17:49 LLMs as Knowledge Base 23:26 Knowledge Graphs 25:30 Use of Ontology in AI 27:31 Use of Knowledge Graph in Business 29:25 Model Journeys 32:26 Learning Over Graph 35:02 Lowest Hanging Fruit: Based On Practical Use case 50:03 Overview of Approaches 1:11:53 Knowledge Graphs enhanced by LLMs.
I imagine you can keep adding more loops into this to form better guard rails. While I know nothing about this yet really, it seems like an answer generated by the LLM could be fed into a/another BERT LLM. The relations generated by this BERT could then be compared to the original knowledge graph again for consistency. Any inconsistencies could be fed back to a GPT model to form a new prompt. This prompt would ask for another iteration on the originally generated answer to fix the inconsistencies found. Very interesting video. Thank you!
Excellent content Rudy!
I have never commented on any video, but here - Please do post more content :-)
17:49 LLMs as Knowledge Base
23:26 Knowledge Graphs
25:30 Use of Ontology in AI
27:31 Use of Knowledge Graph in Business
29:25 Model Journeys
32:26 Learning Over Graph
35:02 Lowest Hanging Fruit: Based On Practical Use case
50:03 Overview of Approaches
1:11:53 Knowledge Graphs enhanced by LLMs.
Excellent presentation which clearly delineates the need and benefits of integrating different AI tools to meet business and personal objectives,
Awesome content, one of the best videos
Excellent thanks for sharing
Post more, please, Rudy :)
Would love an update on this video based on today’s developments and technologies!
Great overview, thanks for posting
Hope you make more long vids like this! Keep sharing 😁 there are very few people talking about KG's
Thank you. It is a very useful information
I imagine you can keep adding more loops into this to form better guard rails. While I know nothing about this yet really, it seems like an answer generated by the LLM could be fed into a/another BERT LLM. The relations generated by this BERT could then be compared to the original knowledge graph again for consistency. Any inconsistencies could be fed back to a GPT model to form a new prompt. This prompt would ask for another iteration on the originally generated answer to fix the inconsistencies found.
Very interesting video. Thank you!
Incredible!