Deadline
Zarqa is a Neural-Symbolic Large Language Model (NS-LLM), a hybrid artificial intelligence system that combines the strengths of both neural networks and symbolic reasoning. Large Language Models (LLMs) like GPT are based on neural networks and excel at pattern recognition, natural language understanding, and generation. However, they are limited in their ability to perform logical reasoning and handle complex relationships that require more structured knowledge representation.
Neural-symbolic systems integrate symbolic reasoning with neural networks, allowing the model to reason more effectively and go beyond the patterns learned from the training data. This enables the AI to exhibit more human-like intelligence, creativity, and problem-solving capabilities. By incorporating symbolic AI techniques into LLMs, a Neural-Symbolic Large Language Model can leverage the advantages of both approaches, offering improved performance and more advanced capabilities. Such hybrid models have the potential to revolutionise various industries and contribute to the development of Artificial General Intelligence (AGI), which could represent the most significant milestone in the history of our civilization.
