Denys Linkov, Head of Machine Learning at Voiceflow, discusses the vital role of micro metrics in evaluating large language models (LLMs). He highlights how granular assessment enhances user experience and business value. The conversation touches on the challenges of measuring relevant aspects like user engagement and emotional responses from AI. Linkov also delves into prompt engineering complexities and the importance of automated evaluation frameworks. Lastly, he shares insights on AI orchestration for better customer support, focusing on customizable workflows.
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insights INSIGHT
Micro Metrics for User Experience
Micro metrics measure specific user experience issues.
These metrics tie to business value, unlike broader metrics like accuracy.
question_answer ANECDOTE
Language Switching Issue
Voiceflow encountered an issue with LLMs switching languages mid-conversation.
Implementing a retry mechanism solved 99% of these issues.
volunteer_activism ADVICE
Practical LLM Development
Don't aim for LLM perfection; focus on nuanced trade-offs in production.
Leverage domain expertise to define relevant metrics.
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Live from the QCon San Francisco Conference, we are talking with Denys Linkov, Head of Machine Learning at Voiceflow. Linkov shares insights on using micro metrics to refine large language models (LLMs), highlighting the importance of granular evaluation, continuous iteration, and rigorous prompt engineering to create reliable and user-focused AI systems.
Read a transcript of this interview: https://bit.ly/49tOvt8
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