Nanowerk

Stacked memristor arrays compute Euclidean distance in memory to accelerate self-organizing maps

A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling ...

AI chip developer FuriosaAI reportedly raising up to $500M

The report didn’t specify the valuation that FuriosaAI is expected to receive. The company was worth $735 million as of July, ...

AI chip developer FuriousaAI reportedly raising up to $500M

The report didn’t specify the valuation that FuriousaAI is expected to receive. The company was worth $735 million as of July ...
The Malaysian Reserve

MicroCloud Hologram Inc. Utilizes FPGA to Accelerate Tensor Network Computing to Achieve Quantum Spin Models

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, proposed an innovative hardware acceleration technology that converts the quantum tensor network ...
IEEE

Modular Polynomial Codes for Secure and Robust Distributed Matrix Multiplication

Abstract: We present Modular Polynomial (MP) Codes for Secure Distributed Matrix Multiplication (SDMM). The construction is based on the observation that one can decode certain proper subsets of the ...
IEEE

SDIM: A Subtly Designed Invertible Matrix for Enhanced Privacy-Preserving Outsourcing Matrix Multiplication and Related Tasks

Abstract: Matrix multiplication computation (MMC) is a fundamental operation with various applications, including linear regression, k-nearest neighbor classification and biometric identification.
techxplore

AI models stumble on basic multiplication without special training methods, study finds

These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated reasoning. But when it comes to four-digit multiplication, a task taught in ...