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Let's make chatbots smarter using REAPER
Data Science   Latest   Machine Learning

Let's make chatbots smarter using REAPER

Manpreet Singh
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October 9, 2024
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Last Updated on November 3, 2024 by Editorial Team

Author(s): Manpreet Singh

Originally published on Towards AI.

This member-only story is on us. Upgrade to access all of Medium.

Picture this: you’re online, chatting with a shopping assistant about your order, or you’re curious if a phone you’re eyeing is compatible with your new earbuds. The chatbot, quick as lightning, responds with precise information — almost as if it knows you personally. What you don’t see is the fascinating technology making it all happen.

Credit: https://unsplash.com/illustrations/a-man-running-with-a-book-and-a-cell-phone-35Sqe_mCcGw

One fine day, while researching, I found a paper mentioning a term REAPER. Then I find out it's a brand-new approach to handling these complex tasks that transform how chatbots work behind the scenes. Today, we’re going to break down REAPER and see why it’s a game-changer for conversational systems.

First lets understand what Are RAG Systems, and Why Do They Matter?

Let’s start with something called RAG, which stands for Retrieval Augmented Generation. It’s a fancy term, but it boils down to this: chatbots use massive amounts of data to respond accurately to your questions. Instead of just making things up from what they know, they go out and fetch specific facts — kind of like a librarian hunting down the exact book or article you need. This ensures the answers you get are not… Read the full blog for free on Medium.

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} strongTag.remove(); }); }); } removeStrongFromHeadings(); "use strict"; window.onload = () => { /* //This is an object for each category of subjects and in that there are kewords and link to the keywods let keywordsAndLinks = { //you can add more categories and define their keywords and add a link ds: { keywords: [ //you can add more keywords here they are detected and replaced with achor tag automatically 'data science', 'Data science', 'Data Science', 'data Science', 'DATA SCIENCE', ], //we will replace the linktext with the keyword later on in the code //you can easily change links for each category here //(include class="ml-link" and linktext) link: 'linktext', }, ml: { keywords: [ //Add more keywords 'machine learning', 'Machine learning', 'Machine Learning', 'machine Learning', 'MACHINE LEARNING', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, ai: { keywords: [ 'artificial intelligence', 'Artificial intelligence', 'Artificial Intelligence', 'artificial Intelligence', 'ARTIFICIAL INTELLIGENCE', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, nl: { keywords: [ 'NLP', 'nlp', 'natural language processing', 'Natural Language Processing', 'NATURAL LANGUAGE PROCESSING', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, des: { keywords: [ 'data engineering services', 'Data Engineering Services', 'DATA ENGINEERING SERVICES', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, td: { keywords: [ 'training data', 'Training Data', 'training Data', 'TRAINING DATA', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, ias: { keywords: [ 'image annotation services', 'Image annotation services', 'image Annotation services', 'image annotation Services', 'Image Annotation Services', 'IMAGE ANNOTATION SERVICES', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, l: { keywords: [ 'labeling', 'labelling', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, pbp: { keywords: [ 'previous blog posts', 'previous blog post', 'latest', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, mlc: { keywords: [ 'machine learning course', 'machine learning class', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, }; 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