Customer data from more than 350 hotels around the world may have been accessed as part of realistic reservation-hijacking scams. Travelers' information and booking details may have been stolen from hundreds of hotels around the world, according to new findings from security researchers. These swiped trip details, such as booking names and reservation information, are then being repurposed by cybercriminals to create highly targeted phishing messages used to steal credit card information. At least 350 hotels, vacation rentals, motels, and guesthouses in 50 different countries have been caught up in so-called reservation hijacking scams, according to an analysis of phishing messages and cybercriminal infrastructure by security company Norton. Researchers say the use of legitimate booking information in phishing messages may increase the chances that someone clicks on a fraudulent link and hands over other sensitive details to criminals.

When you purchase through links in our articles, we may earn a small commission. Norton's new Neo browser brings AI to the search bar, today Norton Neo is free to test, but the browser may include paid features in the future. For years, the URL bar in your browser has done double duty: you can enter a web address, sure, but you can also use it to enter search requests. Now Norton has a new "free" browser, Neo, which adds a third function: AI prompting. Norton--most famous for its antimalware solutions like Norton 360 Deluxe --is entering the browser market with Norton Neo, an AI-first browser that you can sign up for and join the waitlist.

Norton's award-winning security software makes it simple to keep you and your family safe from increasingly sophisticated digital threats. AI scams are getting more sophisticated. Here's how Norton is fighting back to protect you and your family. It feels like overnight AI has ended up just about everywhere. From deepfakes and ChatGPT homework, to em-dashes and political misinformation, keeping on top of the latest AI trends is almost impossible.

Tractography fiber clustering using diffusion MRI (dMRI) is a crucial method for white matter (WM) parcellation to enable analysis of brains structural connectivity in health and disease. Current fiber clustering strategies primarily use the fiber geometric characteristics (i.e., the spatial trajectories) to group similar fibers into clusters, while neglecting the functional and microstructural information of the fiber tracts. There is increasing evidence that neural activity in the WM can be measured using functional MRI (fMRI), providing potentially valuable multimodal information for fiber clustering to enhance its functional coherence. Furthermore, microstructural features such as fractional anisotropy (FA) can be computed from dMRI as additional information to ensure the anatomical coherence of the clusters. In this paper, we develop a novel deep learning fiber clustering framework, namely Deep Multi-view Fiber Clustering (DMVFC), which uses joint multi-modal dMRI and fMRI data to enable functionally consistent WM parcellation. DMVFC can effectively integrate the geometric and microstructural characteristics of the WM fibers with the fMRI BOLD signals along the fiber tracts. DMVFC includes two major components: (1) a multi-view pretraining module to compute embedding features from each source of information separately, including fiber geometry, microstructure measures, and functional signals, and (2) a collaborative fine-tuning module to simultaneously refine the differences of embeddings. In the experiments, we compare DMVFC with two state-of-the-art fiber clustering methods and demonstrate superior performance in achieving functionally meaningful and consistent WM parcellation results.

"In the industrial age, automation came for the shoemaker and the factory-line worker," writes Dennis Yi Tenen near the start of Literary Theory for Robots. "Today, it has come for the writer, the professor, the physician, the programmer and the attorney." Like the end-of-the-planet movies that pelted the multiplexes at the turn of the millennium, newspapers and – increasingly – bookshops are awash with economists, futurologists and social semioticians talking up, down and about artificial intelligence. Even Henry Kissinger, in The Age of AI (2021), spoke of "epoch-making transformations" and an imminent "revolution in human affairs". Tenen, a tenured professor of English at New York's Columbia University, isn't nearly as apocalyptic as he initially makes out.

These days, the sheer volume of scam attempts online makes it difficult to figure out what's genuine and what's not. But Norton's AI-powered Genie tool is designed to help. Norton says Genie uses artificial intelligence to analyze images and text, then tell you if it's likely to be a scam or not. If it thinks you're being scammed, you'll be offered advice on what to do next. To get started, you can head to the web version (on Chrome, Safari, Edge or Firefox) or download the iOS app (version 14.0 or later), then upload a screenshot or paste text from a potential scam.

Norton says it tracked more than $29 million in bitcoin stolen last year and expects this figure to continue to rise in 2022. The company says in Australia, between January and March of this year, Norton thwarted more than 37,098,261 threats, the equivalent of around 403,241 threats per day. That included 471,361 phishing attempts and 59,540 tech support scams. Its latest Consumer Cyber Safety Pulse report found that deepfakes are being utilised by bad actors to scam consumers and spread disinformation. The Norton Labs team spotted deepfakes used to create fake social media profiles, fuel charity scams and other fraudulent ploys, and spread propaganda relating to the ongoing war in Ukraine.

This article was first published in the Virginia Mercury. Last week when Virginia's new Secretary of Transportation Sheppard Miller publicly declared his belief that flying cars will be a reality within the next 50 years as a reason that leaders across the commonwealth should "reexamine transit," some might have scoffed. But just as flying cars consumed the fantasies of many mid-century Americans, today plenty of people put their faith in another utopian technology replete with endlessly elusive promises of improved safety and unbridled freedom: autonomous vehicles. As is often the case in the United States, the regulation of autonomous vehicles is largely left to the states, resulting in a patchwork of conflicting and confusing policies where some sort of national approach ought to exist. Any state has the right to craft their own legal framework for the emerging technology but few have -- our commonwealth included.

Robots and artificial intelligence will replace workers on Australia's first fully automated farm created at a cost of $20 million. Charles Sturt University in Wagga Wagga will create the "hands-free farm" on a 1,900-hectare property to demonstrate what robots and artificial intelligence can do without workers in the paddock. Food Agility chief executive Richard Norton said the reality of "hands-free" farming' was closer than many people realised. "Full automation is not a distant concept. We already have mines in the Pilbara operated entirely through automation", he said "It's not beyond the realms of possibility that a farmer could be sitting in a study in front of a computer driving multiple vehicles".

The impact of the COVID-19 pandemic on education has been profound, with new ways of thinking about how best to teach students reverberating in institutions of higher learning, K-12 classrooms and in the business community. The role of AI is central to the discussion on every level. For the K-12 classroom, teachers are thinking about how to use AI as a teaching tool. For example, Deb Norton of the Oshkosh Area school district in Wisconsin, was asked several years ago by the International Society for Technology in Education to lead a course on the uses of AI in K-12 classrooms, according to a recent account in Education Week. The course includes sections on the definition of artificial intelligence, machine learning, voice recognition, chatbots and the role of data in AI systems.