Show HN: CausaNova – Deterministic runtime for LLM constraints via Ontology (petzi2311.github.io)

CausaNova, a newly introduced framework, aims to enhance the deployment of large language models (LLMs) by integrating a deterministic runtime that addresses various operational constraints through the use of ontology. This innovative kernel, equipped with features such as an active ontology defined in JSON-DSL, allows for complex rule validation and the enforcement of specific conditions, like compliance with the Geneva Convention and civilian safety checks during military simulations. By leveraging SMT (Satisfiability Modulo Theories) solver constraints, CausaNova ensures that LLMs can operate within defined ethical and performance boundaries. This development is significant for the AI/ML community as it represents a step towards making LLMs not only more adaptable but also safer and more accountable in complex environments. The ability to configure LLMs for real-time decision-making while adhering to strict rules is critical, particularly in sensitive applications such as defense and emergency response. The framework's implementation may pave the way for integrating AI operations with rigorous ethical standards, enhancing trust and reliability in AI systems deployed in real-world scenarios.