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Beyond Bots: What Else Can AI Do For Business?

Feb 26, 2024 - forbes.com
The article discusses the use of Retrieval Augmented Generation (RAG) and Stream-Trigger Augmented Generation (STAG) systems in AI. RAG systems, like OpenAI's ChatGPT, work by formulating responses to user queries using a large language model (LLM). However, they are reactive and require the user to pose a question. STAG systems, on the other hand, are proactive and continuously query on behalf of the user, analyzing streaming data to identify trends and issues.

The author suggests that businesses should use both RAG and STAG systems for a more comprehensive AI strategy. While RAG systems are popular for their user-friendly interfaces, STAG systems can unlock the value of unstructured data and provide actionable insights. The combination of RAG and STAG can support the structure behind the most transformative human teams, balancing standing responsibilities with strategic management.

Key takeaways:

  • RAG (retrieval augmented generation) and STAG (stream-trigger augmented generation) are two complementary AI architectures that can be used to enhance data analysis and user interaction.
  • While RAG is reactive and requires user queries to provide valuable responses, STAG is proactive and continuously queries on behalf of the user, providing insights on emerging trends or issues.
  • STAG systems are particularly effective at processing and contextualizing unstructured data, identifying key patterns, trends and actionable insights that would otherwise remain hidden.
  • The most effective AI deployment strategies will leverage both RAG and STAG systems in a balanced and comprehensive approach, mimicking successful human organizations.
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