Graphs for Inference
Lately I’ve become intrigued about the published research + open source code for a relatively specific topic: generating graphs to use for inference.
This category seems to be becoming popular as means for blending LLM use with graph technologies to obtain more grounded results. By other names “Hybrid AI” might be a good general description for this category, or as one of the flavors of “Neurosymbolic AI” — though frankly I’m not as much of a fan of the latter terminology. To wit, how can we blend the benefits of machine learning and generative approaches with symbolic inference?
See the full article at: https://blog.derwen.ai/graphs-for-inference-684d73d8b59c
In general, I’m tracking new papers in this category using a Hugging Face collection: https://huggingface.co/collections/pacoid/graph-reasoning-6556546cdd1c096392f1095e
Kudos to Jürgen Müller and Shachar Klaiman at BASF for hiking uphill at a reasonable pace then engaging in many varied graph technologies discussions over Peruvian cuisine in old town Heidelberg.
Featured image: Heidelberger Schloss, the backdrop for recent graph discussions