How to Use AI to Create Images of Anything You Can Imagine

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How to Use AI to Create Images of Anything You Can Imagine

Only a few months ago, if you wanted to make a picture of anything, you had to be able to draw, paint, or use one of the photoshopping apps that everyone keeps mentioning. However, everything changed after 2022, owing to AI—yes, as in “artificial intelligence.”

Instead of attempting to rule the world, aesthetically minded AI technologies may transform any description you give them into a picture.

Join us as we explore the realm of AI-powered text visualization, and learn how you can utilize such tools to turn your ideas into actual images by just entering what you have in mind.

Dall-E: The Artistic Side of OpenAI’s GPT-3

The first widely used AI-powered tools were built using OpenAI’s GPT-3. One of the reasons was the project’s openness to outside access, which prompted some to speculate that GPT-3 represents the future of creative production.

Today, you may utilize the official OpenAI beta tools or third-party solutions that take use of its language skills. You may, for example, ask GPT-3 to compose a post, answer basic questions, or even modify or translate some material.

In 2022, OpenAI reported that GPT-3 was as adept in picture creation. The DALL-E project, a pun on Pixar’s WALL-E and Dali’s name, employs GPT-3 as an image-creation engine rather than a text-editing tool.

DALL-E, like GPT-3 and text, isn’t a creative genius, materializing visuals out of thin air. Instead, it has been “trained” on millions of existing photographs on the internet. Its AI abilities are derived by evaluating such photos, extracting aspects from them, altering, morphing, adjusting, and eventually integrating them into new imagery.

That is, at least, a simplified version of what occurs in the background. Most people are just concerned with what they see in front of them, which is a text box into which they may input anything and see it transformed into a picture within a few minutes.

Google’s Imagen Answer

Google is one of the top three “players” in artificial intelligence research. Nonetheless, their development is not clearly discernible, and their implementations into products are not as accessible as OpenAI’s services.

One of Google AI’s earliest publicly accessible applications was in Google Docs and Gmail, in the form of Smart Compose, which provides more intelligent auto-complete and recommendations. We won’t get into specifics since we’ve already discussed Smart Compose (and how you can use it).

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When such capabilities are enabled, Google’s web applications compare what the user is typing to what millions of others have previously written. It then recommends what they typed after that.

It demonstrates that, contrary to popular belief, we are not all that different. If 99 out of 100 individuals write “later” after “see you,” we’re likely to do the same.

We’ve all used autocomplete, dating back to the “dumbphone” era’s T9 predictive text technology. As a result, Google’s AI tools did not seem to be as clever as OpenAI’s GPT-3. They didn’t feel much better in use than a superior T9 system updated for the twenty-first century. That’s also why Imagen’s disclosure came as a surprise.

Imagen is a text visualization tool that functions similarly to DALL-E on steroids. Based on what is currently available, Imagen can generate “cleaner” and more vivid pictures while also dealing with sophisticated elements such as diffusion and transparency.

Unfortunately, access to Imagen was still limited at the time of writing, so we couldn’t test it.

DALL-E Mini and Friends: Open for Business

You still can’t easily access DALL-E and Imagen. If you want to experiment with AI-powered textual picture production, there are many of options.

Keeping in mind that they are still in their early stages, and the results or user experience they provide may be subpar, it’s still worth checking out some of the following.

Making Memes With Dall-E Mini

DALL-E small became one of the most popular AI text visualizers due to a combination of more-than-adequate results and a user-friendly interface, but more significantly, its widespread availability.

DALL-E mini’s findings are far from ideal, and they might often be more abstract than planned.

Other times it might fail to create what you had in mind but can get pretty close.

After its explosion in popularity, DALL-E mini’s creators moved it into a new home under new branding. Now you can find DALL-E mini’s latest version as Craiyon on its own site.

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Using Craiyon today is as easy as searching online for an existing image. You can visit its site, type a description of your picture in its text field, and hit Enter. After a while, you’ll see the results on your screen.

What’s striking is how good Craiyon and similar tools are at mimicking visual styles. For example, we’ve asked it to conjure images of a puppy on a skateboard:

Then, we used the exact phrase but added a “Pixar style” after it. After a while, Craiyon showed a grid of more “cartoony” images, closer to what we perceive as Pixar’s ray-traced graphics in their beloved movies.

Craiyon gave us even better results when we replaced “Pixar style” with “anime style” in the same prompt.

Anime is more stylized in its appearance than Pixar’s more realistic imagery, which seems to have helped Craiyon produce some almost ready-to-use images.

Fooling Around With Latent Diffusion

The Latent Diffusion model trained on the LAION-400M dataset is another interesting AI text visualizer. However, it’s also more complicated in its use. You must run it online in a virtual machine and play with its various parameters instead of merely typing in a text field. Still, it’s easier than it sounds.

  1. Visit the Google Latent Diffusion colab location, which serves as its present home.
  2. Scroll down and look for the Prompt area under Parameters. Replace the default prompt with the picture you wish to portray.
  3. Use the Runtime menu to choose Run All, or press CTRL + F9.
  4. Whether you want to be able to export the generated photographs straight from the tool, choose yes when asked if you want to connect it to your Google Drive account. The utility requires some time to configure and must download various files throughout the process.

Increasing the values for Steps, Iterations, and Samples in parallel, may lead to more detailed results. However, the tool is extremely demanding in resources on Google’s servers. As a result, it may crash if you increase those values too much, or the process of creating a particular image becomes more complicated than expected.

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Interesting Alternatives

We’ve put DALL-E small and Latent Diffusion through rigorous testing. Our scientific process was divided into two components. First, we had to come up with thoughts that could only be regarded as insane. Then, instruct those AI visualizers to convert them into pictures. They succeeded more frequently than anticipated, getting near to the basic structure we had envisioned.

For this post, we also tested some of the accessible alternatives. We’re still waiting for permission to see others. Some worth looking into include (in no particular order):

Will AI-Generated Art Replace Visual Arts?

Many people believe that visual arts will disappear soon due to the quantity and growing popularity of image-generating AI-powered technologies. What’s the sense of devoting time and effort to learning to draw or using complex tools to depict things when an AI can do it faster (and soon better) than you?

Those technologies, as you may have noted, are all “trained on datasets.” In layman’s terms, this implies that they do what they do because people have previously done the same thing.

That’s why such instruments can’t take the place of human talent, creativity, and innovation. They’re mimics, or intelligent replicators. They couldn’t make anything without the human-produced originals on which they’re taught.

Still, that is the present, and we concede we have no idea what the future contains. Visual artists may rest easy for the time being. However, given the pace at which AI is advancing, many experts feel that it is a question of when, not if, it will eventually replace individuals like yours truly. It’s only a question of time.

But, hey, it’s not all bad news. While Skynet prepares to steal our jobs, we can at least cheer ourselves up by effortlessly generating photos of pups on skateboards!

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