Interview with Jans Aasman, CEO of Franz, Inc.
Image by Gerd Altmann from Pixabay
Jans Aasman’s AI background goes back to his training as a cognitive scientist at the University of Groningen in the Netherlands beginning in 1978.
Jans Aasman, CEO of Franz, Inc.
Since then, he’s seen over 40 years of AI’s evolution. Throughout that time, he’s been hands on with a range of modeling techniques, from LISP and Prolog, to description logic and statistical machine learning.
Jans is the CEO of Franz, Inc., which started as a LISP compiler company. Under his leadership, Franz designs enterprise-class graph database management systems (DBMSes) used for metadata-rich knowledge graph development. Now the company is at the leading edge of neurosymbolic or composite AI, the kind of AI that effectively blends three different branches of AI, as shown in this diagram:
Illustration courtesy of Franz, Inc.
One of the key advantages to using the semantic graph database approach that Jans describes is a continual learning loop. “Any analytics you ever do needs to go back into the database. You need to store the provenance, so you can go back and review a prediction,” Jans says. “If you don’t store all the metadata, within a few months, you don’t know what happened anymore.”
Toward the end of the interview, Jans elaborates on the beginnings of an agent-oriented knowledge graph, one you can talk to. This sort of composite AI, soon to be available in Allegrograph 8.2, makes it possible to blend these elements together:
- The precision of logic
- LLM chatbot interface capabilities
- The relevance of wide range of heterogeneous data sources a knowledge graph approach can make interoperable
- The complex data handling and boundary crossing graph query generation capabilities of graph database management systems
Hope you find this conversation as illuminating as I have.
Interview with Jans Aasman, CEO of Franz, Inc.
