You ain’t seen nothing yet on the ChatGPT road CanadiansInvest
and the subsequent announcements of similar products and massive investments by competitors suggest we are at the beginning of many exciting advances.
Emerging LLMs are developing techniques to enhance their training data and compensate for these gaps. For example: At least one research group asks the LLM model to reflect on its answer and refine it before presenting it. Emerging LLMs divide their parameters into subject domains to create sparse models or multiple sub-models. LLMs then process just the sub-model parameters corresponding to the query’s domain.
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