The article discusses a systematic approach for evaluating large language models (LLMs) in conversational chatbots due to rapid advancements in AI technology. Key factors include latency, cost, instruction following, and maintainability. The process involves both objective testing with metrics and subjective evaluation by human reviewers to assess model performance within specific contexts. The main takeaway is the importance of thorough testing within one's own system rather than relying solely on benchmarks or documentation.
Read the full article at Towards AI - Medium
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