CNBC

A Google AI breakthrough is pressuring memory chip stocks from Samsung to Micron

Google said this week that its research on a new compression method could reduce the amount of memory required to run large language models by six times. SK Hynix, Samsung and Micron shares fell as ...
Ars Technica

Google’s TurboQuant AI-compression algorithm can reduce LLM memory usage by 6x

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...
IEEE

Research on Speech Separation Algorithms Based on Deep Learning

Abstract: This paper introduces an efficient speech separation algorithm based on optimized Long Short-Term Memory (LSTM) networks. The enhanced LSTM architecture improves accuracy and processing ...
IEEE

ADASTT: Adaptive Speech-to-Text Algorithm Selection Via Meta-Learning

Abstract: We introduce ADASTT, an adaptive meta-learning framework that selects, in real time, the most suitable speech-to-text (STT) model for each incoming audio input. Factors such as background ...