Unleashing Artificial Cognition: Integrating Multiple AI Systems

TL;DR

This paper introduces a novel AI system that combines language models, query analysis, and a Chess engine with a vector database to enable explainable decision-making, demonstrating versatility for various complex tasks.

Contribution

It presents an open-source AI framework integrating multiple AI components for explainable cognition, applicable beyond Chess to fields like medicine and finance.

Findings

Successful integration of language models with a Chess engine

Use of vector database for retrievable explanations

Potential for diverse real-world applications

Abstract

In this study, we present an innovative fusion of language models and query analysis techniques to unlock cognition in artificial intelligence. The introduced open-source AI system seamlessly integrates a Chess engine with a language model, enabling it to predict moves and provide strategic explanations. Leveraging a vector database to achieve retrievable answer generation, our AI system elucidates its decision-making process, bridging the gap between raw computation and human-like understanding. Our choice of Chess as the demonstration environment underscores the versatility of our approach. Beyond Chess, our system holds promise for diverse applications, from medical diagnostics to financial forecasting. Our AI system is available at https://github.com/TheOpenSI/CoSMIC.git