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   What is grounding in AI & large language models?

   • Grounding, in the context of AI and Large Language Models (LLMs), is a vital process that enhances the capability of AI systems to produce accurate, relevant, and contextually appropriate outputs. It involves equipping LLMs with specific, use-case-driven information not inherently included in their training data.

   Grounding in Large Language Models (LLMs) and AI

   attri.ai/generative-ai-wiki/grounding-in-large-language-models-llms-and-ai

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   Why do AI models need grounding?

   • This is because grounding gives the models a richer, more contextually nuanced understanding of the information they process. The result is an AI system that can respond more accurately to specific situations rather than relying on generalized or overly broad interpretations of data.

   Grounding in Large Language Models (LLMs) and AI

   attri.ai/generative-ai-wiki/grounding-in-large-language-models-llms-and-ai

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   What is Ai grounding?

   • AI grounding encompasses the strategies and techniques that anchor the learning and decision-making processes of AI in real-world data and environments. Here’s how Grounded AI helps users;

   What Is Grounding? - All About AI

   www.allaboutai.com/ai-glossary/grounding/

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   What are the benefits of a grounded AI system?

   • Improving Reliability and Relevance: Grounded AI systems are more reliable and relevant, as they are trained and tested on data reflecting real-world conditions and variances. Adaptability to Real-World Changes: Grounding allows AI systems to adapt and evolve with changing real-world scenarios, maintaining their effectiveness over time.

   What Is Grounding? - All About AI

   www.allaboutai.com/ai-glossary/grounding/

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   Why is grounding important in AI decision-making?

   • Exploring the necessity of grounding in AI decision-making, this section delves into how real-world integration enhances AI’s accuracy, reliability, and adaptability in diverse scenarios. Provides a reality check: Grounding ensures that AI decisions are not just theoretically sound but also practical and applicable in real-world scenarios.

   What Is Grounding? - All About AI

   www.allaboutai.com/ai-glossary/grounding/

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   Why is grounding important in AI & LLM development?

   • Grounding is a critical aspect of AI and LLM development, playing a pivotal role in enhancing the accuracy, relevance, and effectiveness of AI-generated content. By grounding AI in real-world contexts and specific use cases, developers can create AI systems that are not only intelligent but also reliable and trustworthy.

   Grounding in Large Language Models (LLMs) and AI

   attri.ai/generative-ai-wiki/grounding-in-large-language-models-llms-and-ai

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2. cloud.google.com › vertex-ai › generative-aiGrounding overview | Generative AI on Vertex AI - Google Cloud

   cloud.google.com › vertex-ai › generative-ai

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   4 days ago · In generative AI, grounding is the ability to connect model output to verifiable sources of information. If you provide models with access to specific data sources, then...

   • RAG and grounding on Vertex AI | Google Cloud Blog

     Grounding with high-fidelity mode, announced in experimental...

3. www.allaboutai.com › ai-glossary › groundingWhat Is Grounding? - All About AI

   www.allaboutai.com › ai-glossary › grounding

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   Oct 11, 2024 · The main purpose of grounding in AI is to enhance the accuracy, reliability, and applicability of AI systems. It ensures that AI decisions and outputs are relevant, practical, and based on actual data and scenarios, thereby increasing the trustworthiness and effectiveness of AI applications.

4. techcommunity.microsoft.com › t5 › fasttrack-forGrounding LLMs - Microsoft Community Hub

   techcommunity.microsoft.com › t5 › fasttrack-for

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   Jun 9, 2023 · What is Grounding? Grounding is the process of using large language models (LLMs) with information that is use-case specific, relevant, and not available as part of the LLM's trained knowledge. It is crucial for ensuring the quality, accuracy, and relevance of the generated output.

5. Videos

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     Grounding AI Explained: How to stop AI hallucinations

     20 Apr 2023

     6.5K views

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     AI 900 — Grounding

     13 Jan 2024

     155 views

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     Vertex AI Embeddings API + Matching Engine: Grounding LLMs made easy

     19 Jul 2023

     20.7K views

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6. www.salesforce.com › blog › ai-groundingHow To Prepare a Knowledge Base for AI Grounding | Salesforce

   www.salesforce.com › blog › ai-grounding

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   Jun 3, 2024 · What is grounding in generative AI? The term “grounding” means augmenting your AI-generated content by connecting the model your AI uses with information from verified sources. Grounding, also known as retrieval-augmented generation (RAG), ensures that your AI-generated content is both accurate and specific to your organization.

7. attri.ai › generative-ai-wiki › grounding-in-largeGrounding in Large Language Models (LLMs) and AI

   attri.ai › generative-ai-wiki › grounding-in-large

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   Explore the vital role of grounding in AI and Large Language Models (LLMs), a key process for ensuring accurate, relevant, and context-sensitive AI outputs. Dive into techniques, importance, and applications for grounding AI models, making them more effective in real-world scenarios.

8. www.miquido.com › ai-glossary › groundingUnderstanding Grounding in AI - Miquido

   www.miquido.com › ai-glossary › grounding

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   What is Grounding in AI? Grounding in AI refers to the ability of an generative artificial intelligence system to connect its understanding and language generation to the real world or a shared knowledge base.

9. cloud.google.com › rag-and-grounding-on-vertex-aiRAG and grounding on Vertex AI | Google Cloud Blog

   cloud.google.com › rag-and-grounding-on-vertex-ai

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   Jun 27, 2024 · Grounding with high-fidelity mode, announced in experimental preview today, is a new feature of our grounded generation API that will further reduce hallucinations. Grounding with third-party...