I started using NotebookLM with Google Docs and it's been a game changer

Google Docs has been my digital workspace for ages, my go-to for everything from meeting notes to comprehensive reports. Still, there was a missing piece: a way to overcome the flood of information in my Google Docs library. That's where NotebookLM stepped in, and the connection it created with Google Docs has been transformative. I have used this combination for a while, and the impact on my productivity and the quality of my work has been massive. I'm excited to share how this powerful combination streamlined my process, making everything from pitching ideas to getting insightful information from my documents intuitive and efficient. Related Forget Google Keep, OneNote and Evernote, 5 reasons NotebookLM is the future of note-taking It's time to ditch your old note apps Posts 14 Using Google Docs for my workflow It's quite limiting at times My existing Google Docs workflow for any significant project or research often feels limiting. The core issue appears from having information spread across several Google Docs documents. Whether it's research notes, interview transcripts, outlines, drafts, or materials from complex subjects, each piece has its own document. Sometimes, I had to open dozens of tabs in my browser to get insightful information from them. Even then, the process was time-consuming and felt restrictive. For example, if I needed to cross-reference a specific point from an article I read last week, I had to open a tab. Similarly, if I had to pull a quote from an interview, I had to navigate to that transcript. It was a constant back-and-forth between clicking tabs, scrolling, searching, and trying to hold information in my short-term memory. This process is time-consuming and mentally taxing. Even Gemini in Google Docs (which is a paid add-on at $20 per month) operates on a single-document basis. I can't ask Gemini to get information from any document in Google Docs. Here is where NotebookLM comes into play. It's free to use, works with a bunch of Google Docs documents (and more), and has a few AI tricks to amaze you. Combining Google Docs with NotebookLM It's been a game-changer Integrating Google Docs with NotebookLM has been a productive boost for my workflow, especially on complex projects like the new website I built for a client. Before NotebookLM, managing multiple Google Docs was a headache. I had separate documents for project overview, meeting details, client feedback, the website content, and more. Then I discovered NotebookLM. I created a new notebook for the QWERTYBYTE website and uploaded everything as source. Even better, I linked the Google Sheet containing the project finances. All my project information was in one place, accessible through a single interface. The real magic happened when I asked NotebookLM questions. I can now ask complex questions like these: What are the client's key concerns about the website design? Summarize the feedback from the last three client meetings. What's the estimated project cost and timeline? Which tasks are due for the upcoming week? NotebookLM can analyze all the sources and give relevant answers in no time. It also displays related questions at the bottom. The ability to ask questions and get detailed answers across all my project documents transformed my workflow from a time-consuming process to an efficient one. Related I started using Google Docs to manage my projects and here's how it went My unconventional project management system Posts 3 Packed with AI tricks Building on that client website project, the capabilities of NotebookLM went beyond just answering questions. It changed how I interacted with the information. When all those Google Docs (and even that Google Sheet with finances) are in NotebookLM, the real power becomes apparent. For instance, I'm a visual thinker, and the ability to generate a mind map from my project documents is intuitive. This isn't a static diagram. It's an interactive overview that helps me quickly grasp the project's scope. Then there is the audio overview feature. When I need a quick refresh without staring at a screen, I can generate an audio overview with the key points from my project documents and generate an audio summary. It's like having the entire project briefing played back to me. The possibilities are endless. Timeline is another handy trick. With a single click, I can generate a timeline of the project that includes deadlines, delivery milestones, and a clear visual of the project's progress. My docs are now smarter If you wrestle with information overload and a messy workflow in Google Docs, it's time to give NotebookLM a try. Aside from Google Docs, NotebookLM supports other file types, so don't hold yourself back. Add all the materials from different sources to get the best out of every material. NotebookLM is still new on the market, and it may feel overwhelming. If you are among them and have yet to explore Google's AI note-taking tool, check out these tips and tricks to get started.

