Improving LLMs
Thomas discusses the challenges of improving LLMs and the limitations of current knowledge bases, highlighting the need for unsupervised learning and the ability to ask and tell information accurately.In this clip
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The Gradient
Thomas Dietterich: From the Foundations
Related Questions
Is this large language model (LLM) subject to hallucinations?
I'm thinking that classical or deep ML solutions have a flaw in that they cannot be extended. For example, if one builds a model and wants to introduce a new feature, typically the model has to be retrained from scratch. So, I'm considering building a Knowledge Graph using LLMs. This knowledge graph would have to include time-dependent data (for example, it should be able to retrieve the "current" President of the USA and also previous presidents if asked). I'm thinking this Knowledge Graph could be used for Retrieval Augmented Generation (RAG) to help with business goals or maybe used with more clever User Interfaces (UIs). I'm not sure how to build or populate this KG and also have a rough idea of how to use it. Can you help me with suggesting particular paths for building and populating this Knowledge Graph?