Skip to main content

Difference between Google Search and Google AI Mode Search

 What is the difference between Google Search and Google AI Mode Search?

Google has been incorporating AI into Search for many years through features like Knowledge Graph and AI Overviews
. However, the recently launched AI Mode (initially available in India and the US) represents a more significant shift towards an AI-centric search experience.
Here are the key differences between traditional Google Search and Google AI Mode:
Feature Traditional SearchAI Mode (AI-powered Search)
Core FunctionProvides a list of links to web pages that match keywords or phrases.Aims to directly answer questions and provide summarized responses using generative AI.
Query TypeRelies on keyword-based searches, often requiring users to refine queries for better results.Designed to handle complex, multi-layered, and conversational queries more effectively.
OutputDisplays a list of links to web pages.Provides an AI-generated answer or summary at the top of the results, often accompanied by links to supporting websites.
InteractionPrimarily a one-time search and retrieval process.Supports follow-up questions within the same search session, fostering a more interactive and conversational experience.
PersonalizationOffers limited personalization based on factors like location and past search history.Aims to provide more personalized results by learning user behavior and preferences, potentially considering past interactions and connected Google apps like Gmail.
UnderstandingRelies on algorithms like PageRank and BERT to understand context and relevance based on keywords and links.Leverages advanced AI, including large language models like Gemini 2.5, for deeper contextual understanding, reasoning, and multi-step queries.
Input MethodsPrimarily text-based queries.Supports multimodal input, allowing users to ask questions using text, voice, or images (via Google Lens).
Website ClicksDrives traffic to websites by providing a list of links for users to explore.While it includes links to sources, the direct answers provided might reduce the number of clicks on individual website links.
LearningThe ranking algorithms are constantly updated and refined based on various factors and user behavior.Learns and improves continuously based on user interactions and feedback, potentially leading to increasingly tailored results.
Current StatusThe standard and widely used Google Search experience.Rolling out to users, initially in specific regions and languages (like English in India and the US), often through Search Labs.
In essence, Google AI Mode represents an evolution of Google Search. It moves beyond indexing and listing web pages to actively processing, synthesizing, and presenting information in a more direct, conversational, and personalized manner. It aims to provide answers and insights rather than just directing users to sources, though it still links to the web for further exploration. AI Mode is still developing, and user feedback is being gathered to refine the experience. 

Comments

Popular posts from this blog

NetScreen on Windows: Skit | Memories from 2006

[A skit written for our internal corporate event in 2006]   NetScreen on Windows: Skit    Story, Dialogue Mohan Krishnamurthy Starring: Rajesh  – An overly aggressive sales guy who believes every phone call is a golden opportunity to close a deal. Ramesh  – Rajesh’s faithful backend support, always on standby. His primary skill: Googling frantically. Mrs. Mumtaz Ali  – A practical housewife looking to buy net screens for her windows to keep out mosquitoes and houseflies. Mr. Ahmed  – Mumtaz’s husband, an average computer user who knows just enough about technology to be confused but not enough to escape Rajesh’s sales pitch. Setting: Pan-Emirates, the town’s go-to hardware shop, has its phone ringing nonstop. Rajesh’s direct number, 8915691, is often mistaken for the shop’s main line, 8915961. Typically, wrong numbers frustrate him—except today, when fate delivers an accidental lead that perfectly matches the product he sells. Time to strike! Act 1 – T...

Step-by-Step Tutorial to Create a 'Gem' with Google Gemini

 Creating a "Gem" under Google Gemini is a straightforward process that allows you to build a custom AI expert tailored to your specific needs. Here's a detailed, step-by-step tutorial on how to do it. A "Gem" is essentially a set of instructions that tells Gemini what role to play, what task to perform, and how to format its responses. Think of it as creating your own specialized version of Gemini. Step 1: Access the Gem Creation Interface Go to the Gemini web app at gemini.google.com . On the left-hand side, look for and click on Explore Gems . Click the New Gem button. Step 2: Name Your Gem The first thing you'll be prompted to do is give your new Gem a name. Choose a name that clearly reflects the Gem's purpose. For example, if you're building a Gem to help you write blog posts, you might name it "Blog Post Writer" or "Content Creator." Step 3: Write the Instructions This is the most crucial part of creating your Gem. The ins...

What are the new things happening on Internet similar to ChatGPT?

  There are a number of new developments in the field of natural language processing and machine learning that are similar to ChatGPT. Some examples include: OpenAI's GPT-3: GPT-3 is a more advanced version of GPT-2, it was released a few months after GPT-2, and it has been demonstrated to have even better performance on a number of natural language processing tasks. Google's BERT: BERT is a neural network-based model for natural language processing that has been trained on a large dataset of text and can be fine-tuned for a variety of natural language processing tasks, including sentiment analysis and question answering. Microsoft's Turing-NLG: It's similar to OpenAI's GPT-3, Turing-NLG is a text generation model that can be fine-tuned to perform a variety of natural language generation tasks, such as question answering and text summarization. Facebook's RoBERTa: RoBERTa is an optimized version of BERT, which was trained on a much larger dataset of text and has...