Morning Overview on MSN

Google says TurboQuant cuts LLM KV-cache memory use 6x, boosts speed

Google researchers have published a new quantization technique called TurboQuant that compresses the key-value (KV) cache in ...

Google reveals algorithms to address AI memory challenges; memory and storage stocks drop

Google unveils TurboQuant, PolarQuant and more to cut LLM/vector search memory use, pressuring MU, WDC, STX & SNDK.
IEEE

An Information-Theoretic Framework for Receiver Quantization in Communication

Abstract: We investigate information-theoretic limits and design of communication under receiver quantization. Unlike most existing studies that focus on low-resolution quantization, this work is more ...
IEEE

IRS With Discrete Phase Shifts: When Is Quantization Optimal?

Abstract: Intelligent reflective surfaces (IRS) with discrete phase shifts are considered. While no analytical solutions for globally-optimal discrete phase shifts are known, quantization of optimized ...
GitHub

Swin Transformer

Used as a backbone for Self-Supervised Learning: Transformer-SSL Using Swin-Transformer as the backbone for self-supervised learning enables us to evaluate the transferring performance of the learnt ...