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Will DataGemma models reduce hallucination rates in LLMs by March 31, 2025?
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Google•DataGemma•Data Commons•Retrieval Interleaved Generation•Retrieval Augmented Generation•Gemma•UN•WHO•GoogleDeepMind
Resolution / Starting Odds
Yes • 50%
No • 50%
Peer-reviewed research publications or official GoogleDeepMind reports
Story
GoogleDeepMind Releases DataGemma and Gemma 2 to Enhance LLM Accuracy with Real-World Data
Sep 12, 2024, 01:14 PM
Google has released DataGemma, a series of open models designed to enhance the factual accuracy of large language models (LLMs) by grounding them with real-world data from Data Commons. DataGemma employs Retrieval Interleaved Generation (RIG) and Retrieval Augmented Generation (RAG) techniques to reduce LLM hallucinations. The models, including Gemma 2, are fine-tuned for these approaches to incorporate public statistical data, thereby improving the reliability and responsibility of AI outputs. Data Commons is a publicly available knowledge graph containing over 240 billion data points across hundreds of thousands of statistical variables, sourced from trusted organizations like the UN and WHO. The release was announced by GoogleDeepMind.
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Similar markets
Yes • 50%
No • 50%
Retrieval Interleaved Generation (RIG) • 25%
Retrieval Augmented Generation (RAG) • 25%
Both RIG and RAG • 25%
Other • 25%
Reduction in hallucinations • 25%
Improvement in factual accuracy • 25%
Enhanced numerical and statistical data integration • 25%
Other • 25%
Yes • 50%
No • 50%
Yes • 50%
No • 50%
Yes • 50%
No • 50%
Yes • 50%
No • 50%