Android Police

Sun, 22 Jun, 12:00 PM UTC

7 Key Benefits Of Intelligent Document Processing

Data is one of the most crucial elements in today's fast-paced, competitive world. It contributes to organizational growth, tracks business performance, makes informed decisions, and finds solutions to problems. For business, this data is essential for growth, transaction tracking, orders, and more. They need to extract these data from different documents, including delivery notes, invoices, receipts, bills, packing lists, etc. Intelligent document processing (IDP) technology automates manual data extraction techniques from paper-based documents, images or PDFs. IDP extracts the data from different papers and organizes them for seamless access and process, benefitting the business. Benefits of Intelligent Document Processing Intelligent document processing combines optical character recognition (OCR) with artificial intelligence (AI) and machine learning (ML) to automate document processing. It processes complex documents in variable formats and extracts valuable information by understanding their concept and format, saving time, operational cost, and more. Use Cases of Intelligent Document Processing Businesses operating in different fields, relying on data daily, must process several documents and can use intelligent document processing. IDP processes various document types, including invoices, receipts, air waybills, packing lists, OMR sheets, ID cards, passports, purchase orders, transport bills and other documents. Individuals can also train the model to process any new kind of document. The AI-based software processes learn the importance of specific data and ensure accuracy. KlearStack is a pioneer in intelligent document processing software that processes documents with 99.9% accuracy and increases operational efficiency by 500%. The software is compatible with all document types and pretrained for various document models, including: You can create one or more custom models with this intelligent document processing software for any specific document type and leverage its benefits for your business. Some of the business that uses intelligent document processing are: Intelligent document processing for documents works in different steps. Step 1: Pre-processing This is the first step of document processing, in which the software evaluates the document's quality, and if it finds it to be of poor quality, IDP enhances it. However, if the document is not up to the mark, the software eliminates it before processing. Step 2: Document Classification In this step, Intelligent document processing software identifies the document type and categorises it accordingly. The document classification ensures you find similar kinds of documents in the same place. Step 3: Data Extraction It's the crucial step in which the intelligent software extracts valuable information from your documents using optical character recognition, machine learning, artificial intelligence, and natural language processing and organises them in an understandable order. Step 4: Data Validation Once the data is processed, it's time to validate the information. Here, you can check whether the IDP has extracted the right information. In KlearStack, an intelligent document processing solution, the screen is split into two parts where you can compare the extracted information with the original document. If there is any wrong information, you can edit it and simultaneously train the model for future documents. Step 5: Approve the Extraction Once you have checked the data, you can approve it. You can track all the approved documents in a single place. With RestfulAPIs, you can also integrate intelligent document processing software with other existing applications for seamless data management. Conclusion Intelligent document processing is software equipped with machine learning, artificial intelligence, optical character recognition, and natural language processing to ease the document processing task. It benefits the business by saving time and money and boosting operational efficiency. Moreover, the software offers scalability, data security, and integration to support the growth of the business and organisation. Adapting, AI-driven IDP helps the company with document management, makes informed decisions, and increases the productivity of human resources. For an organisation that deals with documents daily, the innovation of Intelligent document software is a boon. Want to know how intelligent document processing can work for your business growth? Schedule a demo!

Outlook India

Sat, 20 Jul, 8:00 AM UTC

Save Time With This AI-Powered PDF Tool That Extracts Key Ideas for You

The following content is brought to you by PCMag partners. If you buy a product featured here, we may earn an affiliate commission or other compensation. Deal pricing and availability are subject to change after the time of publication. While PDFs are the universal document type for students and professionals alike, the hard truth is that they're not very easy to work with -- unless you have the right tools. Rather than pay a monthly fee to edit or convert your PDFs with Adobe Acrobat, you could own this AI-powered tool instead. With Afirstsoft, you're not just getting a PDF management tool, you also get an AI power for quick PDF summaries and OCR for easy scanning. Now, lifetime access to this tool is available for less than $50. Use this tool on your Windows, Mac, iOS, and Android devices. If you see a spelling error or want to rephrase a sentence, Afirstsoft PDF lets you jump in and edit and format text. You'll also be able to customize your documents so your PDFs are fully interactive with text and images, as well as annotate them for extra clarity. What's most helpful about this platform is the Afirstsoft AI, which allows you to chat with your PDFs to get answers to your questions and summarizes your documents so you get the key ideas immediately. Working with PDFs is simple when you grab a lifetime subscription to this AI-powered PDF management tool, now $49.99 (reg. $179).

