Knowledge Engineering with Bradley Allen - Weaviate Podcast #139!
From Weaviate Podcast by Weaviate
June 1, 2026 · 1h 1m
About this episode
Dr. Bradley Allen discusses the evolution of AI and knowledge engineering, exploring various concepts and challenges in the field.
Dr. Bradley Allen brings five decades of AI history into a deep conversation on knowledge engineering, neurosymbolic AI, and the future of enterprise intelligence. The discussion begins with the boom-and-bust cycle of rule-based expert systems, AI winters, and why today’s large language model wave may be different. The conversation then turns to how knowledge is organized in practice, from personal piles of papers searched on demand to formal knowledge graphs built with classes, relations, ontologies, A boxes, T boxes, description logic, and subsumption-based reasoning. Allen explains why semantic web and biomedical ontology successes still leave unresolved questions about cost, maintenance, and whether LLMs can dynamically structure information in ways that preserve meaning. That leads into natural language concept definitions, LLM-based classifiers, rationales, probabilistic reasoning, and the challenge of updating classes as new edge cases emerge.From there, the focus widens to vector databases, semantic search, RAG, topic modeling, distributional semantics, and the ongoing revision required for systems that can never be “once and done.” Allen connects modern LLM behavior to…
People in this episode
Host: Weaviate
Guest: Dr. Bradley Allen
Topics covered
- knowledge engineering
- neurosymbolic AI
- enterprise intelligence
- semantic web
- vector databases
- natural language processing
Keywords
- AI history
- knowledge graphs
- LLMs
- semantic search
- probabilistic reasoning
- reinforcement learning
Mentioned in this episode
Organizations: Weaviate
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