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Home AI News

Google’s Project Tailwind Rebrands as NotebookLM

July 15, 2023
in AI News

Google recently announced a rebranding of Project Tailwind, its AI note-taking tool. Google renamed the tool NotebookLM. Despite the name change, the product remains unchanged, as Google’s main objective is to provide users with their own personal AI assistant that leverages their data and notes to assist them in comprehending and organizing their information.

Interestingly, the foundation of NotebookLM appears to originate from Google Docs. Once granted access to the application, users can select multiple documents and use NotebookLM to inquire about them and generate new content based on the selected documents. Google is cautious about starting with a small-scale rollout. Currently, users can only access the NotebookLM through a waitlist in Google Labs.

NotebookLM Features

Google noted that NotebookLM presents various possibilities. These include automated summarization of lengthy documents and transforming a video outline into a script.

While these features are common in AI products, Google aims to enhance the model’s responses and confidently address its tendency to generate misleading information. One can achieve this by constraining the underlying model only to utilize the information the user provides.

NotebookLM is Google's new AI-driven notes application that will soon allow users to load in all the sources and data they want to "ground" a more-personal AI chat experience. https://t.co/qioI8bk6gi pic.twitter.com/C59zGSNmrh

— Chrome Unboxed (@chromeunboxed) July 13, 2023

According to Google, the model operates in a manner that limits its access to only the documents the user chooses. Furthermore, Google assures that user data remains private and is not made available to others, nor is it utilized for training new AI models. This aspect presents a challenge inherent to such products: users must share their personal information with an AI model in exchange for convenient and valuable features. The complexity of this tradeoff increases when dealing with more sensitive information.

The featured image is from boxmining.com

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