has now been vectorized using the Intel® Advanced Vector ...

Vectorization in R refers to the practice of applying a function to an entire vector or array of data at once, rather than iterating through the elements one by one. This is possible because R is ...

Abstract: In long-term Earth observation, change detection (CD) is a crucial and intricate task with applications spanning diverse fields, including land resource planning and natural disaster ...

Vector databases and search aren’t new, but vectorization is essential for generative AI and working with LLMs. Here's what you need to know. One of my first projects as a software developer was ...