Tether successfully integrated Google’s TurboQuant into the inference engine of its local AI framework, QVAC. It is the ...

Companies running large language models face a persistent bottleneck: the memory consumed by key-value caches during ...

At the architectural level, Command A+ represents a major evolution from Cohere’s previous dense models. It is a decoder-only Sparse Mixture-of-Experts (MoE) Transformer. While the model houses a ...

Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...

Nature-inspired optimisation techniques have revolutionised image compression by emulating collective behaviours and evolutionary processes observed in biological and physical systems. Central to many ...

turboquant-py implements the TurboQuant and QJL vector quantization algorithms from Google Research (ICLR 2026 / AISTATS 2026). It compresses high-dimensional floating-point vectors to 1-4 bits per ...

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...

A new study published today in Nature has found that X’s algorithm – the hidden system or “recipe” that governs which posts appear in your feed and in which order – shifts users’ political opinions in ...

This article was co-authored with Emma Myer, a student at Washington and Lee University who studies Cognitive/Behavioral Science and Strategic Communication. In today’s digital age, social media has ...

LinkedIn's algorithm has changed, making old tactics obsolete. Align your profile with content topics. Prioritize "saves" as the key engagement metric by creating valuable, referenceable content. Post ...