'100 Video Calls Per Day': Models Are Applying to Be the Face of AI Scams Dozens of Telegram channels reviewed by WIRED include job listings for "AI face models." The (mostly) women who land these gigs are likely being used to dupe victims out of their money. "I can speak fluent English, I can speak good Chinese, I also speak Russian and Turkish," the glamorous, 24-year-old Uzbekistani woman explains in a selfie-style video made for recruiters. Angel had arrived in the Cambodian city of Sihanoukville that day, she said, and was ready to start work immediately. Those impressive language skills, however, have likely been put to use as part of elaborate " pig-butchering " scams targeting Americans.

Many in the UK who unwrapped a new drone this Christmas may face a rude awakening next week, when they will have to take a theory test before being allowed to fly outdoors. From 1 January, those intending to fly drones or model aircraft weighing 100g or more outside must complete a Civil Aviation Authority (CCA) online theory test to get a Flyer ID - something previously only needed for heavier drones. The regulator believes up to half a million people in the UK may be impacted by its new requirements. CAA spokesperson Jonathan Nicholson said with drones becoming a common Christmas present it was important people knew how to comply with the law. With the new drone rules coming into force this week, all drone users must register, get a Flyer ID and follow the regulations, he said.

Skateboarders call it "pumping," and it's a skill that both Olympic medalists and aspiring thrashers use to build launch speed from what seems like thin air. But what separates the steeziest pro from the sketchiest beginner is the years' worth of practice it takes to develop the know-how to execute the cleanest pump -- or at least that was the case until now. In a paper published Monday in the journal Physical Review Research, scientists have revealed the secret of achieving serious airtime. A skateboarder rides the bowls at Etnies skatepark in Lake Forest. With a bit of coding, researchers were able to describe the optimal technique for pumping -- a tactic where skateboarders crouch down low momentarily and then push their body upright on inclines.

The birth of human consciousness may have truly been magic. Scientists have claimed that the consumption of the fungi psilocybin, also known as'magic mushrooms,' influenced pre-human hominids' brains six million years ago. They analyzed dozens of studies involving psilocybin and consciousness, finding the fungi increased connectivity between networks in the frontal brain region associated with expressive language, decision-making and memory. These'significant neurological and psychological effects' may have been the catalase ancient ancestors to interact with each other and the environment - spurring consciousness among our species. The idea that magic mushrooms sparked the pivotal point in humans has been touted by podcaster Joe Rogan, who has referenced the'Stoned Ape Theory' on his show multiple times.

Mechanisms for generating differentially private synthetic data based on marginals and graphical models have been successful in a wide range of settings. However, one limitation of these methods is their inability to incorporate public data. Initializing a data generating model by pre-training on public data has shown to improve the quality of synthetic data, but this technique is not applicable when model structure is not determined a priori. We develop the mechanism jam-pgm, which expands the adaptive measurements framework to jointly select between measuring public data and private data. This technique allows for public data to be included in a graphical-model-based mechanism. We show that jam-pgm is able to outperform both publicly assisted and non publicly assisted synthetic data generation mechanisms even when the public data distribution is biased.

Privately generating synthetic data from a table is an important brick of a privacy-first world. We propose and investigate a simple approach of treating each row in a table as a sentence and training a language model with differential privacy. We show this approach obtains competitive results in modelling tabular data across multiple datasets, even at small scales that favor alternative methods based on marginal distributions.

The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimisation of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimisation. Here, an automated, HRR-compatible system produced high fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimisation of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually-optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimisation of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.

ChatGPT, the AI-driven chatbot that produces remarkable results from simple queries, has been the sensation of the tech world over the past few months, since launching in November. And unless you've been living in a cave without wifi you are likely to have read a flurry of articles on what impact it may have. Some people believe it marks a technology inflection point; and points to the redefining of many knowledge jobs, beginning with lawyers, journalists, marketers, teachers, lecturers, software coders and possibly even doctors. Others have speculated that it points to a post-Google world, leapfrogging the familiar search paradigm of the past 20 years, or will transform personal business and productivity tools so that emails, spreadsheets, reports and even software may all be generated by AI tools. GPT-3, or Generative Pre-trained Transformer, from San Francisco start-up OpenAI, is a type of artificial intelligence that has the unerring ability to generate remarkably human-like text, from a short query or input text.

Aerospace Xelerated recently hosted a panel discussing one of our upcoming programme themes. In the'Demystifying AI' panel, we welcomed some exciting guests from the field: The diverse range of panellists, hosted by Programme Manager Ksenia Kurileva, discussed the importance and challenges that Artificial Intelligence poses. We learned how panelists got into the AI space and their experiences with artificial intelligence, including the projects that they are currently working on. John McKenna shared how Artificial Intelligence is assisting in aviation regulation in relation to drone company Sees.ai. He flagged the issue of capturing data and its importance to AI: data is required to train AI models, but the initial data needs to be obtained before that can happen.

AI and robotic process automation are taking over more and more tasks from ERP users. RPA mimics human behavior, recording users as they enter data, execute commands and move documents across applications. The machine-learning AI in ERP scans information for patterns, "learns" what to expect, makes decisions and even tries to predict the future. Both technologies are enabling a new kind of ERP that is more automated, responsive and easier to use than its often frustratingly obstinate ancestors. But just how intelligent, really, is the AI in ERP? Where does robotic process automation (RPA) belong?