Even though traditional databases now support vector types, vector-native databases have the edge for AI development. Here’s ...

Abstract: Considering that Von Neumann architecture has bottlenecks in both speed and power consumption, in-memory computation is a promising solution. The in-memory computation needs to be carried ...

Microsoft has teamed up with Barclays on a novel approach to tackling artificial intelligence (AI) and optimisation problems based on a scalable analogue optical computer (AOC) architecture, designed ...

This project focuses on lossless compression techniques optimizing space, time, and energy for multiplications between binary (or ternary) matrix formats and real-valued vectors.

The growing imbalance between the amount of data that needs to be processed to train large language models (LLMs) and the inability to move that data back and forth fast enough between memories and ...

Abstract: Structured sparsity has been proposed as an efficient way to prune the complexity of Machine Learning (ML) applications and to simplify the handling of sparse data in hardware. Accelerating ...

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ABSTRACT: Introduction: Malaria control needs the development of complementary and/or alternative strategies such as biological controls. Despite, malaria’s current control efforts, the spread and the ...