Dall-E Review: Learn More About the Popular AI Image Generation Tool

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Dall-E is an artificial intelligence (AI) program that generates images based upon text prompts. This means that all that you need to produce high quality images through AI is to provide Dall-E with clear instructions in natural language.

At the time of writing, the AI-based tool operates in the form of Dall-E 2, which is the latest version of the program. Dall-E 2 is commercially available through its developer OpenAI, which offers the program through its web interface as well as its application programming interface (API).

In order to learn what is Dall-E and how it works, hereโ€™s a quick guide to this state of the art image generation program.

Key Points

  • Dall-E is an AI-based image generation tool that produces images through text instructions.
  • Dall-E uses deep learning to assimilate text prompts as well as visual cues, and turns related visual material into coherent images.
  • Dall-E also offers an image editor to enhance existing images through AI-based editing capabilities.
  • Dall-E is available both as a graphical user interface (GUI) and an API.
  • You retain complete ownership rights to any images that you generate through Dall-E.

How Do You Generate AI Images Through Text?

dalle text image

Dall-E is an image generation tool that works via AI to assimilate text instructions and turn them into original images. In order to achieve this feat, Dall-E uses deep learning to understand an extensive set of images and references.

When it is given a text prompt, Dall-E uses its training from those datasets in order to produce images that match the provided instructions. This makes it possible for anyone to use AI for image generation, without having to use extensive coding or technical instructions.

This functionality is one of the many reasons why Dall-E has become so popular since its debut in 2020. In its latest iteration, Dall-E 2, the program also offers additional capabilities. These include the option to edit existing images by adding new visual elements or the ability to expand the canvas by creating related visuals for an original image.

In order to use Dall-E 2, you can head to OpenAIโ€™s website and use the tool through the web-based GUI. Even if you have never used an AI program before, the simple interface makes it easy for you to enter your text prompt and get your desired images in return.

The editing interface that was unveiled in late 2022 works with the same approach to simplicity. With an easy-to-use eraser tool, you can remove the parts of your image that you want to be edited or enhanced with Dall-E. From there, you can add text prompts to add new elements to your image.

You can also use the โ€œGeneration Frameโ€ tool to extend the canvas and size of an existing image. You can add this generation frame towards the top, bottom, or either side. You may also adjust the size of this frame. Once you have settled the generation frame and given a prompt to Dall-E, you can see your image extend to your desired size while being in line with the rest of its visuals, theme, and art style.

dalle image redesign

This quick introduction allows you to understand what is Dall-E and how to operate it. But if you have further questions about how exactly the tool works its magic, you can move forward with understanding the mechanics behind it.

Dall-E Uses Various AI-Based Techniques to Enhance Its Visual Prowess

While Dall-E is incredibly adept at identifying images and replicating their style, the proficiency isnโ€™t born out of nowhere. Instead, the Dall-E AI has been trained by using a neural network that combines visual references with natural language supervision.

This neural network employs deep learning, which is a subset of AI that processes large sets of data to learn about the subject matter at hand. With it, deep learning through neural networks can also categorize different patterns and identify the relation between varying segments of data.

The neural network that is used for Dall-E training is called CLIP (Contrastive Language-Image Pre-training). CLIP uses a zero-shot learning (ZSL) setup, which allows it to assess visual samples and text references even if it has not encountered them before. This is possible through the extensive data sets that CLIP has been trained on in order to match one set of information with the other.

In order to learn these visual and text references, Dall-E has been trained on no less than 12 billion parameters. These parameters label different images with a text reference and allow Dall-E to understand what is expected out of it when a user asks for a specific image to be generated. In addition to enabling image generation for straightforward concepts, this capability also shines through in abstract concepts such as drawing anthropomorphic characters out of inanimate objects.

This is where the AI model of Dall-E closely matches another product by its developer OpenAI. This match comes in the form of Generative Pre-trained Transformer 3 (GPT-3). While GPT-3 generates text by predicting what the next word should be in the text that it is generating, Dall-E produces images by determining how it should create a complete image according to the elements that it generates in a series.

