What is DALL-E?
Trained by a neural network and capable of taking input text captions, SALL-E Generate the images corresponding.
In other words, this artistic AI (artificial intelligence) tool turn text into images.
Openai's DALL-E is an important achievement for generating images from textual descriptions.
- It can generate a wide variety of images, from anthropomorphized versions of animals and objects to surreal images and never-before-seen creations.
- The DALL-E algorithms have learned to transpose concepts into visual representations through training on a large data set of texts and images (up to a resolution of 1024×1024).
- The applications of DALL-E are endless, ranging from creating images for social media to designing products to creating new worlds for video games and movies.
1. History of OpenAI
Before creating innovative concepts of Machine learning “text-image” thanks to DALL-E, the company started out as a text generator, more specifically a language processor.
In 2019, OpenAI initially created a model called GPT-2 that could predict the next word in a text. It had 1.5 billion parameters and had been trained on 8 million web pages to produce its data set.
The aim was to predict the following word, as a text generator would:
- “For linguistic tasks such as answering questions, reading comprehension, summarizing, and translating, GPT-3 starts learning these tasks from plain text, without using specific training data,” OpenAI said.
Its successor, the GPT-3 model (then GPT-4 in 2023), would become the preliminary DALL-E model, modified to generate images instead of additional text.
2. Past technology
Generative adversarial networks (GANs) were once the best method for creating images from a description (prompt).
However, GANs have several limitations.
- they require a lot of data to function properly.
- they also tend to produce images that are of low quality and lack detail.
While GAN has existed for some time, many believe that the release of DALL-E marked the end of GAN's reign:
- More effective than GANs,
- Can generate realistic images in much better quality and in a fraction of the time.
3. Dall-e mini
In addition to the full DALL-E AI model, OpenAI has also released a miniature version called DALL-E mini available via the web browser.
Despite its reduced capabilities, DALL-E mini creates high quality generated images.
DALL-E mini by Craiyon.com is more accessible to those who do not have access to large amounts of computing resources.
DALL-E mini is also an open-source version and available for everyone.
How does DALL-E work?
It can generate images via the web browser of images based on words provided by creators and artists, even in the case of the most unique and unusual descriptions.
How does she produce art?
- It uses the algorithm contained in the words and places them in a series of vectors or text-image embeds.
- Then, the AI (artificial intelligence) creates an original image from the generic representation that was presented to it in its data sets, based on the text added by the user who creates the work. It can “take any text and turn it into an image,” said Ilya Sutskever, co-founder and chief scientist of OpenAI.
AI (artificial intelligence) can also appropriately add slight details, like shadows and reflections, to make images look even more realistic.
Features
DALL-E can change several of the attributes of an object.
It creates unique results from the textual description, controlling the size, shape, color, and frequency of objects.
The platform is capable of creating entire scenes and forming relationships between objects.
1. 3D
DALL-E is not limited to two-dimensional images (in 2D) but is capable of generating 3D models of objects from different angles.
2. Semantics of the words “not spoken”
The words that a person uses to describe an object rarely contain all the information needed to generate an accurate image.
- It can take into account words that are not written but remain implicit.
- While 3D renderers would be able to approach it after several attempts, the fact that there is no need to explicitly specify every detail is a powerful demonstration of what artificial intelligence can be capable of.
3. Real vs imaginary
The ability to synthesize objects and scenes that seem identical to the real world opens up a whole new range of possibilities for what can be created.
DALL-E gives a few examples of this situation:
- take qualities associated with random objects and transfer them to animals
- the establishment of links that have never been established before thanks to inspiration unrelated to the subject at hand
For example, the prompt “a snail with the texture of a harp” gives rise to an image that combines the real world and the imagination.
The result is not something that exists in the real world, but it can give interesting results.
4. Geographic and spatial landmarks
He seems to have a good knowledge of geographic details, landmarks, and communities.
Think of a text like:
- A photo of food in China
These prompts allow DALL-E to generate fairly accurate images that are representative of reality.
Difference between DALL-E and DALL-E 2
DALL-E 2 has been available on the OpenAI website since April 2022.
The difference is in the number of parameters, which allows DALL-E 2 to create images that are even better than those of DALL-E.
This is done by generating higher resolution images:
- DALL-E used 12 billion parameters, while
- DALL-E 2 is working on 3.5 billion parameters, with an additional 1.5 billion parameters to improve resolution.
Dall·e 2 creates higher-resolution images, although smaller than its predecessor.
- Dall-e 2 also “learned the relationship between images and the text used to describe them in a process also known as diffusion.”
- In this method, there is generally a dot pattern that gradually changes to an image as it recognizes aspects of that image.
- DALL-E 2 can extend images beyond what's in the original photo, which is called outpainting, creating new compositions from old images.
- Its resolution is 4 times higher than that of DALL-E.
Overall, DALL-E 2 is more versatile and produces images more realistic and more accurate only its precursor.
What is DALL-E 2?
On September 28, 2022, DALL-E 2 was officially open to the public.
The new version comes with several new features and improvements, the most notable of which concerns the training data sets used to train theartificial intelligence.
