Explore new possibilities and Compress Addendums with AI

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Aug 6th, 2022
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01. Upload a document from your computer or cloud storage service.
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02. Modify your document or let the ai PDF editor summarize, rewrite, or proofread your PDF.
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03. Sign your document online in a few clicks.
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04. Send, export, fax, download, or print out your document.

Compress Addendums using AI without having batting an eyesight

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Document managing is an integral part of your daily tasks and workflows. However, this essential task might sometimes feel overwhelming without the right software. Luckily, DocHub can change your experience for the better. Introducing ChatGPT-driven functions, we seek to boost your routine tasks so you can put your time to better use. Compress Addendums, eSign, share, and safely store your documents in a single place without changing in between solutions.

The best way to Compress Addendums with AI easily

  1. Get a free DocHub profile to start working.
  2. Add your document and wait for it to open within the editor.
  3. Start a ChatGPT Assistant and then click on the Compress feature.
  4. Compress Addendums and view the results.
  5. Make other modifications utilizing the Manage Fields sidebar.
  6. Assign people to fillable fields to boost the completion process.
  7. Download or share your document using an email attachment or invite link.

Your workflows don’t need to be complex or need high priced software. DocHub check all the boxes for a modern, easy-to-use, and flexible software for your organization or personal use. Compress Addendums using AI, streamline workflows, collect eSignatures, and reclaim your office hours. Begin a free trial version right now to try out the strength of AI!

A single solution for all your PDF needs

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Quick data collection
Create and fill out PDF forms online on any device. Turn your form or document into a reusable template and share it via URL or email so anyone can fill out their own copy.
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AI PDF functionality
Improve productivity with DocHub's ai tools. Get quick summaries with the ai PDF summarizer, enhance document readability with an ai that reads PDF, and use the ai PDF editor to ensure the quality of your document’s content.

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Got questions?

Below are some common questions from our customers that may provide you with the answer you're looking for. If you can't find an answer to your question, please don't hesitate to reach out to us.
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Traditional video compression removes bits of visual information to reduce the overall file size of a video. AI video compression examines the contents of a video to recreate it on a smaller scale. In other words, it creates a hyper-realistic duplicate of the original video.
This is because AI video compression is machine learning (ML)-based video compression (sometimes known as neural compression). ML algorithms or models learn to perform tasks and make evaluations based on relevant training data fed by a human or in this case, a video feed.
Pruning is the most popular technique for model compression which works by removing redundant and inconsequential parameters. These parameters in a neural network can be connectors, neurons, channels, or even layers. It is popular because it simultaneously decreases models size and improves latency.
Model compression reduces the size of a neural network (NN) without compromising accuracy. This size reduction is important because bigger NNs are difficult to deploy on resource-constrained devices. In this article, we will explore the benefits and drawbacks of 4 popular model compression techniques.
Learned data compression Overview. Setup. Define the trainer model. Compute rate and distortion. Train the model. Compress some MNIST images. The ratedistortion trade-off. Use the decoder as a generative model.
Yes. If you know anything about compression, you know that compression is very data-dependent. AI tools are very good in classifying data, so they can be used as a pre-processing step to classify the data and then apply the most appropriate compression scheme.
Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Yes, artificial intelligence can definitely help to improve data compression.
AI codecs, having been developed over the course of decades, use machine-learning algorithms to analyze and understand the visual content of a video, identify redundancies and nonfunctional data, and compress the video in a more efficient way.

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