The JadePuffer autonomous AI agent has upgraded with custom malware called EncForge that focuses on encrypting AI assets, ...
Vector quantization, stock dips & RAMageddon – the real story behind how a memory compression algorithm went viral ...
Vector search underpins most retrieval-augmented generation (RAG) pipelines. At scale, it gets expensive. Storing 10 million document embeddings in float32 consumes 31 GB of RAM. For dev teams running ...
TurboQuant is a compression algorithm introduced by Google Research (Zandieh et al.) at ICLR 2026 that solves the primary memory bottleneck in large language model inference: the key-value (KV) cache.
The scaling of Large Language Models (LLMs) is increasingly constrained by memory communication overhead between High-Bandwidth Memory (HBM) and SRAM. Specifically, the Key-Value (KV) cache size ...
This is the official implementation of our paper GaussianImage, a groundbreaking paradigm of image representation and compression by 2D Gaussian Splatting. With compact 2D Gaussian representation and ...
As LLM technologies gain more mainstream adoption and the ecosystem begins to mature, organizations are beginning to recognize the limits and costs of using LLM technologies. Many enterprises, ...
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