Just after I sent my previous note, I saw the reference to a 63-page article with a title and direction that I strongly endorse: Cognition is All You Need, The Next Layer of AI Above Large Language Models .  

Since I only had time to flip the pages, look at the diagrams, and read some explanations, I can't say much more than I strongly endorse the direction as an important step beyond LLMs.   I would ask the questions in my previous note:  Can their cognitive methods do the evaluation necessary to avoid the failures (hallucinations) of generative AI?  

Since I have recommended the term 'neuro-cognitive' as an upgrade to 'neuro-symbolic', I believe that future research along lines that the authors discuss is a promising direction.   Even more important, their methods can use ontologies to check and evaluate whatever LLMs produce.  Since ontology is the primary theme of this forum, it's good to see that ontology will still be needed for a long time to come.

As I said in my previous note, generative AI without something that can evaluate the results cannot be trusted as a foundation for advanced AI systems.   Cognitive AI is a good term for that something.  This article is more of a promise than a finished solution.   But the directions they recommend are related to the Cognitive Memory System of our old VivoMind company.  See https://jfsowa.com/talks/cogmem.pdf .

In fact, our current Permion.ai company is developing tools that combine LLMs with an extension of the cognitive methods of VivoMind.  And by the way, the Permion methods can use as much computational power as available.  But they can also run very effectively on just a large laptop with a disk drive of a couple of terabytes.  All the old VivoMind technology was developed on the laptops of that generation, and its performance could be extended linearly to the very large computer systems of our customers.

John

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From: "Nadin, Mihai" <nadin@utdallas.edu>
Subject: [ontolog-forum] an alternative