ChatGPT Explains Photoshop Neural Filters

See Adobe Photoshop: Tips and Tricks for similar articles.ChatGPT Explains Photoshop Neural Filters

While working on a Photoshop lesson on reconstructing and retouching photographs and thinking about how to cover Photoshop’s Neural Filters, which use artificial intelligence to touch up and modify photos, I thought I’d see how a different artificial intelligence tool could help me out. So, I had the following conversation with ChatGPT, and used some of the content in its replies in the course:



Write me an introduction to Photoshop’s neural filters.


Photoshop’s Neural Filters are a new set of AI-powered image editing tools that use advanced deep learning algorithms to apply various effects and transformations to photos. These filters allow users to easily enhance images, add creative styles, and perform complex image manipulation tasks with just a few clicks, leveraging the power of artificial intelligence. Some of the popular Neural Filters include Style Transfer, Depth of Field, Portrait Relighting, and Skin Smoothing, to name a few. These filters provide a unique and innovative way of editing photos and offer limitless creative possibilities for photographers and designers.


Now, explain the process of applying a neural filter.


The process of applying a Neural Filter in Photoshop is relatively simple and straightforward. Here’s a general outline of the steps involved:

  1. Open an image in Photoshop: Start by opening the image that you want to edit in Photoshop.
  2. Select the Neural Filter: Go to the Filter menu and select “Neural Filters.” A new panel will open with a list of available Neural Filters.
  3. Choose the desired filter: From the list of filters, select the one you want to apply. Each filter will have a preview thumbnail that you can use to see how it will look on your image.
  4. Adjust the filter settings: Some filters will have additional settings and options that you can tweak to fine-tune the effect. You can adjust the intensity of the effect, add masking, etc.
  5. Apply the filter: Once you’re satisfied with the settings, click on the “Apply” button to apply the filter to the image.
  6. Save the image: Finally, save the image with the applied Neural Filter effect.


Now explain the difference between neural filters and the other filters available in Photoshop.


Neural Filters in Photoshop are different from traditional filters in several key ways:

  1. AI-powered: Neural Filters use advanced deep learning algorithms to apply effects and transformations to images, while traditional filters are based on simple mathematical operations and algorithms.
  2. More sophisticated results: Neural Filters produce more sophisticated and nuanced results compared to traditional filters, as they are trained on large datasets and can learn to recognize and replicate complex patterns and styles.
  3. Real-time results: Neural Filters provide real-time results, so you can see the effect as you make adjustments to the settings.
  4. More user-friendly: Neural Filters are designed to be more user-friendly than traditional filters, with a simple and intuitive interface that allows you to easily apply and adjust effects without needing to know any technical details.
  5. More creative options: Neural Filters offer a wider range of creative options compared to traditional filters, as they can be trained on a diverse set of styles and effects, including styles from famous artists, movies, and more.

Overall, Neural Filters in Photoshop provide a new and innovative way of editing photos, offering limitless creative possibilities and a more sophisticated and user-friendly image editing experience.


I think it did a really good job of explaining at a high-level what Neural Filters are, how they’re used, and how they differ from traditional Photoshop filters! It will be interesting to see what it can do in the future. For example, will it be able to add screenshots or even animated images or videos showing how to apply filters?

Written by Nat Dunn. Follow Nat on Twitter.

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