Generative models such as DALL-E 2 could represent a promising future tool for image generation, augmentation, and manipulation for artificial intelligence research in radiology provided that these models have sufficient medical domain knowledge. Here we show that DALL-E 2 has learned relevant representations of X-ray images with promising capabilities in terms of zero-shot text-toimage generation of new images, continuation of an image beyond its original boundaries, or removal of elements, while pathology generation or CT, MRI, and ultrasound images are still limited. The use of generative models for augmenting and generating radiological data thus seems feasible, even if further fine-tuning and adaptation of these models to the respective domain is required beforehand. DALL-E 2 is a novel deep learning model for text-to-image generation, first introduced by OpenAI in April 2022 [Ramesh et al., 2022]. The model has recently gained widespread public interest due to its ability to create photorealistic images solely from short written inputs [Kather et al., 2022][Conwell and Ullman, 2022][Marcus et al., 2022].

The interwebs, as of late, have been filled with images created by artificial intelligence rendering bots such as DALL-E and Midjourney -- and the humans (I think they're humans) using them as tools. Brooklyn-based artist Zach Katz has used it to reimagine the urban design of cities. A reporter at SFGATE has undertaken a similar project, asking DALL-E 2 to retool some of the city's architecture and infrastructure. In July, the Guardian rounded up four artists to come up with unlikely prompts -- such as "biotech harpy in field at sunset" -- for DALL-E Mini (the free, public version of DALL-E). Naturally, the advent of bots that can create an image out of a simple text command is drawing the scrutiny of illustrators.

What do the recent AI breakthroughs, DALLE[1] and Stable Diffusion[2] have in common? Hence, if you want to grasp how those models work, understanding CLIP is a prerequisite. Besides, CLIP has been used to index photos on Unsplash. But what does CLIP do, and why it's a milestone for the AI community? CLIP is an open source, multi-modal, zero-shot model.

Midjourney and DALL-E 2 emerged too late to be included in "Working With AI: Real Stories of Human-Machine Collaboration," by Thomas Davenport and Steven Miller, information-systems professors at Babson College and Singapore Management University, respectively. But the authors note other novel titles: chief automation officer; senior manager of content systems; architect, ethical AI practice. As AI's influence expands, its borders with the work world gain complexity. The bulk of "Working With AI" comprises 29 case studies in which corporate teams integrate automation into a workflow. Each chapter ends on three or four "lessons we learned."

Imagine producing your own film filled with big-budget scenery, but from a computer. A tech entrepreneur in Germany named Fabian Stelzer(Opens in a new window) is trying to do just that by using AI-powered programs to create the footage, sound effects, and voices for a 70s-inspired sci-fi film. The experimental project is called Salt(Opens in a new window), and it's built entirely with AI-generated art. To create the visuals, Stelzer has been tapping publicly available programs such as Midjourney, Stable Diffusion, and DALL-E 2, which can essentially draw anything you want by relying on a mere text description from the user. On Twitter, Stelzer has been releasing Salt in short clips, called "story seeds."

Studio Angel 1111 & "A Monk's Art" create this Buddhist Art Collection using Deep Dreaming algorithms and neural network color grading. All background images are AI generated. In the event that the piece is resold, these artworks are sold on secondary markets at a 2% royalty. These funds will be used to assist two monks with their spiritual studies.

The Yoga Tara Collection is a range of beautiful and unique Generative AI art inspired by the Buddhist deity Tara. The Yoga Tara Collection is not only stylish but also has a deeper meaning and purpose.

In August, first prize in the digital-art category of the Colorado State Fair's fine-art competition went to a man who used artificial intelligence (AI) to generate his submission, "Théâtre d'Opéra Spatial." He supplied the AI, a program called Midjourney, with only a "prompt"--a textual description of what he wanted. Systems like Midjourney and the similar DALL-E 2 have led to a new role in our AI age: "prompt engineer." Such people can even sell their textual wares in an online market called PromptBase. Midjourney and DALL-E 2 emerged too late to be included in "Working With AI: Real Stories of Human-Machine Collaboration," by Thomas Davenport and Steven Miller, information-systems professors at Babson College and Singapore Management University, respectively.

These AI systems create images based on instructions or directions. They will, if told to, create an image of a kiwi bird eating a kiwi fruit while sitting on a big padlock key. They can be used to create ads, fashion designs or movie production storyboards. DALL-E, Midjourney and Wombo Dream are examples of AI image generators. AI can also create three-dimensional spaces and objects, both real and digital. It can design buildings, rooms and even whole city plans, as well as virtual spaces for gameplay or metaverse-style collaboration.

Loab has been dubbed the first artificial intelligence-generated cryptid image and is taking the AI community by storm with its urban-legend mystique and horror backstory. Computers are becoming increasingly sophisticated, and powerful AI is being developed to make human lives easier, more fun or anything in between. AI simply stands for artificial intelligence, and as the name implies, it is the idea of creating a system that has similar intelligence or thinks similarly to humans. With advanced text-to-image software such as Dall-E 2 and Google's Imagen AI, the possibilities of artificial intelligence have never looked so bright, but are there darker aspects to this technology or horrible consequences for creating intelligent systems that users don't fully understand? Related:What Is The Future Of Dall-E AI Technology?