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AI assistants often cannot be trained on user-provided data, highlighting RAG complexities

By PulseAugur Editorial · [2 sources] ·

The common question of whether an AI assistant can be trained on specific data is often met with a negative response, highlighting limitations in current AI capabilities. While Retrieval-Augmented Generation (RAG) is typically viewed as a straightforward process, the reality of its implementation and the underlying complexities of AI training are more nuanced. This discussion touches upon the practical challenges and user expectations surrounding AI model training and data integration. AI

IMPACT Highlights current limitations in AI's ability to be trained on specific user data, managing expectations for AI assistant capabilities.

RANK_REASON The cluster discusses common user questions and AI assistant responses regarding data training, touching on RAG complexities without announcing a new product or research.

Read on Mastodon — sigmoid.social →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

AI assistants often cannot be trained on user-provided data, highlighting RAG complexities

COVERAGE [2]

  1. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    Retrieval-Augmented Generation (RAG) is often described as a simple pipeline: Query → Retrieve documents → Send context to an LLM → Generate answer In productio

    Retrieval-Augmented Generation (RAG) is often described as a simple pipeline: Query → Retrieve documents → Send context to an LLM → Generate answer In production, however, retrieval is rarely that simple. The retriever can return irrelevant documents. Important information may be…

    LINKS dev.to/…/9-rag-techniques-that-actually-i…
  2. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    "Can we just train the model on this data together?" is one of the most common things people ask an AI assistant. And almost every time, the answer comes back:

    "Can we just train the model on this data together?" is one of the most common things people ask an AI assistant. And almost every time, the answer comes back: "Let's use RAG instead." That answer sounds like a dodge if you don't know what's actually happening underneath it. It i…

    LINKS dev.to/…/training-vs-rag-whats-actually-d…

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