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The opaque nature of large language models (LLMs) is one of the biggest challenges preventing organizations from getting great AI concepts into production.

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Traditional machine learning evaluation techniques simply fall short with LLMs and new LLM evaluation frameworks seem to be popping up every week. What’s the right approach for your RAG and fine-tuning use cases? In this webinar, our AI experts discuss how to evaluate LLM effectiveness and risks.

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Attendees will learn:

• Tips for defining clear objectives for what the LLM should achieve.
• What performance metrics to assess for accuracy, relevance, response time, toxicity and user satisfaction.
• Error analysis identification and categorization.
• Benchmarking considerations.
• How and when to consider qualitative user feedback.

Watch the recording