True, when we write academic articles nowadays, nobody expects you to provide the trail of references all the way down to Aristotle. But few people would say that taking someone's recent NeurIPS paper and republishing it would be ok. Yes, it is a continuum, but it's still real. What exactly is common knowledge and what deserves a reference at a given point in time varies by person, depending on their domain knowledge and principles. Still, everybody has a fairly clear idea of what their own boundaries are. Would you personally be comfortable with changing some variable names in a StackOverflow snippet and passing it as your own work? Would you tell your child it's ok to copy-paste essay passages from public domain sources - after all, it's not illegal? How about if you hear an apt metaphor in someone's keynote that you haven't heard anywhere else - would you say that it's "just English" and use it as your own? Whatever your answers are to these questions - you have these answers, which means that you have your own attribution norms.

In recent months, many people have begun to explore a new pastime: generating their own images using several widely-distributed programs such as DALL-E, Midjourney, and Stable Diffusion. These programs offer a straightforward interface wherein nontechnical users can input a descriptive phrase and receive corresponding pictures, or at least amusingly bad approximations of the results they intended. For most users, such artificial intelligence1 (AI)-generated art is harmless fun that requires no computer graphics skills to produce and is suitable for social media posts (see Figure 1). However, AI algorithms combine aspects of existing data to generate their outputs. DALL-E, Stable Diffusion, and other popular programs pull images directly from the internet to train their algorithms. Though these images might be easily obtainable--from the huge Google Images database, for example--the creators have not always licensed their art for reuse or use in the production of derivative works.

Has AI made Creativity a Thing of the Past? Recently, there has been an avalanche of interest in generative AI: programs that can produce text, speech, images, designs, music, and even computer code in an uncanny resemblance to human creations. AI systems, such as GPT-3, which mostly produces text, but can also produce images and computer code, or Dall-E, Stable Diffusion, or Midjourney, which produce images, are the tip of the iceberg in an expanding field that is attracting millions of users and billions of dollars in investments. The outputs of these systems can rival the quality of human products and work faster and cheaper than human writers, artists, and composers. Industries such as animated images for television and film are choosing AI artists over human ones to save time and money.

OpenAI, the San Francisco-based lab behind AI systems like GPT-3 and DALL-E 2, today launched a new program to provide early-stage AI startups with capital and access to OpenAI tech and resources. Called Converge, the cohort will be financed by the OpenAI Startup Fund, OpenAI says. The $100 million entrepreneurial tranche was announced last May and was backed by Microsoft and other partners. The 10 or so founders chosen for Converge will receive $1 million each and admission to five weeks of office hours, workshops and events with OpenAI staff, as well as early access to OpenAI models and "programming tailored to AI companies." "We're excited to meet groups across all phases of the seed stage, from pre-idea solo founders to co-founding teams already working on a product," OpenAI writes in a blog post shared with TechCrunch ahead of today's announcement.

Picsart, the world's leading digital creation platform and a top 20 most downloaded app worldwide, announced new generative AI tools to create images and ad copy. "There are two huge advantages of this technology: the first is making creativity accessible to new people and the second is increasing productivity for those who already create. The tools we're launching today are the first of many generative AI features we plan to roll out." Growing in popularity, text-to-image generators allow users to create an image from a few words or phrases. Picsart's AI Image Generator provides a unique, free and seamless end-to-end editing experience by offering the ability to create AI images in seconds.

The company then spent the next decade, and billions of dollars, trying to use Watson's artificial intelligence capabilities to solve a broad set of healthcare challenges, from helping doctors diagnose diseases based on symptoms to recommending clinical trials. In January, IBM announced it was selling Watson for parts to PE firm Francisco Partners. AI technologies have come a long way since that game show triumph. Some AI, such as those recommending ads on Google or detecting cancer on medical scans, have become part of everyday life. While improvements for these types of AI have been mostly incremental, over the last year machines suddenly became good at generating images and writing text.

AI image generators, which create fantastical sights at the intersection of dreams and reality, bubble up on every corner of the web. Their entertainment value is demonstrated by an ever-expanding treasure trove of whimsical and random images serving as indirect portals to the brains of human designers. A simple text prompt yields a nearly instantaneous image, satisfying our primitive brains, which are hardwired for instant gratification. Although seemingly nascent, the field of AI-generated art can be traced back as far as the 1960s with early attempts using symbolic rule-based approaches to make technical images. Yilun Du, a Ph.D. student in the Department of Electrical Engineering and Computer Science and affiliate of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), recently developed a new method that makes models like DALL-E 2 more creative and have better scene understanding. Here, Du describes how these models work, whether this technical infrastructure can be applied to other domains, and how we draw the line between AI and human creativity.

The tool is rolling out to Bing in selected markets, with integration with Microsoft Edge to come later this month. Microsoft says it will be free to use, but has outlined a content policy to prevent misuse. "It's important with early technologies like Image Creator – which is powered by AI technology DALL E 2 by OpenAI – to acknowledge that this is new and that we expect it to continue to evolve and improve," the blog adds. "We take our commitment to responsible AI seriously. To help prevent the delivery of inappropriate results across the Designer app and Image Creator, we are working together with our partner OpenAI, who developed DALL E 2, to take the necessary steps and will continue to evolve our approach. We will regularly take the feedback we have and share that with OpenAI to improve the model as well as applying to our own mitigations work."

If you grew up in a covered 12-foot hole in the Earth, and only had a laptop running the latest version of the Stable Diffusion AI image generator, then you would believe that there was no such thing as a woman engineer. The U.S. Bureau of Labor Statistics shows that women are massively underrepresented in the engineering field, but averages from 2018 show that women make up around a fifth of people in engineering professions. But if you use Stable Diffusion to display an "engineer" all of them are men. If Stable Diffusion matched reality, then out of nine images based on a prompt "engineer," 1.8 of those images should display women. Artificial intelligence researcher for Hugging Face, Sasha Luccioni, created a simple tool that offers perhaps the most effective way to show biases in the machine learning model that creates images. The Stable Diffusion Explorer shows what the AI image generator thinks is an "ambitious CEO" versus a "supportive CEO."

The AI community has a new obsession. It's called'generative artificial intelligence', and it refers to the idea of having computers take over creative tasks such as writing, filmmaking, and graphic design. AI art generators are paving a new path towards the freedom of artistic expression. In an extremely short period, they've allowed everybody with internet access and a keyboard to generate incredible art from simple text prompts. Considering the current state of things, it's too early to tell whether this new wave of apps will end up costing artists and illustrators their jobs. What seems clear though is that these tools are already being used in creative industries.