The latest release of qvac-fabric-llm.cpp, the inference engine of the QVAC Fabric LLM, features TurboQuant integration for resource management in long-running inference sessions. Tether adopts the ...

Introduces a low-rank-based approach to KV cache compression, one of the key bottlenecks in long-context AISpeeds up attention computation by up to 6.9x and overall generation throughput by up to 3.1x ...

Running a large language model is expensive, and a surprising amount of that cost comes down to memory, not computation. Every time a model like Gemini or GPT-4 processes a long document or sustains a ...

Vector quantization, stock dips & RAMageddon – the real story behind how a memory compression algorithm went viral ...

As enterprise AI becomes more complex, AI architectures can no longer treat context as temporary.

GPU memory (VRAM) is the critical limiting factor that determines which AI models you can run, not GPU performance. Total VRAM requirements are typically 1.2-1.5x the model size due to weights, KV ...

Google's TurboQuant reduces the KV cache of large language models to 3 bits. Accuracy is said to remain, speed to multiply. Google Research has published new technical details about its compression ...

SEOUL, South Korea, July 2, 2026 /PRNewswire/ -- Dnotitia Inc. (Dnotitia), a company specializing in long-term memory AI and semiconductor-based AI infrastructure technologies, has released the paper ...