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By Convai
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Knowledge Bank Feature for AI Grounding
๐ The Knowledge Bank feature addresses the inaccuracy of large language models (LLMs) by grounding the AI in provided content.
๐งช Initially, an AI character (Mason Stone, expert on European monuments) provided an inaccurate size (8 cm) for Notre Dame staples when asked about recent research.
๐ By uploading a 100+ page document containing the accurate detail (staples were 20 inches long) to the Knowledge Bank, the character subsequently provided the correct answer.
Application Examples
๐ฑ For a product expert character (Macy Markup), uploading a 50-page product catalog corrected the battery life information for the "Oxy Pulse Pro" from an invented figure to the accurate 16 hours of continuous operation.
๐ก This feature is highly valuable for creating reliable AI characters for learning/training applications, metaverse assistance, information centers, and non-player characters (NPCs) versed in specific lore.
Key Points & Insights
โก๏ธ Grounding LLMs using the Knowledge Bank is essential for serious applications where factual accuracy is critical, overcoming the tendency for models to generate plausible but incorrect responses.
โก๏ธ The process involves uploading text files (e.g., books, documents) to the Knowledge Bank and then connecting that learned information to a specific AI character.
โก๏ธ After connecting new data, the AI uses the provided source material, demonstrated by correcting the Notre Dame staple size from 8 cm to nearly 20 inches long.
๐ธ Video summarized with SummaryTube.com on Mar 10, 2026, 02:38 UTC
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Full video URL: youtube.com/watch?v=yXzU8jooAB0
Duration: 3:43

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