Information retrieval systems are designed to satisfy a user. To make a user happy with the quality of their recall. It’s important we understand that. Every system and its inputs and outputs are ...

Retrieval augmented generation (RAG) has quickly risen to become one of the most popular architectures when building AI assistants, especially in scenarios where combining the power of language models ...

What is Google TurboQuant, how does it work, what results has it delivered, and why does it matter? A deep look at TurboQuant, PolarQuant, QJL, KV cache compression, and AI performance.

What if the way we retrieve information from massive datasets could mirror the precision and adaptability of human reading—without relying on pre-built indexes or embeddings? OpenAI’s latest ...