A long-running feud between Elon Musk and Sam Altman spilled out into the open this week as the AI billionaire heavyweights publicly fought over their rival companies. The latest round in the battle between the X CEO and the CEO of OpenAI began when Musk claimed that Apple had been favoring Altman's AI app over his own in the Apple Store rankings. "Apple is behaving in a manner that makes it impossible for any AI company besides OpenAI to reach #1 in the App Store, which is an unequivocal antitrust violation," Musk said on X on Monday evening. "xAI will take immediate legal action," he added, referring to the AI company he leads. "Hey @Apple App Store, why do you refuse to put either X or Grok in your'Must Have' section when X is the #1 news app in the world and Grok is #5 among all apps?" he asked.

With more than 39 TB of publicly available engineering data, DrivAerNet++ fills a significant gap in available resources, providing high-quality, diverse data to enhance model training, promote generalization, and accelerate automotive design processes.

Artificial intelligence (AI) is advancing quickly and is being adopted in most industries. Using AI to draft an email message or check your grammar is typically not a cause for concern, but using it to make decisions that affect people's lives is another matter. When constitutional rights are involved, as in the justice system, transparency is paramount. During the Biden-Harris administration, Executive Order 14110 directed agencies to develop guidelines for acceptable uses and regulation of AI. Some of these uses, like summarizing and notetaking, will occur across the government.

Experts have warned of a'frightening expansion' of'Orwellian' technology as the government expands the use of live facial recognition across the country. Ten vans equipped with facial recognition cameras will be deployed across seven police forces – Greater Manchester, West Yorkshire, Bedfordshire, Surrey, Sussex, Thames Valley and Hampshire. The Home Office maintains that this technology will only be used to catch'high–harm' offenders with rules to ensure'safeguards and oversight'. According to the government, the technology has already been used to make 580 arrests in London over the last year, including 52 registered sex offenders. However, rights groups have raised concerns that the unprecedented rollout of this surveillance technology risks becoming overly intrusive.

YouTube is one of the most popular online platforms in the U.S. among all age groups. But not all content on the video-sharing site is appropriate for all ages. While the platform, like most, has restrictions on certain content, such as violence and nudity, for users under 18, these safeguards have in the past been easy for young users to circumvent by entering an older birthdate on their account. But now, the company is rolling out an artificial intelligence-powered tool to estimate a user's age based on their activity on the platform "and then use that signal, regardless of the birthday in the account, to deliver our age-appropriate product experiences and protection," said James Beser, director of product management at YouTube Youth, in blog post last month. The technology, according to Beser, has been used in other markets "for some time" and will begin being tested in the U.S. on Wednesday before a wider rollout.

AI risks entrenching racism and sexism in Australia, the human rights commissioner has warned, amid internal Labor debate about how to respond to the emerging technology. Lorraine Finlay says the pursuit of productivity gains from AI should not come at the expense of discrimination if the technology is not properly regulated. Finlay's comments follow Labor senator Michelle Ananda-Rajah breaking ranks to call for all Australian data to be "freed" to tech companies to prevent AI perpetuating overseas biases and reflect Australian life and culture. Ananda-Rajah is opposed to a dedicated AI act but believes content creators should be paid for their work. Media and arts groups have warned of "rampant theft" of intellectual property if big tech companies can take their content to train AI models.

Google's dominance of the search engine and online advertising market has come under intense scrutiny, with the technology giant embroiled in years of legal wrangling as part of two antitrust cases. A US federal judge is expected to issue a ruling this month that could see Google being ordered to break up its search business. The company has said it would appeal such a ruling, saying the idea of spinning off Chrome was an "unprecedented proposal" that would harm consumers and security. A spokesman for Perplexity told the BBC that its bid marks an "important commitment to the open web, user choice, and continuity for everyone who has chosen Chrome." As part of the proposed takeover, Perplexity said it would continue to have Google as the default search engine within Chrome, though users could adjust their settings.

Big Brother Watch is bringing a legal challenge against the Met Police's use of the technology, alongside Shaun Thompson, who was wrongly identified by an LFR camera. Rebecca Vincent, interim director of Big Brother Watch, said: "Police have interpreted the absence of any legislative basis authorising the use of this intrusive technology as carte blanche to continue to roll it out unfettered, despite the fact that a crucial judicial review on the matter is pending. "The Home Office must scrap its plans to roll out further live facial recognition capacity until robust legislative safeguards are established." Charlie Whelton, policy and campaigns officer at Liberty, said: "It's welcome news that the government will finally develop a statutory framework on the use of facial recognition, but this should be in place before more facial recognition technology is rolled out. "There's no reasonable excuse to be putting even more cameras on our streets before the public have had their say and legislation is brought in to protect all of us." The government says officers using the LFR vans will need to follow the College of Policing's guidance on the technology and the Surveillance Camera Code of Practice.

The rapid emergence of large language models (LLMs) has raised urgent questions across the modern workforce about this new technology's strengths, weaknesses, and capabilities. For privacy professionals, the question is whether these AI systems can provide reliable support on regulatory compliance, privacy program management, and AI governance. In this study, we evaluate ten leading open and closed LLMs, including models from OpenAI, Anthropic, Google DeepMind, Meta, and DeepSeek, by benchmarking their performance on industry-standard certification exams: CIPP/US, CIPM, CIPT, and AIGP from the International Association of Privacy Professionals (IAPP). Each model was tested using official sample exams in a closed-book setting and compared to IAPP's passing thresholds. Our findings show that several frontier models such as Gemini 2.5 Pro and OpenAI's GPT-5 consistently achieve scores exceeding the standards for professional human certification - demonstrating substantial expertise in privacy law, technical controls, and AI governance. The results highlight both the strengths and domain-specific gaps of current LLMs and offer practical insights for privacy officers, compliance leads, and technologists assessing the readiness of AI tools for high-stakes data governance roles. This paper provides an overview for professionals navigating the intersection of AI advancement and regulatory risk and establishes a machine benchmark based on human-centric evaluations.

Natural disasters such as hurricanes and wildfires increasingly introduce unusual disturbance on economic activities, which are especially likely to reshape commercial land use pattern given their sensitive to customer visitation. However, current modeling approaches are limited in capturing such complex interplay between human activities and commercial land use change under and following disturbances. Such interactions have been more effectively captured in current resilient urban planning theories. This study designs and calibrates a Urban Theory-Informed Spatio-Temporal Attention Model for Predicting Post-Disaster Commercial Land Use Change (Urban-STA4CLC) to predict both the yearly decline and expansion of commercial land use at census block level under cumulative impact of disasters on human activities over two years. Guided by urban theories, Urban-STA4CLC integrates both spatial and temporal attention mechanisms with three theory-informed modules. Resilience theory guides a disaster-aware temporal attention module that captures visitation dynamics. Spatial economic theory informs a multi-relational spatial attention module for inter-block representation. Diffusion theory contributes a regularization term that constrains land use transitions. The model performs significantly better than non-theoretical baselines in predicting commercial land use change under the scenario of recurrent hurricanes, with around 19% improvement in F1 score (0.8763). The effectiveness of the theory-guided modules was further validated through ablation studies. The research demonstrates that embedding urban theory into commercial land use modeling models may substantially enhance the capacity to capture its gains and losses. These advances in commercial land use modeling contribute to land use research that accounts for cumulative impacts of recurrent disasters and shifts in economic activity patterns.