Analog AI

Analog AI's Memory Engine has achieved a remarkable milestone: it scored a record 79.2% Exact Match (EM) on the HotpotQA benchmark, alongside an impressive 85.5% F1 score . This performance, combined with 91% precision in LLM evaluations, demonstrates near human-level comprehension in multi-hop question answering and reasoning tasks. At its core, the Analog AI Memory Engine works by connecting entities and relationships through a structured graph network . Nodes represent key entities (people, concepts, events, etc.), while edges capture the relationships between them. This graph-based approach under the hood enables rich, interconnected knowledge representation that goes far beyond flat vector embeddings or traditional retrieval systems. One of the standout advantages is speed: the engine is 5-6x faster at "remembering" and retrieving information compared to similar projects. This efficiency makes it highly feasible for real-life interactions, especially where livin...