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A complete guide to Adobe Illustrator's AI tools

T he genie's out of the bottle – it seems that AI is here to stay. With Illustrator's new generative features (see our Illustrator 24 review ), it's a good time to try out AI tech in your workflow, particularly for idea generation or mockups. Jump from imagination to screen to print with our tutorials that explain each tool below.

Text-to-Vector Graphic enables you to generate vector graphics from text prompt, Recolor uses AI to shift your colour scheme in an instant, Mockup puts your design in situ on a 3D product and Retype allows you to select a font and find the closest matches for your own designs. 

Here, I have created a step-by-step tutorial for each of these tools, and you can use the side-nav to skip ahead to the one you want to read. Afterwards, check out the raft of other Illustrator tutorials we've collated.

Text to Vector Graphic

Even a complete beginner can conjure up a fantastical illustration in minutes, generating intricate vector graphics from even the most basic of text prompts. As a professional, you might want to use these to generate ideas, or to provide a rough mockup of your idea to clients before working on the real thing. It’s fun to experiment with and fully editable once created. The only limit is your own imagination.

01. Open the window

Text to Vector Graphic is still in beta and not immediately available in the Illustrator interface, but can be accessed via the Properties panel, Window > Text to Vector Graphic. Alternatively, activate the Contextual Bar in Window > Contextual Bar. This will remain switched on indefinitely and appears beneath any object or frame selected. Initiate the process by drawing a frame. Since you’ll end up with a scalable vector graphic, size isn’t too important, but it's worth keeping the aspect ratio in mind, for example drawing a square for Instagram post or 16:9 for video.

02. Select the type of object

If you’re using the Contextual bar, press the Generate (beta) button to open the options (this isn’t needed in the Properties panel). Select the item you wish to create – Scene, Subject, Icon or Pattern. For an illustration, it can be better to start with Scene, so you have an idea of the space and perspective available.

03. Type in text prompts

Add as many text prompts as you like – the more information provided, the better the graphic (though you don't want to add too many and confuse it). Consider the setting, style, time of day and detail. An example prompt would be “Art Deco colourful mountain landscape at dusk with a treeline, road and snow.” If you wish to adopt the style of a pre-existing artwork, then you can drop it onto the Canvas and reference it with the Style Picker tool. The Properties panel also gives you some extra sample prompts and a slider to change the level of detail (set at 3/5 as default).

04. Review the results

Any time you press the Generate button, you will be presented with three new, unique results. Cycle through these using the arrows in the Contextual bar or by previewing the thumbnails in the Properties panel. It’s still common enough to encounter erroneous results that clearly lack the human touch, so don’t forget to rate your results, the tool will only improve with constant feedback.

If none of the results meet your requirements, simply press the generate button again to get three new graphics or make edits to your current text prompts to refine the generation parameters. Every time you press Generate, you lose some credits from your Adobe account. Don’t worry about running out, you'll still be able to use AI tools, but they will work at a slower rate.

05. Build your scene

Add to your scene by including objects or characters. Any content created will automatically conform to the style of the active artboard, though you can switch this option off in the properties panel. Finding enough elements that suit the perspective of your scene can be a process of trial and error, so be patient and don’t be afraid of adapting your vision.

06. Clean up your graphic

If you’re only using this tool as a rough storyboard then you might be done at this point. However some of the vectors can still be rough, so this is the time to go in and clean up the details. Often an element may come with a false shadow that needs deleting or imprecise shapes that need smoothing or replacing.

Generative Recolour

After mastering the Text to Vector process, you might find that your creation requires an entire shift in tone. Avoid complicated colour theory and the laborious process of editing each colour by giving the software a few simple cues and letting it do the rest.

01. Open the Recolor window

Select your entire scene or graphic. When the Contextual bar appears, click the Recolor button and select the Generative Recolor tab in the Recolor panel. You can find the same panel in Edit > Edit Colors.

02. Sample prompts

A grid of Sample Prompts offer guidance for anyone feeling particularly uninspired. These give you a brief overview of potential contrasting tones and moods and might spark some ideas.

03. Type text prompts

If you're confident of the theme you're aiming for, type in some basic prompts into the text bar and press Generate. As with the Text to Vector effect, you're presented with three results, which you can toggle through and select any successful blends. There are more Advanced Options for people wanting to customise their colour scheme even more.

