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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

At the start of 2025, I predicted the commoditization of large language models. As token prices collapsed and enterprises moved from experimentation to production, that prediction quickly became ...

In the 1920s, a Russian journalist named Solomon Shereshevsky became famous for his extraordinary memory. He could memorize and repeat up to 70 unrelated words, provided they were read about three ...

A massive international brain study has revealed that memory decline with age isn’t driven by a single brain region or gene, but by widespread structural changes across the brain that build up over ...