Traders on the floor of the New York Stock Exchange as markets fell on Friday morning trading after a steep drop on Thursday, as investors continue to worry about the impact of AI on business and the wider economy. Traders on the floor of the New York Stock Exchange as markets fell on Friday morning trading after a steep drop on Thursday, as investors continue to worry about the impact of AI on business and the wider economy. The message from investors to the software, wealth management, legal services and logistics industries this month has been clear: AI is coming for your business. The release of new, ever more powerful AI tools has coincided with a stock market slide, which has swept up sectors as diverse as drug distribution, commercial property and price comparison sites. Advances in the technology are giving increasing credulity to predictions that it could render millions of white-collar jobs obsolete - or, at least, eat into the profits of established companies.

Big AI companies courted controversy by scraping wide swaths of the public internet. With the rise of AI agents, the next data grab is far more private. For years, the cost of using "free" services from Google, Facebook, Microsoft, and other Big Tech firms has been handing over your data. Uploading your life into the cloud and using free tech brings conveniences, but it puts personal information in the hands of giant corporations that will often be looking to monetize it. Now, the next wave of generative AI systems are likely to want more access to your data than ever before. Over the past two years, generative AI tools--such as OpenAI's ChatGPT and Google's Gemini--have moved beyond the relatively straightforward, text-only chatbots that the companies initially released.

New research shows that social media creators have enormous influence over their audiences' politics--especially those who don't normally share political content. Donald Trump's appearances on the podcasts of Joe Rogan and Theo Von, among others, were seen by many as a key part of securing his second term in office. But while Trump was speculating about alien life on Mars with Rogan, he had a team of acolytes appearing on dozens, if not hundreds, of much smaller niche podcasts hosted by right-wing content creators who typically don't talk about politics. This is how, just six days before the election, Kash Patel, the man now struggling to run the FBI, ended up appearing on the livestream, a fringe, QAnon-infused show hosted on a platform called Pilled. "The Deep State exists," Patel told the audience.

Shimon Whiteson is a Professor of Computer Science at the University of Oxford and a Senior Staff Research Scientist at Waymo UK. His research focuses on deep reinforcement learning and imitation learning, with applications in robotics and video games. He completed his doctorate at the University of Texas at Austin in 2007. He spent eight years as an Assistant and then an Associate Professor at the University of Amsterdam before joining Oxford as an Associate Professor in 2015. His spin-out company Latent Logic was acquired by Waymo in 2019.

Drug repurposing often starts as a hypothesis: a known compound might help treat a disease beyond its original indication. Knowledge graphs are a natural place to look for such hypotheses because they encode biomedical entities (drugs, genes, phenotypes, diseases) and their relations. In KG terms, that repurposing can be framed as a triple (). However, many link prediction methods trade away interpretability for raw accuracy, making it hard for scientists to see why a suggested drug should work. We argue that for AI to function as a reliable scientific tool, it must deliver scientifically grounded explanations, not just scores.

Is chlorophyll actually good for you? Some benefits are rooted in science, but others are just leafy lore. Thanks to social media, chlorophyll water is now an internet sensation, promising everything from clearer skin to better breath. But does the green liquid live up to the hype? Breakthroughs, discoveries, and DIY tips sent every weekday.

The original version of this story appeared in Quanta Magazine. When she was 10 years old, Rose Yu got a birthday present that would change her life--and, potentially, the way we study physics. Her uncle got her a computer. That was a rare commodity in China 25 years ago, and the gift did not go unused. At first, Yu mainly played computer games, but in middle school she won an award for web design.

Scientists have discovered a hidden sign of consciousness in comatose patients that shows they can hear and understand the world around them. The study found bursts of organized, fast frequencies within the patient's normal sleep patterns when they were exposed to stimuli such as their doctor talking. Researchers at Columbia University analyzed 226 recent comatose patients, observing a third displayed the unique bursts - a phenomenon scientists call'sleep spindles.' Brain circuits that are fundamental for consciousness are also key to how we sleep, the Columbia team explained. Moreover, scientists said comatose patients with this type of'hidden consciousness' showed signs they were already on the road to recovery from their brain injuries and many dealt with fewer disabilities later in life.

This enables the identification of the text for which AI assistance has been used. How AI was used AI tools can be used for many different tasks: summarizing, translation, paraphrasing, finding related work and citations, etc. So, it is important to have information on how AI tools were used in the paper. For example, we can encode in the metadata that GPT -4 (so the "which") was used to summarize (the "how") and write the abstract (the "where").UNDERSTANDING THE IMP ACT OF AI IN ACADEMIC WRITING Let us consider now that we have a large corpus of papers and we want to know how many of them have used AI to summarize the abstract. Without metadata, all papers look the same (Figure 2, left), so we have to extract the text and either try to detect the use of AI in the abstract or find a disclosure of the authors that states the use of AI in the abstract. Instead if the proposed metadata has been added to the paper, we can just look at the how (summarizing) and where (abstract) to find the papers. The papers are now marked and can be easily identified (Figure 2, right). The metadata can be used to analyze many aspects of the use of AI in academic writing, for example, we can analyze: 1) The adoption of the different AI tools and their variations over time.

Generative artificial intelligence (AI) has taken off at lightning speed in the past couple of years, creating disruption in many industries. A new report published this week finds that news audiences and journalists alike are concerned about how news organisations are – and could be – using generative AI such as chatbots, image, audio and video generators, and similar tools. The report draws on three years of interviews and focus group research into generative AI and journalism in Australia and six other countries (United States, United Kingdom, Norway, Switzerland, Germany and France). Only 25% of our news audience participants were confident they had encountered generative AI in journalism. About 50% were unsure or suspected they had.