Long-term memory is essential for large language model (LLM) agents operating in complex environments, yet existing memory designs are either task-specific and non-transferable, or task-agnostic but ...

Abstract: We consider the issue of the memory bandwidth required for the transfer of weights of an LLM between the memory and the processor (CPU or GPU). Observing that a few exponent values dominate ...

Nota AI Reduces Memory Usage of Upstage's Solar LLM by 72%, Demonstrating Proprietary Quantization Technology PR Newswire SEOUL, South Korea, March 5, 2026 New "Nota AI MoE Quantization" approach ...

Enterprise AI applications that handle large documents or long-horizon tasks face a severe memory bottleneck. As the context grows longer, so does the KV cache, the area where the model’s working ...

SEOUL, South Korea, March 5, 2026 /PRNewswire/ -- Nota AI, an AI optimization technology company behind the Nota AI brand, announced that it has developed a next-generation quantization technology ...

As more organizations run their own Large Language Models (LLMs), they are also deploying more internal services and Application Programming Interfaces (APIs) to support those models. Modern security ...

The generative AI boom minted a startup a minute. But as the dust starts to settle, two once-hot business models are looking more like cautionary tales: LLM wrappers and AI aggregators. Darren Mowry, ...

Automation has long been part of the discipline, helping teams structure data, streamline reporting, and reduce repetitive work. Now, AI agent platforms combine workflow orchestration with large ...

In this tutorial, we build a self-organizing memory system for an agent that goes beyond storing raw conversation history and instead structures interactions into persistent, meaningful knowledge ...

The saying “round pegs do not fit square holes” persists because it captures a deep engineering reality: inefficiency most often arises not from flawed components, but from misalignment between a ...