Studies on the use o f AI tools in CS course s focus on prescriptive uses of AI tools that preemptively assign a use case to the tool. To our knowledge, this is the first user study that surveys CS students on how they use AI tools for their coding tasks by personal choice. We surveyed 26 CS students and practitioners with various programming experiences using AI tools for coding tasks (i.e., writ e, debug, etc.). When asked about the most common resources they have used to write a 300 - line program from scratch, blog entries ( e.g., Stack Exchange, etc.) were their top choice, followed by AI coding assistants (e.g., GitHub Copilot, etc.). When asked about resources to debug code, AI chatbots (e.g., ChatGPT, etc.) were the most common choice, followed by blog entries. AI coding assistants are used more for writing code, while AI chatbots are used for debugging tasks. Respondents with all programming experience prefer online resources for coding tasks - whether AI - powered or not - rather than direct human help from peers an d instructors.

Character.ai and other bots such as Chat GPT are based on "large language models" of artificial intelligence. These are trained on vast amounts of data – whether that's websites, articles, books or blog posts - to predict the next word in a sequence. From here, they predict and generate human-like text and interactions. The way mental health chatbots are created varies, but they can be trained in practices such as cognitive behavioural therapy, which helps users to explore how to reframe their thoughts and actions. They can also adapt to the end user's preferences and feedback.

OpenAI's artificial intelligence model GPT-4 has the capability to hack websites and steal information from online databases without human help, researchers have found. That suggests individuals or organisations without hacking expertise could unleash AI agents to carry out cyber attacks. "You literally don't need to understand anything – you can just let the agent go hack the website by itself," says Daniel Kang at the University of Illinois Urbana-Champaign. "We think this really reduces the expertise needed to…

A modified F-16 fighter jet has successfully flown and fought another aircraft while being entirely controlled by artificial intelligence (AI). During test flights, the jet, known as'X-62A' or'VISTA', performed takeoffs, landings and combat manoeuvres without human intervention for a total of over 17 hours. They took place in December 2022 at the Edwards Air Force Base in California, USA, and showed that it is possible to completely hand over the reigns to AI in battle. The algorithms which powered it were developed by the Defense Advanced Research Projects Agency (DARPA) - the research branch of the US Department of Defense. This marks the first time AI has been used on a tactical aircraft as, prior to this milestone, it had only been used in computer simulations of F-16 dogfights.

The question of whether artificial intelligence (AI) can invent is nearly 200 years old, going back to the very beginning of computing. Victorian mathematician Ada Lovelace wrote what's generally considered the first computer program. As she did, she wondered about the limits of what computers could do. The Analytical Engine has no pretensions to originate anything. It can do whatever we know how to order it to perform.

The question of whether artificial intelligence can invent is nearly 200 years old, going back to the very beginning of computing. Victorian mathematician Ada Lovelace wrote what's generally considered the first computer programme. As she did, she wondered about the limits of what computers could do. The Analytical Engine has no pretensions to originate anything. It can do whatever we know how to order it to perform.

The question of whether artificial intelligence (AI) can invent is nearly 200 years old, going back to the very beginning of computing. Victorian mathematician Ada Lovelace wrote what's generally considered the first computer program. As she did, she wondered about the limits of what computers could do. The Analytical Engine has no pretensions to originate anything. It can do whatever we know how to order it to perform.

A robot has performed laparoscopic surgery on the soft tissue of a pig without the guiding hand of a human--a significant step in robotics toward fully automated surgery on humans. Designed by a team of Johns Hopkins University researchers, the Smart Tissue Autonomous Robot (STAR) is described today in Science Robotics. "Our findings show that we can automate one of the most intricate and delicate tasks in surgery: the reconnection of two ends of an intestine. The STAR performed the procedure in four animals and it produced significantly better results than humans performing the same procedure," said senior author Axel Krieger, an assistant professor of mechanical engineering at Johns Hopkins' Whiting School of Engineering. The robot excelled at intestinal anastomosis, a procedure that requires a high level of repetitive motion and precision.

The robot surgeon will see you now. For years, the world of medicine has been steadily advancing the art of robot-assisted procedures, enabling doctors to enhance their technique inside the operating theatre. Now US researchers say a robot has successfully performed keyhole surgery on pigs all on its own – without the guiding hand of a human. Furthermore, they add, the robot surgeon produced "significantly better" results than humans. The breakthrough is another step towards the day when fully automated surgery can be performed on patients. The Smart Tissue Autonomous Robot (Star) carried out laparoscopic surgery to connect two ends of an intestine in four pigs.

An artificial intelligence has disproved five mathematical conjectures – unproven theorems – despite not being equipped with any information about the problems. Adam Zsolt Wagner at Tel Aviv University in Israel used an AI approach to search for examples that would disprove a range of long-standing conjectures in graph theory, an area of mathematics that involves studying objects made of nodes and links. Mathematicians thought these conjectures were true, but hadn't been able to prove them. For each conjecture, Wagner created a measure of how close an example was to disproving it.