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Best of Both Worlds A.I.: Data Consistency and Deep Reserach

  • Jack Lau
  • 11月14日
  • 讀畢需時 3 分鐘

Dear Friends,

By now, most of us have used a public AI chatbot. But for many business leaders, a key question remains: "How can I trust it with my data? How do I stop it from 'hallucinating' and giving me answers that sound good but are factually wrong?"

This is the central problem we must solve. We are all looking for a way to move AI from a public "toy" to a private, reliable "tool."



Quick Summary


I've been prototyping a "Hybrid AI" model that I believe is the solution. It works by combining two key pieces of Google's technology:

  1. The "Brain" (Gemini): A powerful, creative reasoning engine.


  2. The "Sources" (NotebookLM): A private, grounded knowledge base built from your documents.



By forcing the "Brain" to only get its facts from your "Sources," we get the best of both worlds: powerful reasoning without the risk of public hallucinations. This is the key to unlocking secure, deep research on your own proprietary data.


What Are Gemini and NotebookLM?


For those not familiar, let's quickly define these two tools. They represent the two halves of the perfect AI assistant:

  • Google Gemini: You can think of Gemini as the powerful "Brain." It's a "Large Language Model" (LLM) with incredible abilities in reasoning, summarizing, and understanding complex ideas. It's the creative engine that can synthesize information. But, left on its own, it draws from the entire public internet and can sometimes make mistakes.

  • Google NotebookLM: This is the "Sources." It's a completely different tool. You can think of it as an intelligent, private notebook. You upload your documents—company reports, sales data, product specs, meeting notes—and NotebookLM becomes an expert only on the information you provided. Its knowledge is "grounded" in your facts.



The Big Idea: Connecting the Brain to the Sources


The problem with the "Brain" (Gemini) is that it doesn't know your private business. The problem with the "Sources" (NotebookLM) is that it's designed to be a closed system.


My experiment was to build a bridge. What if we could use the power of the Gemini "Brain" but force it to only reason over the facts provided by your NotebookLM "Sources"?

This "Hybrid AI" model means you get all the benefits of advanced reasoning without the risk of data leaks or factual errors. The AI is required to cite its sources—sources that you provided and trust.


Why This Matters: From Chatbot to Deep Research Tool


For senior leaders, this isn't just a technical curiosity. This is how AI becomes a serious business tool.

This hybrid approach unlocks the ability to perform deep research on your own proprietary data.


  • Before: You might ask a public chatbot, "What are good strategies for market entry?"

  • After: You can ask your private Hybrid AI, "Based on our last 10 board reports and all of our Q3 sales data, what are the top 3 risks our team has identified for our European expansion, and what were the proposed mitigations?"

This is the difference between a novelty and a strategic advantage. It's an expert assistant that has read all your company's documents and is ready to provide trusted, verifiable insights.


See It in Action


This is more than just theory. I've put together a small prototype to show exactly how this works. I’ve recorded a video to walk through the concept and published the code for those who want to see the "how" behind the "what."

I believe this hybrid approach is the practical, grounded, and useful AI we've been waiting for. Let me know what you think.

 
 
 

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