Just last night I took a similar approach to arriving a number of paths to take when I shared my desired output with a knowledge graph that I had populated and asked the AI to fill in the blank about the activities that would lead a user to my desired output. it worked! I got a few none-corralative gaps that came up as well and after some fine tuning, got included in the graph to enrich the contentious output.
I feel this is a similar approach and it's our job to populate and understand the gaps in between if we are trying to understand how these relationships came to existence. a visual mind map of the nodes and the entire network is a big help for a visual learner like myself to see the context of LLMs better.
anyway, the tool I used is InfraNodus and am curious if this community is aware of it, I may have even discovered it on HN actually.
Just last night I took a similar approach to arriving a number of paths to take when I shared my desired output with a knowledge graph that I had populated and asked the AI to fill in the blank about the activities that would lead a user to my desired output. it worked! I got a few none-corralative gaps that came up as well and after some fine tuning, got included in the graph to enrich the contentious output.
I feel this is a similar approach and it's our job to populate and understand the gaps in between if we are trying to understand how these relationships came to existence. a visual mind map of the nodes and the entire network is a big help for a visual learner like myself to see the context of LLMs better.
anyway, the tool I used is InfraNodus and am curious if this community is aware of it, I may have even discovered it on HN actually.