Search Results for "working memory"

...The core idea behind Bolt is to compress large collections of dense numeric vectors and perform mathematical operations directly on the compressed representations instead of decompressing them first. This approach significantly reduces both memory usage and computational overhead when working with high-dimensional data commonly used in machine learning systems. Bolt is particularly useful in applications such as similarity search, approximate nearest neighbor queries, and large-scale matrix computations where millions of vectors must be processed efficiently. The project includes algorithms designed to accelerate operations such as dot products and distance calculations, which are central to many machine learning tasks.