One morning your correspondent woke up to an email from his editor, asking for yet another article. "Chatgpt and other generative-ai services seem to be taking the world by storm," it read. "Could you write an article explaining what they are and why they are not just hype?" As he was feeling lazy he asked Chatgpt, an ai-based online service trained on reams of text from the internet, to answer that question, adding that it should be written in Shakespearean language. But how will gpts (short for generative pre-trained transformers) and other such services make money?

Are you ready for a world where super-intelligent robots faithfully impersonate people? To help see what that might look like, The Wall Street Journal deployed ChatGPT, a free (for now) Artificial Intelligence trained on a huge dataset researchers gathered through 2021, which recently became a viral hit. We asked it to compose tweets in the style of public figures and institutions to see if anyone could distinguish them from the real thing. We included specifics in our prompts to the AI: write a tweet by Neil deGrasse Tyson about the universe. The topics we picked were based on the author's previous tweets.

Artificial intelligence is advancing faster than ever, with a new crop of generative AI programs that are creating art, videos, humor, fake news, and plenty of controversy. The technologies powering this latest slate of tools have been in the works for years, but the public release of these programs--particularly a new chatbot enabled by OpenAI's GPT system--represents a big step forward for machine intelligence. Same with the image-generating app Lensa, which creates painterly selfies that have captured the public's imagination. Now, engineers are asking chat programs for coding help, students are using AI to generate book reports instantly, and researchers are testing the tools' ethical boundaries. It's all gotten very weird, but AI is about to get bigger and even weirder still.

This article is part of our coverage of the latest in AI research. This week, OpenAI released ChatGPT, another fascinating large language model (LLM) based on its flagship GPT series. ChatGPT, which is available as a free demo at the time of this writing, is a model that has been specialized for conversational interactions. As with most things regarding LLMs, the release of ChatGPT was followed by controversy. Within hours, the new language model became a Twitter sensation, with users posting screenshots of ChatGPT's impressive achievements and disastrous failures. However, when looked at from the broad perspective of large language models, ChatGPT is a reflection of the short but rich history of the field, representing how far we have come in just a few years and what fundamental problems remain to be solved.

The ability to turn a user's selfie into an anime character has turbocharged the Meitu app to the top of Japan's download rankings over the past week, spurring a big jump in the company's shares. Hong Kong-based Meitu is up more than 50% over the past couple of weeks, in which time its app has reached the top of Apple's free iPhone downloads chart and No. 2 on Android's Google Play in Japan, according to data.ai While not new to the Japanese market, the key novelty in the beauty app was the addition of the option to transform a photo into an anime style with the help of AI. The use of AI to generate or alter images has taken off in global popularity this year with the introduction of text-to-image systems like Midjourney and OpenAI's Dall-E. The technology is not without its controversy, but its appeal and accessibility have helped it proliferate.

Who knew artificial intelligence could be so entertaining? Case in point is ChatGPT, a free AI chatbot that has probably been all over your social feeds lately. "Who was George Washington Carver?" But it can get creative, too: "Write a movie script of a taco fighting a hot dog on the beach" generates a thrilling page of dialogue, humor and action worthy of YouTube, if not quite Netflix: Taco: "So you think you can take me, hot dog? You're nothing but a processed meat product with no flavor."

Former English teacher, Peter Laffin, predicts OpenAI's new artificial intelligence chatbot will lead to a learning crisis and force teachers to rethink education. The emergence of artificial intelligence chatbots that can complete students' assignments will lead to a crisis in learning, forcing educators to rethink schooling entirely, a former teacher said. "The introduction of new artificial intelligence technologies into schools that enables students to auto-generate essays has the capacity to blow up our entire writing education curriculum," Peter Laffin, founder of Crush the College Essay and writing coach, told Fox News. "It may make us have to rethink it from the ground up, and that might ultimately be a good thing." Last week, tech company OpenAI unveiled an AI chatbot, ChatGPT, which has stunned users with its advanced functions.

A few weeks ago, Wharton professor Ethan Mollick told his MBA students to play around with GPT, an artificial intelligence model, and see if the technology could write an essay based on one of the topics discussed in his course. The assignment was, admittedly, mostly a gimmick meant to illustrate the power of the technology. Still, the algorithmically generated essays -- although not perfect and a tad over-reliant on the passive voice -- were at least reasonable, Mollick recalled. They also passed another critical test: a screening by Turnitin, a popular anti-plagiarism software. AI, it seems, had suddenly gotten pretty good.

OpenAI has recently released their latest Artificial Intelligence (AI) chatbot prototype powered by a model from the GPT-3.5 series. It provides a service where you can ask questions and it comes back with a detailed answer in a conversational way. Almost as if you were talking to a human! ChatGPT is based on a trained model using Reinforcement Learning from Human Feedback which allows it to simulate conversation, answer follow-up questions and even admit to mistakes. Even though OpenAI's ChatGPT has recently taken the internet by storm, is it as good as it seems when it comes to dealing with a niche topic?

Despite the impact of psychiatric disorders on clinical health, early-stage diagnosis remains a challenge. Machine learning studies have shown that classifiers tend to be overly narrow in the diagnosis prediction task. The overlap between conditions leads to high heterogeneity among participants that is not adequately captured by classification models. To address this issue, normative approaches have surged as an alternative method. By using a generative model to learn the distribution of healthy brain data patterns, we can identify the presence of pathologies as deviations or outliers from the distribution learned by the model. In particular, deep generative models showed great results as normative models to identify neurological lesions in the brain. However, unlike most neurological lesions, psychiatric disorders present subtle changes widespread in several brain regions, making these alterations challenging to identify. In this work, we evaluate the performance of transformer-based normative models to detect subtle brain changes expressed in adolescents and young adults. We trained our model on 3D MRI scans of neurotypical individuals (N=1,765). Then, we obtained the likelihood of neurotypical controls and psychiatric patients with early-stage schizophrenia from an independent dataset (N=93) from the Human Connectome Project. Using the predicted likelihood of the scans as a proxy for a normative score, we obtained an AUROC of 0.82 when assessing the difference between controls and individuals with early-stage schizophrenia. Our approach surpassed recent normative methods based on brain age and Gaussian Process, showing the promising use of deep generative models to help in individualised analyses.