Google AI breakthrough TurboQuant reduces KV cache memory 6x, improving chatbot efficiency, enabling longer context and ...
Abstract: Whole Slide Images (WSIs) are gigapixel, highresolution digital scans of microscope slides, providing detailed tissue profiles for pathological analysis. Due to their gigapixel size and lack ...
Alphabet (GOOGL) has grown over time from a search engine into a hyperscaler. The company classifies its two revenue streams ...
Zilliz, the creator of Milvus -- the world's most widely adopted open-source vector database with over 43,000 GitHub stars and more than 10,000 enterprise deployments -- has been recognized as a ...
The open-source vector database Endee.io, that is well known for its Ultra High performance with 10x lower Infra, is ...
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Memory chip stocks are falling again: Why Micron, SanDisk, WDC, and Seagate keep getting hammered
It has been a bruising 24 hours for investors in memory chip storage companies, including Micron Technology, Inc. (Nasdaq: MU ...
Google's TurboQuant can dramatically reduce AI memory usage. TurboQuant is a response to the spiraling cost of AI. A positive outcome is making AI more accessible by lowering inference costs. With the ...
Random rotation: Multiply the input vector by a fixed random orthogonal matrix. This makes each coordinate follow a known Beta(d/2, d/2) distribution. Lloyd-Max scalar quantization: Quantize each ...
TL;DR: Google developed three AI compression algorithms-TurboQuant, PolarQuant, and Quantized Johnson-Lindenstrauss-that reduce large language models' KV cache memory by at least six times without ...
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