Working out who has produced work isn't always an easy matter Tools to detect if a body of English text has been written by humans or artificial intelligence exhibit bias against people whose primary language isn't English. The tests frequently misidentify their work as being created by an AI. Text-generating AI models such as OpenAI's ChatGPT and GPT-4 are being used by some students at schools and universities to create essays that they are passing off as their own work.

Sam Altman became a tech sensation this year as the CEO of OpenAI, the artificial-intelligence startup that seems pulled from science fiction. But Mr. Altman, who has been among Silicon Valley's most prominent investors for more than a decade, has placed one of the biggest bets of his career on a company that might be even more futuristic: a nuclear-fusion startup called Helion Energy Inc.

As generative AI tools continue to overwhelm "future of technology" discussions at every level, Communications' Senior Editor Ralph Raiola thought it might be interesting to collaborate with OpenAI's ChatGPT on an original sci-fi short story. Here's a full transcript of the process and a partially finished product. COMMUNICATIONS: ChatGPT, would you like to write a sci-fi short story with me?

A few months ago, I was waiting for the subway with a friend, a professional editor, who had never used a large language model (LLM). Standing on the platform, she told me about an article she'd been working on. ChatGPT had come out six weeks earlier, and I input her summary into it on my phone and showed her the result. I'd been following OpenAI's transformer-driven models since 2019 and had forgotten the effect they can have on first exposure. My friend couldn't take her eyes off the little gray box as the article came out, line by line.

Sundar Pichai told '60 Minutes' that the state of the technology is still somewhat of a black box to researchers. With the rapid emergence of artificial intelligence, which is quickly making its way into the daily lives of individuals around the world, there are a lot of questions circulating about the new technology. Artificial intelligence has existed for a long time, but its capacity to emulate human intelligence, and the tasks that it is able to perform have many worried about what the future of this technology will bring. Here are answers to some of the big questions surrounding artificial intelligence. There are lots of questions about artificial intelligence, especially with the emergence of AI chatbots like ChatGPT.

OpenAI CEO Sam Altman said that he was "a little bit scared" of ChatGPT and admitted that his technology would likely destroy "a lot of current jobs." In addition to writing articles, songs and code in mere seconds, ChatGPT could potentially make its way into your doctor's office -- if it hasn't already. The artificial intelligence-based chatbot, released by OpenAI in December 2022, is a natural language processing (NLP) model that draws on information from the web to produce answers in a clear, conversational format. While it's not intended to be a source of personalized medical advice, patients are able to use ChatGPT to get information on diseases, medications and other health topics. Some experts even believe the technology could help physicians provide more efficient and thorough patient care.

This paper introduces a stochastic plug-and-play (PnP) sampling algorithm that leverages variable splitting to efficiently sample from a posterior distribution. The algorithm based on split Gibbs sampling (SGS) draws inspiration from the alternating direction method of multipliers (ADMM). It divides the challenging task of posterior sampling into two simpler sampling problems. The first problem depends on the likelihood function, while the second is interpreted as a Bayesian denoising problem that can be readily carried out by a deep generative model. Specifically, for an illustrative purpose, the proposed method is implemented in this paper using state-of-the-art diffusion-based generative models. Akin to its deterministic PnP-based counterparts, the proposed method exhibits the great advantage of not requiring an explicit choice of the prior distribution, which is rather encoded into a pre-trained generative model. However, unlike optimization methods (e.g., PnP-ADMM) which generally provide only point estimates, the proposed approach allows conventional Bayesian estimators to be accompanied by confidence intervals at a reasonable additional computational cost. Experiments on commonly studied image processing problems illustrate the efficiency of the proposed sampling strategy. Its performance is compared to recent state-of-the-art optimization and sampling methods.

From tech moguls in Silicon Valley to those who have the luxury of indulging in the exploration of cutting-edge AI technologies, OpenAI's ChatGPT has captured the imagination of many with its conversational AI capabilities. The large language models that underpin ChatGPT and similar language technologies rely on vast amounts of textual data and alignment procedures to generate responses that can sometimes leave users pondering whether they're interacting with a piece of technology or a human. While some view making language agents such as Chat-GPT merely as a significant step in developing AI for linguistic tasks, others view it as a vital milestone in the ambitious pursuit of achieving artificial general intelligence - AI systems that are generally more intelligent than humans. In a recent blogpost OpenAI's CEO, Sam Altman, emphasizes the ambitious role of this technology as a step towards building "artificial general intelligence" that "benefits all of humanity." ChatGPT promises to enhance efficiency and productivity with its remarkable capabilities.

ChatGPT is a natural language processing tool that can engage in human-like conversations and generate coherent and contextually relevant responses to various prompts. ChatGPT is capable of understanding natural text that is input by a user and generating appropriate responses in various forms. This tool represents a major step in how humans are interacting with technology. This paper specifically focuses on how ChatGPT is revolutionizing the realm of engineering education and the relationship between technology, students, and faculty and staff. Because this tool is quickly changing and improving with the potential for even greater future capability, it is a critical time to collect pertinent data. A survey was created to measure the effects of ChatGPT on students, faculty, and staff. This survey is shared as a Texas A&M University technical report to allow other universities and entities to use this survey and measure the effects elsewhere.

Cytometry enables precise single-cell phenotyping within heterogeneous populations. These cell types are traditionally annotated via manual gating, but this method suffers from a lack of reproducibility and sensitivity to batch-effect. Also, the most recent cytometers - spectral flow or mass cytometers - create rich and high-dimensional data whose analysis via manual gating becomes challenging and time-consuming. To tackle these limitations, we introduce Scyan (https://github.com/MICS-Lab/scyan), a Single-cell Cytometry Annotation Network that automatically annotates cell types using only prior expert knowledge about the cytometry panel. We demonstrate that Scyan significantly outperforms the related state-of-the-art models on multiple public datasets while being faster and interpretable. In addition, Scyan overcomes several complementary tasks such as batch-effect removal, debarcoding, and population discovery. Overall, this model accelerates and eases cell population characterisation, quantification, and discovery in cytometry.