Building a Smarter AI Assistant: Real-Time Web Search Meets Hyperdimensional Computing and Symbolic Reasoning

Introduction

Artificial Intelligence (AI) systems have advanced tremendously but despite impressive progress, one of the key limitations remains static knowledge. AI models, like GPT or Qwen are trained on a snapshot of data and in turn they lack the ability to continuously learn from new information in real-time.

For example, an AI model trained on data from 2022 may not be able to provide accurate information about events or developments that happened in 2023. To address this limitation, I’ve designed a system that not only uses symbolic reasoning with hyperdimensional computing (HDC) but also dynamically queries the web for up-to-date information thus seamlessly integrating these elements into a robust reasoning engine.

This article will take you through the technical landscape of building this AI system, showing how it balances real-time knowledge retrieval, symbolic reasoning, and memory consolidation to deliver more intelligent, context-aware responses.