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Benchmarking Domain Intelligence | Data Brew | Episode 45
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Manage episode 478821138 series 2814833
In this episode, Pallavi Koppol, Research Scientist at Databricks, explores the importance of domain-specific intelligence in large language models (LLMs). She discusses how enterprises need models tailored to their unique jargon, data, and tasks rather than relying solely on general benchmarks.
Highlights include:
- Why benchmarking LLMs for domain-specific tasks is critical for enterprise AI.
- An introduction to the Databricks Intelligence Benchmarking Suite (DIBS).
- Evaluating models on real-world applications like RAG, text-to-JSON, and function calling.
- The evolving landscape of open-source vs. closed-source LLMs.
- How industry and academia can collaborate to improve AI benchmarking.
44 episodi
Fetch error
Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on October 30, 2025 14:27 ()
What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.
Manage episode 478821138 series 2814833
In this episode, Pallavi Koppol, Research Scientist at Databricks, explores the importance of domain-specific intelligence in large language models (LLMs). She discusses how enterprises need models tailored to their unique jargon, data, and tasks rather than relying solely on general benchmarks.
Highlights include:
- Why benchmarking LLMs for domain-specific tasks is critical for enterprise AI.
- An introduction to the Databricks Intelligence Benchmarking Suite (DIBS).
- Evaluating models on real-world applications like RAG, text-to-JSON, and function calling.
- The evolving landscape of open-source vs. closed-source LLMs.
- How industry and academia can collaborate to improve AI benchmarking.
44 episodi
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