CyC

Cyc is a long-running artificial intelligence project that aims to codify common-sense knowledge into a comprehensive, machine-readable knowledge base and an accompanying inference engine. Initiated in 1984 as The Cyc Project by Douglas Lenat at MCC, it has been developed and commercialized by Cycorp, a company based in Austin, Texas.

The core of Cyc is the Cyc knowledge base, consisting of millions of assertions expressed in CycL, a formal language for representing general knowledge and rules. The system organizes information with taxonomies, relations, contexts called microtheories, and a broad ontology spanning domains such as physical objects, events, social norms, and goals. Inference proceeds through forward and backward chaining on the rules and facts, enabling tasks such as question answering, planning, and natural-language understanding.

Development approach: Cyc relies heavily on hand-authored knowledge and curation to encode common sense that is often implicit in human reasoning. The project has experimented with hybrid reasoning, combining symbolic logic with heuristics. An open-source subset, OpenCyc, was released to the public to facilitate experimentation, though the core Cyc platform remains proprietary in commercial use.

Applications and impact: Cyc has been used for enterprise knowledge integration, semantic search, and natural-language interfaces in some corporate settings. It has influenced research in knowledge representation, ontologies, and common-sense reasoning, highlighting both the potential and the scaling challenges of large, curated knowledge bases.

Limitations and status: Critics cite the resource-intensive nature of maintaining comprehensive knowledge bases and gaps in coverage across domains. Cyc remains one of the longest-running endeavors in common-sense AI, continuing to evolve with new datasets and tooling.