DALLE-2, which stands for "Multimodal Dialogue-based Language Model with Knowledge-enhanced Transformer-2," is a state-of-the-art language model developed by OpenAI. It is designed to generate textual content that is more diverse, coherent and engaging than the previous generation of language models, such as GPT-3. DALLE-2 is a large-scale generative model that uses a transformer architecture, similar to GPT-3. However, it is also multimodal, which means that it can generate not only text but also images and sound. This is made possible by integrating a vision and audio encoder network into the language model. One of the distinctive features of DALLE-2 is its ability to leverage external knowledge to enhance its text and image generation capabilities. It is trained on a vast amount of text and image data, including images from the internet and text from Wikipedia. It also uses a technique called contrastive learning, which allows it to learn the relationship between different modalities. DALLE-2 is able to generate diverse and coherent text and images that are specific to a particular context or prompt given to it by a user. It can also generate text and images that are similar in style and tone to a given input. For example, if a user inputs a sentence describing a unicorn, DALLE-2 can generate an image of a unicorn, as well as additional text describing the mythical creature. In terms of its potential applications, DALLE-2 can be used in a variety of fields, including creative writing, content generation for marketing, and virtual assistant technology. It has the potential to revolutionize the field of natural language processing and bring about a new era of AI-powered content creation.

2. DALL E 2
► Group Members
1. Muhammad Affan CT-21027
2. Pir Salman Shah CT-21036
3. Syed Mudassir Hussain CT-21022
4. Muhammad Mustafa Sheikh CT-21049
5. Umar Jawed Khan CT-21033

4. What is DALL E 2 ?

5. Dall E 1 & Dall E 2
DALL E 1
► DALL-E 1 generates realistic visuals
and art from simple text.
► The resolution of the images
produced by DALL E 1 is 1024
pixels.
DALL E 2
► DALL-E 2 discovers the link
between visuals and the language
that describes them. It employs a
technique known as “diffusion,”
which begins with a pattern of
random dots and gradually changes
that pattern to resemble a picture
when it recognizes particular
characteristics of that image.
► The resolution of the images
produced by DALL E 2 is 4x better
than its previous version.

6. Dall E 1 & Dall E 2
DALL E 1
► DALL-E could only render AI-
created images in a cartoonish
fashion, frequently against a
simple background.
► DALL-E “in-paints” or intelligently
replaces specific areas in an
image.
DALL E 2
► DALL-E 2 can produce realistic
images, which shows how superior
it is at bringing all ideas to life.
The images that come from DALL-E
2 are larger and more detailed.
► DALL-E 2 has far more possibilities,
including the ability to create new
items.

8. DALL E 2 Working
► DALL-E 2's operation is very simple at its most basic:
1. To begin, a text prompt is fed into a text encoder, which has been trained to map the
prompt to a representation space.
2. The prior model then maps the text encoding to a corresponding image encoding that
captures the semantic information contained in the text encoding.
3. Finally, an image decoder generates a random image that is a visual representation of this
semantic information.

10. Advantages
Efficiency:
The ability of DALL-E 2 to quickly produce high-quality, evocative images from a
simple descriptive prompt is the program's most significant benefit to the design
process.
Personas:
When designing with DALL-E, personas can be created in great detail. DALL-E 2 could
greatly aid in visualising a project's primary intended user. For example, if the client
wants to sell fashion to a specific demographic, designers can quickly iterate on how
that consumer might present themselves.

11. Advantages
Story Boarding:
Story boarding is an important part of the design process, and DALL-E 2 could easily be used to quickly
generate multiple scenarios. This could be used to create scenery to demonstrate a specific use case.
Art Direction:
Incorporating DALL-E 2 into the design process could aid in quickly shaping the brand's look and feel. The
A.I could act as an express form of inspiration and innovation, from creating mood boards to anticipating
marketing content and strategies to visualising the lifestyle that a project is attempting to express.
Summary:
To summarize, the future holds a plethora of limitless opportunities for both creatives and their clients.
Through programs like DALL-E 2, our imagination has been stretched to previously unimaginable new
heights. The onus is now on the creative industry to explore the program's plethora of creative avenues.
But this is only the beginning, and isn't it wonderful?

12. Limitation of DALL E 2
• It can’t generate violent content, explicit images, political content, and other sensitive
images. (shooting stars, blood diamond)
• DALL-E 2 can do scenes with generic backgrounds (a city, bookshelves in a library, a
landscape) but even then, if that's not the main focus of the image then the fine details
tend to get pretty scrambled.

13. Limitation of DALL E 2
► Position of objects relative to which other objects is also not good.
► DALL E 2 can’t count the numbers of objects if they are main focus, maximum it can
handle 2 or 3 objects.

14. Limitation of DALL E 2
• DALL E 2 can’t write the correct spellings in the image.

15. Limitation of DALL E 2
• DALL E 2 can’t draw realistic human faces.

16. Conclusion
►DALL-E 1 and DALL-E 2 are examples of how creative people and intelligent systems can work
together to build new things that will ultimately improve our creative potential. For the time being,
most creatives are merely experimenting with tools like this AI image generator as a concept.
► It does, however, show a future in which pushing the bounds of your imagination is the norm.
While many are still learning how DALL-E features work, you can already see how AI
that generates images may assist you in a variety of ways.

17. THANK YOU