victim
Your family could be one phone call from a bank scam
This material may not be published, broadcast, rewritten, or redistributed. Quotes displayed in real-time or delayed by at least 15 minutes. Market data provided by Factset . Powered and implemented by FactSet Digital Solutions . Mutual Fund and ETF data provided by LSEG . Artemis crew says they wanted to'connect with humanity,' show what can be done when they put their mind to it Scientists revive ancient 24,000-year-old'zombie worm' from Arctic ice -- then it reproduced'Gigantic' ancient octopus used jaws to crush prey and hunted alongside the dinosaurs 100M years ago: study Scientists uncover identity of mysterious'golden orb' discovered miles underwater in 2023 Artemis astronauts enter eerie 40-minute communication blackout on Moon's far side NASA chief Jared Isaacman says Artemis II would not be possible'if it wasn't for President Trump' 'Seen and Unseen': Kamala Harris's word of the day is'hope' Is Spielberg's new UFO film more fact than fiction?
Robust and Diverse Multi-Agent Learning via Rational Policy Gradient
Adversarial optimization algorithms that explicitly search for flaws in agents' policies have been successfully applied to finding robust and diverse policies in multi-agent settings. However, the success of adversarial optimization has been largely limited to zero-sum settings because its naive application in cooperative settings leads to a critical failure mode: agents are irrationally incentivized to selfsabotage, blocking the completion of tasks and halting further learning. To address this, we introduce Rationality-preserving Policy Optimization (RPO), a formalism for adversarial optimization that avoids self-sabotage by ensuring agents remain rational--that is, their policies are optimal with respect to some possible partner policy. To solve RPO, we develop Rational Policy Gradient (RPG), which trains agents to maximize their own reward in a modified version of the original game in which we use opponent shaping techniques to optimize the adversarial objective. RPG enables us to extend a variety of existing adversarial optimization algorithms that, no longer subject to the limitations of self-sabotage, can find adversarial examples, improve robustness and adaptability, and learn diverse policies. We empirically validate that our approach achieves strong performance in several popular cooperative and general-sum environments.
Minnesota bans crypto ATMs after scam surge
This material may not be published, broadcast, rewritten, or redistributed. Quotes displayed in real-time or delayed by at least 15 minutes. Market data provided by Factset . Powered and implemented by FactSet Digital Solutions . Mutual Fund and ETF data provided by LSEG . China's brain chip breakthrough raises big questions Should you change your phone number after a hack? McDonald's AI drive-thru may take your next order The Father's Day gift that protects your dad from scammers New Air Force One'flying palace' gifted by Qatar unveiled for President Trump Kevin O'Leary warns U.S. must accelerate data center growth to keep pace with China in AI race Americans need protection against'warrantless surveillance': Rep Chip Roy Spencer Pratt's use of AI to boost campaign sparks debate China approves world's first commercial brain chip Crypto kiosks helped scammers turn fear into fast cash.
AI makes Pompeii victim's final moments look shockingly real
AI makes Pompeii victim's final moments look shockingly real The archaeologists behind the video believe the man covered his head with a bowl to protect himself from volcanic debris. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. This victim of the 79 CE eruption of Mount Vesuvius was discovered in the Pompeii archaeological area near Naples in southern Italy. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy .
Urgent warning to all Outlook users about scam hijacking email accounts... here's how to stay safe
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Surge in scams as fraudsters use AI to target people
Cases of fraud in the UK have surged with criminals using AI to manipulate people and even marrying victims of romance scams to steal more money. More than four million cases in which money was lost were reported last year - the equivalent of nearly eight on average every minute, according to new figures. The total has increased by more than one million in two years, with almost £1.3bn The enormous scale of the problem could only be tackled if tech companies stepped up monitoring and security of their platforms, the banking trade body said. Banks said fraud posed a national security threat given the impact on victims and the huge sums stolen by organised criminals.
Fraud Type Decomposition and the Observation-Mechanism Taxonomy:Class-Specific Detection Limits in Payment Networks
Fraud detection in payment networks relies on labels generated through heterogeneous and imperfect observation processes, yet existing approaches treat fraud as a homogeneous binary variable. We show that this assumption is structurally incorrect and leads to provable inefficiency. We introduce an observation-mechanism taxonomy that partitions fraud into five classes, each defined by a distinct censorship and labeling pipeline. We prove that estimating fraud rates separately by class and aggregating strictly dominates pooled estimation, with the efficiency gap characterized as a Jensen penalty arising from heterogeneous observation rates. For each class, we derive the binding theoretical constraint on detection, including endogenous label corruption, structural non-observability, and feature non-informativeness. These results establish that fraud detection is fundamentally a collection of distinct estimation problems, each governed by its own observation structure and detection limit.
Scammers Are Using Your Real Hotel Reservations to Trick You With Spear-Phishing Attacks
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.
This Pompeii victim was likely a doctor trying to help survivors
Technology is humanizing one of the many victims of the Mount Vesuvius eruption in 79 CE. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Plaster casts can fill hollows in the ground left behind by bodies buried during a volcanic eruption. Breakthroughs, discoveries, and DIY tips sent six days a week. The Garden of Fugitives is one of Pompeii's most haunting sites .