Oral assessments, more security checks and speedier marking are all on the cards as generative artificial intelligence (AI) could transform exams for the next generation of students. As the 2025 exam season drew to a close with GCSE students picking up their results on Thursday, after mostly sitting traditional pen and paper exams, AI is already changing the landscape. Exam preparation is undergoing a revolution, with students increasingly creating personal AI tutors, available around the clock to generate learning materials to suit individual needs that potentially lead to better results. "Using AI can give a student a much better understanding of a subject because they can ask those questions they wouldn't ask in class, or at odd hours, without being judged," said Dr Andrew Rogoyski of the Surrey Institute for People-Centred AI. "It really took off this summer," said Sandra Leaton Gray, a professor of education futures at University College London's Institute of Education. "So they're able to talk to it about the marking frameworks that are in use and upload those, and then they're able to do sample answers on their own. And then they're able to say to the AI: 'How would you improve the answer?' It's like having a tireless tutor."

Integrating malicious AI models6 into software supply chains presents a significant and emerging threat to cybersecurity. The attackers aim to embed malicious AI models in software components and widely used tools, thereby infiltrating systems at a foundational level. Once integrated, the malicious AI models execute embedded unauthorized code, which performs actions such as exfiltrating sensitive data, manipulating data integrity, or enabling unauthorized access to critical systems. Compromised development tools, tampered libraries, and pre-trained models are the primary methods of introducing malicious AI models into the software supply chain. Developers often rely on libraries and frameworks to import pre-trained AI models to expedite software development.

PU learning refers to the classification problem in which only part of positive samples are labeled. Existing PU learning methods treat unlabeled samples equally. However, in many real tasks, from common sense or domain knowledge, some unlabeled samples are more likely to be positive than others. In this paper, we propose soft label PU learning, in which unlabeled data are assigned soft labels according to their probabilities of being positive. Considering that the ground truth of T PR, FPR, and AUC are unknown, we then design PU counterparts of these metrics to evaluate the performances of soft label PU learning methods within validation data. We show that these new designed PU metrics are good substitutes for the real metrics. After that, a method that optimizes such metrics is proposed. Experiments on public datasets and real datasets for anti-cheat services from Tencent games demonstrate the effectiveness of our proposed method.

Due to the necessary security for the airport and flight, passengers are required to have strict security check before getting aboard. However, there are frequent complaints of wasting huge amount of time while waiting for the security check. This paper presents a potential solution aimed at optimizing gate setup procedures specifically tailored for Chicago OHare International Airport. By referring to queueing theory and performing Monte Carlo simulations, we propose an approach to significantly diminish the average waiting time to a more manageable level. Additionally, our study meticulously examines and identifies the influential factors contributing to this optimization, providing a comprehensive understanding of their impact.

Google has warned that numerous Gmail users will soon be wiped from the platform in an effort to tighten its security. The tech giant announced that thousands of abandoned email accounts could be deleted from December amid hacking and scam fears. Users who rely on compromised passwords will be among those deleted, in addition to those whose accounts have gone without regular security checks for two years. This includes the failure to set up two-factor verification, according to Google. In a blog post, it said: 'People want the products and services they use online to be safe and secure.

Artificial Intelligence used to be a fancy word in the past, a system that was going to change the world overnight. Well, it is everywhere these days but the pace for that proposed change is rather evolutionary, slowly taking over manual operations and processes. The biggest playground of AI is in Data Science, including data extraction and processing. But, it is less about diddling fancy terms and more about the result; the urge to reach meaningful conclusions in the least possible time. The advent and maturation of digital services, such as banking, shopping, etc, called for better processes to ensure the identity of users both during onboarding and during the completion of a transaction.

Never mind airport security, artificial intelligence (AI) may also be rooting through your luggage in the near future at Incheon International Airport. Incheon International Airport Corporation said Wednesday it will incorporate AI into its security systems in a bid to improve accuracy in screening passenger luggage for prohibited items. The airport has already started working on the project to develop an AI-based X-ray screening system to be tested in the second half of next year. Instead of the existing system that relies on X-ray scanning, manual image checking by security officers and a final physical check, artificial intelligence will crosscheck the X-ray scan and the analysis will be available to officers along with the X-ray image. The first-stage AI scan is expected to complement and improve the accuracy of the security check as an officer will continue to be responsible for the final call to physically inspect luggage.

Automated facial recognition systems from Japanese biz NEC will be used on staffers and athletes at the Tokyo 2020 Olympics. The technology – which is not without its detractors in the UK – was demonstrated at a media event in the city today. It will require athletes, staff, volunteers and the press to submit their photographs before the games start. These will then be linked up to IC chips in their passes and combined with scanners on entry to allow them access to more than 40 facilities. Tsuyoshi Iwashita, head of security for the games, said the aim was to reduce pressure on entry points and shorten queueing time for this group of people.

The US tax authority – the Internal Revenue Service – is looking at how AI can secure and protect taxpayers' data held on its servers. It recently filed a request for information aimed at experts that can help guide the IRS into possibly developing a platform that uses machine learning to sniff out and react to threats. The cybersecurity division working for the Cybersecurity Cloud Solution Program is hoping that the information will help them identify potential solutions based on current capabilities. "The Internal Revenue Service's (IRS) Cybersecurity Division has a business need for an Artificial Intelligent (AI) machined-based analytical platform to proactively detect and respond to cyber- and insider-related threats," it said in the request. "The IRS intends to use the results of this RFI to assist in the assessment of on-going industry efforts within the identified focus areas. The finding will also help to shape the path forward for potential acquisitions to include determination of contractual mechanisms to potentially pursue capabilities."

Long lines and lengthy waits for round after round of security checks are di rigueur at major events in China such as the annual meetings of its legislature. That may change in the near future with the use of facial recognition to red-flag people for further screening while allowing others to proceed, speeding up the process of letting thousands of delegates, journalists and staff into the Great Hall of the People, according to Baidu CEO Robin Li Yanhong, whose company is testing such a system at airports. "The measures to verify identification, such as the tight security checks during the Two Sessions, have brought inconvenience to people's lives," said Li, who is a delegate to the Chinese People's Political Consultative Conference. "Most of the time, people's identification is done manually, which I think will be completely unnecessary in the future," he told mainland Chinese media ahead of the event. Li's comments highlight the growing use of facial recognition in security applications in China, part of the nation's wider push to lead the world in artificial intelligence and a desire by the central government to improve public safety through surveillance of citizens.