Search 10M+ prompts, create and generate AI Art and AI Avatar via Stable Diffusion, DALL·E 2.

Sometimes we stumble upon insight in unexpected places. Late last year, for example, I read perhaps the most precise description ever written about AI-generated art in The New York Times comments section. The article described what happened when a man named Jason Allen submitted an image generated by the AI program Midjourney to an art contest and won. While the story focused on the debate over the ethics of AI image generators, the comment had nothing to do with thorny moral considerations. Instead, it described how the winning work looked.

If you've ever uploaded photos or art, written a review, "liked" content, answered a question on Reddit, contributed to open source code, or done any number of other activities online, you've done free work for tech companies, because downloading all this content from the web is how their AI systems learn about the world. Tech companies know this, but they mask your contributions to their products with technical terms like "training data," "unsupervised learning," and "data exhaust" (and, of course, impenetrable "Terms of Use" documents). In fact, much of the innovation in AI over the past few years has been in ways to use more and more of your content for free. This is true for search engines like Google, social media sites like Instagram, AI research startups like OpenAI, and many other providers of intelligent technologies. This exploitative dynamic is particularly damaging when it comes to the new wave of generative AI programs like Dall-E and ChatGPT.

A new AI-generated chatbot named ChatGPT is now raising ethical concerns regarding copywriting and plagiarism. AI-generated profile pictures from apps like Lensa AI have also become a viral sensation, and they, too, have faced criticism; artists are accusing the tech of forgery and theft, one of many conversations about how AI art has the potential to devalue work made by humans. No matter your stance on generative AI, one thing is clear: It will only continue to evolve, and as it does, its impact across business sectors is likely to be huge. Generative AI, as the name suggests, leverages artificial intelligence models to create various types of content, including images, code and text. The technology draws from existing data and content, as well as machine learning to predict the next word based on previous word sequences or to create an image based on words describing other images.

Attempts to ban generative AI such as ChatGPT are not all they are cracked up to be. To ban, or not to ban, that is the question. I would guess that if Shakespeare were around nowadays, he might have said something like that about the recent efforts to ban the use of a type of AI known as Generative AI, which is especially exemplified and popularized due to an AI app called ChatGPT. Some high-profile entities have been attempting to ban the use of ChatGPT. For example, the New York City (NYC) Department of Education recently announced that they were proceeding to block access to ChatGPT on its various networks and connected devices. The reported rationale for the ban consisted of indications that this AI app and the overall use of generative AI seemingly portend negative consequences for student learning. Students that opt to use ChatGPT are said to be undercutting the development of their crucial critical-thinking skills and undermining the growth of their problem-solving abilities. On top of those rather stoutly worrisome qualms, there is the undisputed fact that such AI can produce inaccurate outputs that contain errors and other factual maladies. The dangerous icing on the cake is the imagined possibility that the outputs could potentially be used in an unsafe manner by students that unknowingly rely upon said falsehoods. No such documented harms have yet surfaced that I've seen, so we'll need to just take at face value that this could potentially happen (I have discussed the range of possibilities in my postings; for example, some have posited that generative AI essays could tell someone to take medicines that they should not be taking or provide mental health advice that ought to be proffered by human mental health professionals, etc.).

GPT-4, is said by some to be "next-level" and disruptive, but what will the reality be? CEO Sam Altman answers questions about the GPT-4 and the future of AI. In a podcast interview (AI for the Next Era) from September 13, 2022, OpenAI CEO Sam Altman discussed the near future of AI technology. Of particular interest is that he said that a multimodal model was in the near future. Multimodal means the ability to function in multiple modes, such as text, images, and sounds.

Adobe chief product officer Scott Belsky has responded to criticism of the company's content analysis policies by saying it has never used customers' creations to train generative AI models. Artists were furious to learn Adobe could automatically analyze their audio, video or text documents stored on its cloud servers to develop and improve its AI products and services unless they opted out earlier this month. Fears that their work would be used to train generative text-to-image models capable of copying their style sparked an outcry. "We have never, ever used anything in our storage to train a generative AI model," Belsky insisted in an interview with Bloomberg this week. Belsky said the content analysis policy was geared towards improving existing features for its graphics software rather than for developing new AI image generation tools.

OpenAI has sparked an explosion of funding and software development around artificial-intelligence software that understands human language. While the technology still makes plenty of mistakes, new applications are coming out in droves, from tools that help marketers write copy to audio chatbots that may be able to negotiate discounts for customers of a companies like Comcast. Last week, subscribers of The Information joined a conference call about the year ahead in AI with Noam Shazeer, CEO of Character, which is developing chatbots similar to OpenAI's ChatGPT and who co-authored a seminal research paper on that subject while working at Google; and Clement Delangue, CEO of Hugging Face, which runs a Github-like service for software engineers to store their machine learning models.

The OpenAI website ChatGPT about page on laptop computer arranged in the Brooklyn borough of New York, US, on Thursday, Jan. 12, 2023. Microsoft Corp. is in discussions to invest as much as $10 billion in OpenAI, the creator of viral artificial intelligence bot ChatGPT, according to people familiar with its plans.

According to Ion Stoica, co-founder of Databricks and Anyscale, and also a senior professor of computer science at Berkeley, 2023 will be the year of "distributed AI frameworks." Needless to say, he has already had a hand in creating such a tool, in the form of Anyscale's open source Ray platform. Among other uses, Ray helps power OpenAI's groundbreaking ChatGPT. I interviewed Stoica to find out what Ray does exactly and, more generally, what is needed to scale AI software in this new era of generative AI. We also discuss the latest in "sky computing," a term Stoica and his Berkeley team introduced in 2021, in a paper that proposed a new form of cloud computing based around interoperability and distributed computing.