Artificial intelligence is not only increasingly used in business and administration contexts, but a race for its regulation is also underway, with the EU spearheading the efforts. Contrary to existing literature, this article suggests, however, that the most far-reaching and effective EU rules for AI applications in the digital economy will not be contained in the proposed AI Act - but have just been enacted in the Digital Markets Act. We analyze the impact of the DMA and related EU acts on AI models and their underlying data across four key areas: disclosure requirements; the regulation of AI training data; access rules; and the regime for fair rankings. The paper demonstrates that fairness, in the sense of the DMA, goes beyond traditionally protected categories of non-discrimination law on which scholarship at the intersection of AI and law has so far largely focused on. Rather, we draw on competition law and the FRAND criteria known from intellectual property law to interpret and refine the DMA provisions on fair rankings. Moreover, we show how, based on CJEU jurisprudence, a coherent interpretation of the concept of non-discrimination in both traditional non-discrimination and competition law may be found. The final part sketches specific proposals for a comprehensive framework of transparency, access, and fairness under the DMA and beyond.

A Ukrainian strike destroyed a missile complex in Russian-occupied Crimea on Wednesday, August 23, Ukraine's military intelligence agency said. Russia and Ukraine launched drone strikes against each other Wednesday morning, each looking to score a major win in a fight that continues to drag on with little progress or end in sight. Ukrainian intelligence claimed to have destroyed a Russian S-400 surface-to-air missile defense system in Crimea, while Russia struck grain facilities in Odesa overnight Tuesday. The S-400 system shows another instance of Ukraine's plan to strike at Russian assets, even behind the front line. Ukraine's intelligence agency GUR claimed on its Telegram channel that Russia has a "limited number" of sophisticated systems left and that this loss strikes a "painful blow" to their forces.

Today, India's Chandrayaan-3 became the first spacecraft to successfully land near the lunar south pole, and India became the fourth country to make a soft landing anywhere on lunar soil, following the former Soviet Union, the United States, and China. The robotic vehicle touched down at 8:33 Eastern time, nearly six weeks after its launch. The craft includes a four-legged lander and a small rover to study the lunar regolith and look for signs of water ice during a two-week mission. On August 20, the craft malfunctioned and appears to have crashed while preparing for a landing planned for the next day. Roscosmos, Russia's space agency, intended to deploy Luna-25 for a year-long mission near the Boguslavsky impact crater, where its eight scientific instruments would also have examined properties of the regolith and pockets of water ice.

Unlike rivals such as China and Russia, India has aligned itself with the United States by signing an agreement on space exploration, known as the Artemis Accords, a legal framework that governs activity in space. So far, nearly 30 countries have signed, allowing them to partner with the U.S. on space missions and mandating that they adhere to a set of rules, such as publicly sharing scientific discoveries and creating "safety zones" where nations could work undisturbed on the lunar surface.

PANTS ON FIRE – Biden's Maui controversy takes turn for the worst as past comments resurface. ON SECOND THOUGHT – 'Trump Employee 4' retracts'false testimony' given after changing lawyers. STAGE IS SET – Sign up now to watch the first Republican presidential primary debate tonight at 9PM ET on FoxNews.com. GOING'ALL IN' – RNC launches'bank your vote' ad blitz ahead of debate to push Republicans to vote early in 2024 elections. 'VISION TO REVERSE AMERICA'S DECLINE' – DeSantis to make case at debate for his'proven conservative record,' top aide says.

Neil Sahota discussed the potential impact of artificial intelligence on future elections and people's ability to make informed decisions when choosing political candidates Artificial intelligence (AI) generated deepfakes are likely to have a "massive" impact on voters in future elections and there isn't much that can be done right now to stop it, according to an AI advisor for the United Nations (UN). Speaking with Fox News Digital, Neil Sahota said his sources warned the growing use of deepfake advertisements may very well be "the greatest threat to democracy." "A lot of people--and I think those in the media too, are calling the 2024 election'the deepfake election' that is probably going to be marred by tons and tons of deepfakes," Sahota said. "Not much can be done right now to stop any of that." While the UN and various other organizations and corporations are working quickly to roll out software that can detect deepfakes, Sahota noted that common verification tools, such as watermarks, are relatively easy to circumvent in their current iterations.

