HawkinsDB: Neuroscience-Inspired Memory Architecture for Smarter LLM Applications

HawkinsDB: A Neuroscience-Inspired Memory Layer for Smarter LLM Applications While the AI industry obsesses over model size, true intelligence requires more than parameters—it demands functional memory systems. HawkinsDB reimagines AI memory architecture by bridging neuroscience principles with engineering rigor, offering language models a human-like approach to storing and recalling information. The Limitations of Current AI Memory Systems Traditional vector databases and embedding techniques face three critical shortcomings: Fuzzy Matching Fallacy Similarity-based searches often yield irrelevant results—like finding books by cover color instead of content. Data Silos Syndrome Factual knowledge, contextual experiences, and procedural workflows remain isolated. Black Box Dilemma Unexplainable …