Once you understand what is Dall-E, you can see how this approach works wonders for the generation of high quality images from scratch. With it, it also makes it clear how the program creates extended images and edits existing images.

By using its impressive selection of parameters, purposefully designed neural network, and intuitive GUI, Dall-E makes it easy for everyone to benefit from the rapidly evolving generative AI technology for image production.

Dall-E Review: How Much Does Dall-E Cost?

Dall-E is available through its developer OpenAI, which offers credits in exchange for a set price. Each credit equals a single image generation request.

This means that you will be using a single credit for producing an image from a text prompt, editing an existing image to make modifications, or extending the canvas for an existing image. Every image generation request also provides you with four variations. But if you request for more variations, it costs one credit per request.

At the time of writing, Dall-E is available at the price of 115 credits for $15. The credits that you purchase expire within 12 months. You can use these credits over the web interface or through the Dall-E API.

Overall, Dall-Eโ€™s pricing plan is more expensive than its closest competitors, Midjourney and Stable Diffusion. At the time of writing, Midjourneyโ€™s pricing starts at $10 for 200 image generation requests. It also offers a $30 plan for unlimited user generation requests. Whereas, Stable Diffusion charges $100 for 100 image credits.

But given that Dall-Eโ€™s AI is more extensively trained and offers image extension tools that Midjourney and Stable Diffusion do not have, it does have sufficient reason to price its product at a higher tier. Besides, Midjourney requires you to access the program through Discord. Whereas, Dall-E is available through its own web GUI as well as API.

After learning what is Dall-E and what kind of fees it brings to the table, it becomes easier for you to determine whether or not you should pay for its services. While you do so, you can sign-up for the solution anyway and get 50 free credits right away. Afterwards, you can get 15 free credits each month. However, these free credits expire within a month as opposed to the paid creditsโ€™ year-long expiration date.

Dall-E Pros and Cons

Dall-E 2, which was unveiled in April 2022, has more capabilities than its predecessor. By using the images and references from its neural network, the program can generate impressive images that fit your prompt more often than not. Additionally, its intuitive GUI and API features make it easier for you to produce images without having to use convoluted image editing tools.

With that being said, Dall-E is still going through its infancy phase where you cannot expect perfection at every single one of its generated images. While the program does its best to fill in the proverbial or literal blanks through the images that it generates, it still has its limitations due to only being as good as the data it is being trained on.

For instance, if you give Dall-E a prompt that it has no precedent for in its neural network, it will generate the closest image possible to your prompt which may or may not fit your instructions in their natural language. As an example, think about giving the program the instruction to generate โ€œswan lake on the stage.โ€ It could very well refer to the popular ballet or a literal lake with swans placed upon a stage.

When generating photorealistic images, you can also notice an ongoing problem with the depiction of faces, hands, feet, and other anatomical details. Sometimes, the AI generates features that are not quite there in terms of visual accuracy or realism. But this is an issue that exists across the board for other AI tools as well.

Is Dall-E Worth It?

If you enjoy being a part of new tech, playing with fun features, and tolerating slight functional issues in the name of progress, Dall-E could be worth your time and funds. This is especially true if you understand what is Dall-E working with in terms of limitations and do not feel frustrated when you have to face these challenges firsthand.

But that is where you have a favorable option in the form of Dall-Eโ€™s free credits. To make sure that you are satisfied with the program before you pay for it, you can move forward with signing up for the platform and trying it via free credits. If you are happy with Dall-Eโ€™s performance, you can then sign up for the paid credits that it offers through OpenAIโ€™s platform.

Sergio Costa (PhD)

Sergio teaches entrepreneurship and innovation at various levels (BSc, MSc, MBA, PhD) mainly at the University of Bath, Imperial College London, Warwick Business School. He has published research on the Journal of Business Venturing and leading management conferences (AOM, SMS, Babson, BAM).

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