Russian air defence systems have taken down three unmanned aerial vehicles (UAV) that tried to attack Moscow, the latest raid on Russia's capital by combat drones that authorities have accused Ukraine of launching. Russia's defence ministry said one drone was jammed electronically and crashed into a building in central Moscow early on Wednesday morning, and two more were shot down by air defence systems outside the capital. Moscow's Mayor Sergei Sobyanin said on the Telegram messaging app that one downed drone had hit a building that was under construction in central Moscow, and another was shot down in a district to the west of the city. The second UAV hit a building under construction in the City," Sobyanin said on Telegram. Russia's defence ministry said that the third drone was shot down in the Khimki district of Moscow.

General Oleksandr Tarnavskyi, the deputy commander of Ukrainian forces in the south, said Ukraine's troops had gained a footing in the southeastern village of Robotyne and were organising the evacuation of civilians. Oleksandr Prokudin, the governor of Ukraine's Kherson region, said an elderly woman was killed and a 55-year-old man injured in Russian air attacks. A drone raid was reported in Moscow, forcing a temporary halt to air traffic at Vnukovo, Sheremetyevo and Domodedovo airports. City Mayor Sergei Sobyanin said Russian air defence systems shot down the two drones west of the capital and blamed Ukraine. Russia's Air Force said it scrambled two jets against two drones flying near the Crimean Peninsula, which it annexed in 2014.

Landslide susceptibility assessment (LSA) is of paramount importance in mitigating landslide risks. Recently, there has been a surge in the utilization of data-driven methods for predicting landslide susceptibility due to the growing availability of aerial and satellite data. Nonetheless, the rapid oscillations within the landslide-inducing environment (LIE), primarily due to significant changes in external triggers such as rainfall, pose difficulties for contemporary data-driven LSA methodologies to accommodate LIEs over diverse timespans. This study presents dynamic landslide susceptibility mapping that simply employs multiple predictive models for annual LSA. In practice, this will inevitably encounter small sample problems due to the limited number of landslide samples in certain years. Another concern arises owing to the majority of the existing LSA approaches train black-box models to fit distinct datasets, yet often failing in generalization and providing comprehensive explanations concerning the interactions between input features and predictions. Accordingly, we proposed to meta-learn representations with fast adaptation ability using a few samples and gradient updates; and apply SHAP for each model interpretation and landslide feature permutation. Additionally, we applied MT-InSAR for LSA result enhancement and validation. The chosen study area is Lantau Island, Hong Kong, where we conducted a comprehensive dynamic LSA spanning from 1992 to 2019. The model interpretation results demonstrate that the primary factors responsible for triggering landslides in Lantau Island are terrain slope and extreme rainfall. The results also indicate that the variation in landslide causes can be primarily attributed to extreme rainfall events, which result from global climate change, and the implementation of the Landslip Prevention and Mitigation Programme (LPMitP) by the Hong Kong government.

The rapid spread of false information and persistent manipulation attacks on online social networks (OSNs), often for political, ideological, or financial gain, has affected the openness of OSNs. While researchers from various disciplines have investigated different manipulation-triggering elements of OSNs (such as understanding information diffusion on OSNs or detecting automated behavior of accounts), these works have not been consolidated to present a comprehensive overview of the interconnections among these elements. Notably, user psychology, the prevalence of bots, and their tactics in relation to false information detection have been overlooked in previous research. To address this research gap, this paper synthesizes insights from various disciplines to provide a comprehensive analysis of the manipulation landscape. By integrating the primary elements of social media manipulation (SMM), including false information, bots, and malicious campaigns, we extensively examine each SMM element. Through a systematic investigation of prior research, we identify commonalities, highlight existing gaps, and extract valuable insights in the field. Our findings underscore the urgent need for interdisciplinary research to effectively combat social media manipulations, and our systematization can guide future research efforts and assist OSN providers in ensuring the safety and integrity of their platforms.