Unlike the other tools here, it works offline and doesn’t utilise Firefly, but it is itself a beautifully impressive use of technology (and currently the only one here I use in a professional capacity). It uses AI to place a 2D image in situ on your choice of 3D settings, like a mug, so you can see how your design will work in reality.

In the past, I have relied on 3D renders in Blender to mock up product packaging, however Illustrator makes it possible to achieve similar results in a fraction of the time. 

01. Source image

Source an image. You can download directly into Illustrator from Adobe stock, take from an online image library or use your own image. Drag these onto the Canvas.

02. Generate Mockup

Select both your graphic and the image. Go to Object > Mockup > Make. It will analyse the image and map the graphic onto the image, taking the contours and curves into account.

03. Position graphic

Move your graphic around the image, until it fits your desired position. For a more realistic look, you can change the blending mode of the graphic to Multiply, so it adopts more of the colour of the image underneath.

Retype allows you to identify an outlined font in a static graphic and convert it into editable text. It searches Adobe Fonts as well as the font set on your own computer. While it doesn't always find the perfect match, it offers many similar fonts that might work just as well.

01. Select outlined text and Retype

Open a flat graphic in Illustrator. Select it and go to Type > Retype (Beta). This will analyse the text in the graphic and offer you a list of closest matching fonts.

02. Edit text

If you're happy that a font in the list is identical or a close enough match, click on the font to download it or double click on the text to edit it. Once it's converted to live text, exit Retype to edit the text.

For more Adobe tips and tricks, see our list of Illustrator plugins and Adobe software list . Don't have Creative Cloud? Sign up below:

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Kernel Trick in Support Vector Classification

Support Vector Machines (SVMs) have proven to be a powerful and versatile tool for classification tasks. A key component that significantly enhances the capabilities of SVMs, particularly in dealing with non-linear data, is the Kernel Trick. This article delves into the intricacies of the Kernel Trick, its motivation, implementation, and practical applications.

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Linear vs Non-Linear Problems

Concept of feature mapping, what is the kernel trick, how does the kernel trick work.

For linearly separable data, finding this hyperplane is straightforward. However, many real-world problems are non-linear, meaning that no linear separation can perfectly divide the classes. This is where the kernel trick comes into play.

To deal with non-linear data, one approach could be to map the input data into a higher-dimensional space where it is linearly separable. This mapping involves transforming the data into a new space (feature space) where the separation between the data points is clearer.

For example, consider a set of data points that are not linearly separable in two dimensions. By mapping these points into a three-dimensional space, we might find that they can be separated by a plane in this higher-dimensional space.

The kernel trick is a method used in SVMs to enable them to classify non-linear data using a linear classifier. By applying a kernel function, SVMs can implicitly map input data into a higher-dimensional space where a linear separator (hyperplane) can be used to divide the classes. This mapping is computationally efficient because it avoids the direct calculation of the coordinates in this higher space.

Types of Kernel Functions

Several kernel functions can be used, each suited to different types of data distributions:

• Linear Kernel : No mapping is needed as the data is already assumed to be linearly separable.
• Polynomial Kernel : Maps inputs into a polynomial feature space, enhancing the classifier’s ability to capture interactions between features.
• Radial Basis Function (RBF) Kernel : Also known as the Gaussian kernel, it is useful for capturing complex regions by considering the distance between points in the input space.
• Sigmoid Kernel : Mimics the behavior of neural networks by using a sigmoid function as the kernel.

The kernel trick relies on the inner products of vectors. For SVMs, the decision function is based on the dot products of vectors within the input space. Kernel functions replace these dot products with a non-linear function that computes a dot product in a higher-dimensional space. Importantly, the computation of this dot product via the kernel function does not require explicit knowledge of the coordinates in the higher space, thus saving computational resources and time.

The kernel trick is typically expressed as:

• x and y are two vectors in the original input space

The Kernel Trick significantly enhances the versatility and power of Support Vector Machines, making them a robust choice for a wide range of classification tasks. By enabling the handling of non-linear data, it opens up new possibilities for SVM applications across various domains. As computational techniques and resources advance, the use of kernelized SVMs is likely to become even more prevalent and impactful in solving complex real-world problems.

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