PC Magazine

Tue, 17 Sept, 8:01 PM UTC

5 ways Adobe Acrobat's AI Assistant gives you a productivity edge

From document summaries to content creation, the PDF editor's generative AI helps you work smarter. Adobe Acrobat's AI Assistant uses generative AI to make working with PDFs faster, easier, and more intuitive. With this tool, you can engage in conversational interactions with your documents to more easily find, understand, and share key information. Fully integrated into Acrobat's interface, AI Assistant is right at your fingertips, offering smart suggestions based on what you're doing. Whether you're searching for specific details, summarizing lengthy reports, or drafting content, the AI simplifies complex tasks and streamlines your workflow. Here's how it can supercharge your productivity in some common tasks. Further reading: The best PDF editors We've all been handed a long PDF packed with information, but no time to read through it all. Maybe it's a report that lands in your inbox minutes before a presentation, or you're staring at a mountain of research that needs reviewing before you can write your article. That's where Adobe Acrobat's AI Assistant comes in. It scans through the document in seconds and generates a summary of the key points that you can review quickly. Just click the generative summary button in the toolbar. Acrobat instantly creates an outline of the document, letting you click through for quick summaries of each section. Want to dig deeper? Just hit the "Ask AI Assistant" button. It'll suggest questions to explore the document further and encourages you to ask your own. You can even ask the AI to draft an email summarizing the document, ready to copy and paste into your email client. Job hunting is already hard enough without having to tweak your resume for every application. By scanning the job description and comparing it with your resume, AI Assistant can suggest areas for improvement, helping you highlight the most relevant skills and experience. This saves you time while boosting your chances of catching the recruiter's eye. First, open the job description in Acrobat, then tap the AI Assistant button. In the chat box, ask something like "What are the top three skills required for this role?" AI assistant will provide summaries of those skills. Next, open you resume in Acrobat and follow the same steps to ask the AI to help you add bullet points highlighting those skills. It's like having a career coach that quickly tailors your resume without needing hours of manual editing. If your last meeting left you with pages of notes and no time (or will) to sift through them, AI Assistant can quickly turn them into a concise summary, hitting the highlights without you having to read every word. As in the example above, AI Assistant will scan the uploaded document, identify key points and action items, suggest questions, and prompt you to ask your own. The last is a great opportunity to have AI Assistant extract action items or detail next steps on a project that you can share with your team. Staring at a thick instruction manual and trying to figure out how to set up a new device is tedious and often confusing. Acrobat's AI Assistant can aid the process by breaking down complex instructions into clear, step-by-step directions. This way, you can get your new gadgets up and running without pulling out your hair. Open the PDF manual in Adobe Acrobat, and AI Assistant will provide an overview and prompts to help you navigate the document. You can also cut to the information you need by asking direct questions in the chat box. Once those dense, technical instructions are broken down into easy-to-follow steps, you can follow along and set up your device with ease. Need to write a blog post or put together a newsletter but don't know where to start? AI Assistant can help you craft content quickly and efficiently. Upload a report, PowerPoint presentation, or another source document in Acrobat. Once AI Assistant has analyzed and summarized it, you can ask AI Assistant to draft an email, blog post, or other content based on it. With your draft in hand, you can revise the format, tone, word count, and other elements by prompting the assistant, then polish it into a final draft with your own editing. It's an easy way to create professional-looking content without hours of toiling. Adobe Acrobat's AI Assistant is like having, well, an actual assistant that handles time-consuming, repetitive tasks; keep things organized; and helps ensure that everything runs smoothly. Whether you're using it for personal or professional documents, it helps you accomplish more with less effort, freeing you for the work that matters most.

PCWorld

Tue, 8 Oct, 12:25 PM UTC

DocAI: PDFs/Scanned Docs to Structured Data - DZone

The "why" of this AI solution is very important and prevalent across multiple fields. Imagine you have multiple scanned PDF documents: OR Dealing with such scanned/mixed/unstructured documents can be tricky, and extracting crucial information from them could be manual, hence error-prone and cumbersome. The solution below leverages the power of OCR (Optical character recognition) and LLM (Large Language Models) in order to obtain text from such documents and query them to obtain structured trusted information. We can further expand the use cases for the above project to incorporate images, integrate with documentation stores like Confluence/Drive, etc. to pull information regarding a specific topic from multiple sources, add a stronger avenue to do comparative analysis between two documents, etc.

DZone

Wed, 9 Oct, 4:30 PM UTC

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