Knowledge in Animals and Machines
Drawing on philosophical theories of knowledge, I develop a conceptual framework for knowledge in animals and machines. I use this framework to engineer a new concept of large language model (LLM) knowledge and propose a taxonomy of knowledge that spans biological and artificial categories, from C. elegans to LLMs. The approach lays a foundation for a rigorous account of how knowledge can be realized across animals and machines while at the same time respecting the diverse biological and physical sources of such knowledge.
Authors
- L. A. Paul
Institutions
- Munich School of Philosophy (DE)
- Yale University (US)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- Journal of Neuroscience
- Published
- 2026-01-07
- DOI
- https://doi.org/10.1523/jneurosci.0939-25.2025
- Primary Topic
- Language and cultural evolution
- Type
- article
- Field-Weighted Citation Impact
- 0.00