Nvidia researchers developed dynamic memory sparsification (DMS), a technique that compresses the KV cache in large language models by up to 8x while maintaining reasoning accuracy — and it can be ...

As AI agents move into production, teams are rethinking memory. Mastra’s open-source observational memory shows how stable ...

Next version of Microsoft’s software development platform brings improvements for JIT compilation, WebAssembly, C#, and F#.

Abstract: This survey article focuses on the emerging connections between machine learning and data compression. While the fundamental limits of classical (lossy) data compression are well-established ...

If you haven't noticed, the price of memory has shot through the roof. If you can't afford to boost your Linux system with hardware, try this software approach.

In an effort to work faster, our devices store data from things we access often so they don’t have to work as hard to load that information. This data is stored in the cache. Instead of loading every ...

Abstract: Large multimodal models (LMMs) have advanced significantly by integrating visual encoders with extensive language models, enabling robust reasoning capabilities. However, compressing LMMs ...

According to @godofprompt, researchers have developed a novel Cache-to-Cache (C2C) method allowing large language models (LLMs) to communicate directly via their internal key-value (KV) caches, ...