One challenge organizations face when customizing large language models (LLMs) is the need to run multiple experiments, which produces only one useful model….
One challenge organizations face when customizing large language models (LLMs) is the need to run multiple experiments, which produces only one useful model. While the cost of experimentation is typically low, and the results well worth the effort, this experimentation process does involve “wasted” resources, such as compute assets spent without their product being utilized…
