NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — ...

Retrieval-augmented generation enhances the performance of AI agents by expanding their recall. It can do this in three ...

Researchers at the Tokyo-based startup Sakana AI have developed a new technique that enables language models to use memory more efficiently, helping enterprises cut the costs of building applications ...

The AI was smarter than the person setting it up ...

A new technical paper titled “MLP-Offload: Multi-Level, Multi-Path Offloading for LLM Pre-training to Break the GPU Memory Wall” was published by researchers at Argonne National Laboratory and ...

The artificial intelligence (AI) boom has awakened the traditionally cyclical memory and storage sector, driving extraordinary performance for hardware companies that provide the High-Bandwidth Memory ...

Large language models (LLMs) like GPT and PaLM are transforming how we work and interact, powering everything from programming assistants to universal chatbots. But here’s the catch: running these ...

"A blank-slate design for modern LLM inference, not a general-purpose accelerator adapted from earlier AI workloads" ...

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...