In terms of pricing, in July 2022, the OpenAI website started charging credits for art generation on the DALLE-2 platform after two months of free use:
- For starters, all users get a free credit bonus.
- After that, they get 15 free credits every month.
- For those who want more, they can buy 15 dollars for 115 credits, which should technically make it possible to generate up to 450+ DALL-E images.
Outpainting
In August 2022, OpenAI introduced in DALL-E 2 a unique new function called outpainting, which allows users to continue creating an image beyond the original boundaries, giving visual elements a new direction, simply through a natural language description.
This new feature is a nice balance with the previous OpenAI editing feature in DALL-E, called inpainting, which allows users to edit a generated image.
The new feature allows creators to create images at scale by adding the extension.
Thanks to this new process, AI developers better understand the different strengths and capabilities of DALL-E.
Enrollment
You can complete theDALL-E 2 registration by creating an account on the Open AI site with an email address:
- You will be asked to enter your email address and a security code and create an eight-digit password.
- You can also create an account using SSO on sites like Google or Microsoft.
Click “Continue” to accept the terms and conditions, and you are ready to use DALL-E 2.
Create a work of art with DALL-E 2
Here's how to sign up and how to make the AI (artificial intelligence) art generator work for you.
DALL-E 2 is now available in beta for everyone.
- This AI (artificial intelligence) art generator allows users to generate images by simply typing in a description of what they want.
- However, the results can be random, so it is advisable to learn how to refine the Prompts to improve results.
- If you prefer to create your own original work in a traditional way, check out our guide to best graphic design software.
Future of DALL-E
- The potential applications of DALL-E 2 are vast, especially for creating illustrations, product designs, works of art, photorealistic images for movies and video games.
- DALL-E represents a significant advance in artificial intelligence
- DALL-E will help researchers study the impact of technological change on society, as well as the ethical challenges associated with new technologies.
Pricing
Is DALL-E 2 free?
Until July, it was (for those who had access to it, including free credits), but OpenAI now uses a credit-based model.
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New DALL-E 2 users receive 50 free credits that they can use to generate, modify, or create a variation of an image (new image generations give four 1024 x 1024 pixel images for the cost of one credit).
- After that, users get 15 free DALL-E 2 credits every month.
- To get more, you have to buy them at the price of 15 dollars for 115 credits (enough to generate 460 images of 1024 X 1024 pixels).
- OpenAI invited artists who need financial assistance to apply for subsidized access.
Summary.
As a revolutionary text-to-image generator, OpenAI's DALL-E has paved the way for a better understanding of our world.
All you need to get started is an email address. Whether creating original images or working with digital art to create innovative experiences, DALL-E produces unique and consistent images on a scale never seen before.
Brands and businesses are now exploiting image generation models to create realistic images of their products, which will only increase in the future.
With its ability to consider implicit ideas and create exceptional images, DALL-E is paving the way for a new era of visual innovation.
FURTHER READING : AI (artificial intelligence) technology is now present in many aspects of a business.
Whether it is the use of a AI system write content, create books and develop marketing materials, or the use ofAI marketing tools (artificial intelligence) to analyze data and segment audiences, the benefits of AI (artificial intelligence) for businesses are numerous.
AI video generators (artificial intelligence) are also being used to create realistic, high-quality video material, and this trend is set to continue.
READ MORE: How do you turn a photo into a drawing?
FAQs
Is DALL-E 2 available?
For the first five months following the release of the tool in April, access to DALL-E 2 was limited, and the waiting list was long. But in September 2022, access was opened so that anyone could complete theDALL-E 2 registration
Today, using DALL-E 2 is no longer free.
Instead, users will receive a limited number of monthly free credits, with the option to pay to top them up (see below).
Can you remove the watermark from DALL-E 2?
When you upload an image created in DALL-E 2, it includes the watermark of the color band at the bottom right of the image.
- However, According to the conditions of DALL-E 2, this watermark can be removed on the generated images, which in many cases may be necessary for commercial work.
- It should be fairly easy to remove the watermark in any application that has an object removal, cloning, or content-based filling tool, for example Photoshop. There is also a way to directly download the image without a watermark.
- On the desktop, you can right-click on the image, choose “Inspect,” and then search for the URL windows.net.
- Copy the image link and you should find that the image does not contain a watermark.
On a mobile phone, you can touch and hold the image on the generation page and click “Save Image.”
What does DALL-E mean?
How did the creators of this company come up with the name DALL-E?
The name is a combination of artist Salvador Dali and Pixar's WALL-E robot.
Combining both art and digital animation with the help of artificial intelligence, this company's DALL-E system is leaving its mark on the world of AI.
What is CLIP for DALL-E?
DALL-E was revealed around the same time as its other neural network, the Contrastive Language Image Pretraining (CLIP).
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This model is distinct from DALL-E and has been trained with 400 million image pairss whose text had previously been deleted.
His connection with DALL-E consisted in understanding and ranking the DALL-E results by guessing which caption, selected from thousands, would be the most acceptable for the image.
CLIP created text descriptions for the ai images generated by the DALL-E software.
The DALL-E method is called the reverse clip, or a Clip, because it does the opposite of what CLIP does, generating images from text instead of making text from images.
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