Artificial intelligence, or AI for short, has come a long way in the past 10 months since the launch of many people’s favorite chatbot ChatGPT, which has pushed the boundaries of what was once thought impossible in the digital tech space.
One of the most exciting developments in AI is the ability to generate stunning images, which has traditionally been an area dominated by real human artists and designers. So, now you may be wondering, does ChatGPT make images?
The answer to that is, no, ChatGPT does not directly make images. But OpenAI has recently integrated Dall-E 3 with ChatGPT+, so it’s fair to say that ChatGPT+ can be used to make images with its Dall-E integration. It can also create wonderful prompts that can be fed into other image generators like Stable Diffusion and Midjourney.
Read on to discover how this conversational text generator can help you to create images that are out of this world.
Does ChatGPT Make Images?
The simple answer to the question does ChatGPT make images? is no. This is because ChatGPT is a generative text AI model that is unable to produce images in its current iteration. (Yes, it can do thing like ASCII art, but we’re not counting that).
However, those who subscribe to ChatGPT+ get tied in to the Dall-E image generator as part of the package. Dall-E, a GAN image generator, can make images.
Additionally, ChatGPT can generate prompts that are automatically fed into Dall-E 3, which creates an image.
The Power of ChatGPT
ChatGPT is a powerful natural large language model (LLM) that was developed by parent company OpenAI, and has been making waves in the AI community because of its human-like text-based capabilities, which can be used for many potential applications like resume review, spreadsheet work and more, although it has limitations as far as generating images is concerned.
Generative AI, like ChatGPT, comes in many forms.
The term refers to a subset of artificial intelligence that focuses on creating new data instances, such as text, images, or audio, that are similar to existing data.
Unlike traditional AI models, which are designed for tasks like classification and prediction, generative AI aims to generate original and unique content that doesn’t exist within its training data.
That’s why this emerging AI technology has gained so much attention, because its ability to generate and create new content means that it can be used for applications from writing to music, and beyond.
The four most common types of generative AI are:
Transformative models, such as ChatGPT and other GPT series AIs, are primarily used for natural large language understanding and generation. They are based on deep neural networks, and are able to generate clear and contextually relevant text.
Most often, they are used in applications like chatbots, content generation, and automated text summarization.
Generative Adversarial Networks, or GANs, are formed by two neural networks — a generator and a discriminator — that resist each other. The generator tries to create the data, such as images, that are distinguishable from real ones, while the discriminator aims to distinguish between the real and generated data.
AI Image generators like Midjourney, Dall-E, and Stable Diffusion are GANs.
This type of adversarial training results in the generator becoming progressively better at producing more realistic content. GANs are used in image generation, style transfer, deepfake creation, and even assisting in medical imaging and drug discovery.
Otherwise known as VAEs, these AI models are used in unsupervised learning and are primarily applied to image and text data. VAEs are useful for tasks like image synthesis and data augmentation.
Recurrent Neural Networks
Finally, recurrent Neural Networks, or RNNs, are AI models that are able to generate sequential data, such as text or music. They operate by maintaining a hidden state that captures temporal dependencies in the data, and are used in natural language generation tasks, chatbots, and even music composition.
These generative AI techniques have opened up a whole world of possibilities by enabling ‘the machines’ to create content that was once considered the exclusive domain of human creativity. And as they continue to advance, they will lead to even more exciting prospects in fields ranging from arts and entertainment to healthcare and data analysis.
But when it comes to making images with AI, GANs primarily focus on image-to-image generation and manipulation, rather than language understanding and generation, but this is where transformative AI natural large language model ChatGPT shines.
When it comes to making images with AI, GANs primarily focus on image-to-image generation and manipulation, rather than language understanding and generation, but this is where transformative AI natural large language model ChatGPT shines.
So, can ChatGPT, an AI designed for text-based tasks, help to generate images? Well, it does have some image-related capabilities, so let’s take a closer look.
ChatGPT and Image Descriptions
If you don’t have access to ChatGPT+, you can use it to create image prompts for other systems like Midjourney and Stable Diffusion.
One of ChatGPT’s great abilities is that it is able to describe images based on textual prompts. So, for example, if you give it a description like, “A calm beach with fine white sand and crystal clear water”, then ChatGPT will generate a response that visually describes this scene.
What it won’t do is create an actual image, but it will generate a detailed textual description of what the image would look like.
When we prompted ChatGPT to help us with the description “A calm beach with fine white sand and crystal clear water”, this is what we got, which is obviously a much more detailed and stunning image than we would have received with the original prompt:
And this was the result we got from Stable Diffusion when we used ChatGPT’s elaborate description:
Creating images from text prompts can be quite a complex task if you don’t know how to elaborate a textual description in order for it to translate it into a visual representation that generates a beautiful image.
And while there have been significant advancements in AI-driven text-to-image models like DALL-E, Midjourney, and Stable Diffusion, which rely on a combination of GAN-like architectures and extensive image-text pair training datasets, ChatGPT can give your prompts more creative potential that will get these models to create the images you’re after.
By interacting with ChatGPT and providing it with descriptive prompts, users can engage in a back-and-forth dialogue. For example, if you describe a surreal scene, then ChatGPT can respond with imaginative narratives you may have never thought of, which will further develop the scenario.
Using ChatGPT’s image descriptions can also help visually impaired individuals gain a better understanding of the visual content they want to produce by providing textual descriptions of images that can improve accessibility for all users.
Content creators and marketers can use ChatGPT to generate image descriptions for their multimedia content, which can be used to enhance the discoverability of their content, as well as improve SEO by providing textual information that search engines will be able to index.
Writers, designers, and even artists, can use ChatGPT to translate their conceptual ideas into more vivid descriptions. While the AI chatbot won’t replace the need for visual artists, at least in the near future, it can serve as a starting point for anyone’s creative projects.
Finally, when it comes to other potentials, educational institutions can use ChatGPT to give textual descriptions of visual content in textbooks and online courses. Doing so can assist students in understanding diagrams, charts, and other visual aids better.
Of course, as with any AI technology, there are limitations when it comes to getting ChatGPT to help you with enhanced image descriptions that you want to use with AI text-to-image models like Stable Diffusion.
For example, the image descriptions that ChatGPT generates, based on your text prompt, might not always reflect the intended image accurately. Because being an AI model, it’s not always easy to capture the nuances of complex visuals!
In addition, like other AI models, ChatGPT can sometimes produce biased or sensitive content. Therefore, it’s essential to monitor and review the text output you receive from the AI chatbot, in order to ensure that it aligns with ethical guidelines and standards, especially if and when personal information is used.
ChatGPT+ With Dall-E Integration
As mentioned above OpenAI has rolled out a new multimodal version of GPT 4 that can browse the web, perform advanced data processing, and has access to Dall-E. Additionally, Dall-E has just been upgraded to version 3, with solid leaps in quality.
While Midjourney is still clearly the top image generator at the moment, v3 of Dall-e is holding its own for quality. And it is tied in with ChatGPT and included in the Plus subscription, so no need to pay for multiple subscriptions.
Going forward, it appears there will be less of an emphasis on crafting the perfect prompt, and more on using ChatGPT and Dall-E to create better images, conversing with ChatGPT and iterating on your image.
As you now know, ChatGPT is a powerful AI model that excels in natural language understanding and generation. So, does ChatGPT make images? ChatGPT is a Large Language Model, and does not generate images. But the ChatGPT+ version has direct access to Dall-E, which makes images.
So bascially, ChatGPT+ can make images by creating a prompt and then directly interfacing with Dall-E Image Generator. The end result is a wonderful image inside ChatGPT!