Symbolic AI

Symbolic AI, aiming to imbue artificial intelligence with human-like reasoning and explainability, seeks to integrate the strengths of symbolic logic and reasoning with the learning capabilities of connectionist (neural network) approaches. Current research focuses on hybrid neuro-symbolic architectures, such as Logic Tensor Networks and neuro-vector-symbolic systems, to improve model interpretability, generalization, and robustness while leveraging the power of large language models. This interdisciplinary field holds significant promise for advancing AI safety, trustworthiness, and the development of more reliable and explainable AI systems across diverse applications, including cybersecurity and healthcare.