AI expert Marva Bailer explains how, even though there are currently laws in place, the average person has more access than ever to create deepfakes of celebrities. "Elvis" director Baz Luhrmann is not afraid of artificial intelligence so much as he worries about the lack of regulation over the technology. In an interview with Sky News, Luhrmann admitted he was not "personally frightened of AI, but having worked with a very, very smart robot named Ai-Da, and having formed a relationship with her, she would tell you, and I would agree, we are way behind in terms of governance of AI." Earlier this year, Luhrmann partnered with Bombay Sapphire on its "Saw This Made This" campaign, which used an AI robot artist, named Ai-Da, to create art pieces live at exhibitions in London and New York inspired by submissions from human creators. Luhrmann also praised the writers and actors strikes that took place over the summer and fall, with the use of AI being a major issue in negotiations. WHAT IS ARTIFICIAL INTELLIGENCE (AI)?

US Central Command, known as Centcom said that, on Sunday morning, the USS Carney detected an anti-ship ballistic missile exploding near the Unity Explorer, a Bahamian-flagged, UK-owned and operated cargo ship.

Yemen's Houthi movement says it has targeted two Israeli ships with an armed drone and a naval missile, reports a spokesperson for the group's military. The spokesperson said the two ships, Unity Explorer and Number Nine, were targeted after they rejected warnings from the group's navy, the Reuters news agency reported on Sunday. British maritime security company Ambrey said a bulk carrier ship had been hit by at least two drones while sailing in the Red Sea. Another container ship reportedly suffered damage from a drone attack about 101km (63 miles) northwest of the northern Yemeni port of Hodeida, it added. The Pentagon also said a US warship and multiple commercial ships came under attack in the Red Sea, potentially marking a major escalation in a series of maritime attacks since the Israel-Hamas war began on October 7. "We are aware of reports regarding attacks on the USS Carney and commercial vessels in the Red Sea and will provide information as it becomes available," the Pentagon said.

NSC Communications Coordinator John Kirby responds to progressive pushback against U.S. aid to Israel on'FOX News Sunday.' The Pentagon said Sunday a U.S. warship and multiple commercial vessels are under attack in the Red Sea. The development signifies a serious escalation in a series of maritime attacks in the Middle East linked to the Israel-Hamas war. "We're aware of reports regarding attacks on the USS Carney and commercial vessels in the Red Sea and will provide information as it becomes available, later," Pentagon spokesman told Fox News, confirming reports of an attack on a U.S. warship in the Red Sea. The Pentagon initially told the Associated Press, "We're aware of reports regarding attacks on the USS Carney and commercial vessels in the Red Sea and will provide information as it becomes available." USS Carney is a Arleigh Burke-class guided-missile destroyer that has been shooting down drones and cruise missiles in recent weeks launched by Iran-backed Houthi rebels, who claimed credit for Sunday's attack.

NSC Communications Coordinator John Kirby responds to progressive pushback against U.S. aid to Israel on'FOX News Sunday.' Three commercial vessels were attacked in the Red Sea on Sunday, prompting a U.S. warship to shoot down multiple unmanned aerial vehicles (UAV) headed toward them. The development could signify a serious escalation in a series of maritime attacks in the Middle East linked to the Israel-Hamas war. "Today, there were four attacks against three separate commercial vessels operating in international waters in the southern Red Sea," a statement by U.S. Central Command (CENTCOM) explained. "These three vessels are connected to 14 separate nations." The USS Carney was in the southern Red Sea, just north of the Bab al-Mandab Strait, when it shot down three Houthi drones heading in its direction, a U.S. official told Fox News, adding that the action was taken in self-defense. The drones were launched from Houthi-controlled areas of Yemen, the official claimed.

It results in more factual rationales and reduced hallucination in generation. Specifically, CoK consists of three stages: reasoning preparation, dynamic knowledge adapting, and answer consolidation. Given a knowledge-intensive question, CoK first prepares several preliminary rationales and answers while identifying the relevant knowledge domains. If there is no majority consensus among the answers from samples, CoK corrects the rationales step by step by adapting knowledge from the identified domains. These corrected rationales can plausibly serve as a better foundation for the final answer consolidation. Unlike prior studies that primarily use unstructured data, CoK also leverages structured knowledge sources such as Wikidata and tables that provide more reliable factual information. To access both unstructured and structured knowledge sources in the dynamic knowledge adapting stage, we propose an adaptive query generator that allows the generation of queries for various types of query languages, including SPARQL, SQL, and natural sentences. Moreover, to minimize error propagation between rationales, CoK corrects the rationales progressively using preceding corrected rationales to generate and correct subsequent rationales. Extensive experiments show that CoK consistently improves the performance of LLMs on knowledge-intensive tasks across different domains. In recent years, large language models (LLMs) such as ChatGPT (OpenAI, 2023) have demonstrated impressive language generation capabilities (Cheng et al., 2023; Ding et al., 2023). However, one major challenge of LLMs lies in hallucination, which is their tendency to confidently generate plausible but factually incorrect texts (Ji et al., 2023). As shown in Figure 1, given a question, "What year was the Argentine actor who directed El Tio Disparate born?" which requires factual knowledge to answer, the most advanced LLMs often provide an incorrect answer. While LLMs have the remarkable capability to recall information from their training data, effectively updating or controlling the factual knowledge within these models remains challenging (Luo et al., 2023). A promising direction to address hallucination in generation is to augment the LLMs with external knowledge (Mialon et al., 2023). These methods involve incorporating LLMs with a retrieval system, which seeks to utilize external factual knowledge to guide the generation process. Instead of relying solely on the internal training knowledge of LLMs, these methods can fetch relevant infor-Equal contribution. Xingxuan Li, Yew Ken Chia, and Bosheng Ding are under the Joint Ph.D. Program between Alibaba and their corresponding universities. We will make our code and data publicly available.

Historical records of climate fields are often sparse due to missing measurements, especially before the introduction of large-scale satellite missions. Several statistical and model-based methods have been introduced to fill gaps and reconstruct historical records. Here, we employ a recently introduced deep-learning approach based on Fourier convolutions, trained on numerical climate model output, to reconstruct historical climate fields. Using this approach we are able to realistically reconstruct large and irregular areas of missing data, as well as reconstruct known historical events such as strong El Ni\~no and La Ni\~na with very little given information. Our method outperforms the widely used statistical kriging method as well as other recent machine learning approaches. The model generalizes to higher resolutions than the ones it was trained on and can be used on a variety of climate fields. Moreover, it allows inpainting of masks never seen before during the model training.

Climate hazards can cause major disasters when they occur simultaneously as compound hazards. To understand the distribution of climate risk and inform adaptation policies, scientists need to simulate a large number of physically realistic and spatially coherent events. Current methods are limited by computational constraints and the probabilistic spatial distribution of compound events is not given sufficient attention. The bottleneck in current approaches lies in modelling the dependence structure between variables, as inference on parametric models suffers from the curse of dimensionality. Generative adversarial networks (GANs) are well-suited to such a problem due to their ability to implicitly learn the distribution of data in high-dimensional settings. We employ a GAN to model the dependence structure for daily maximum wind speed, significant wave height, and total precipitation over the Bay of Bengal, combining this with traditional extreme value theory for controlled extrapolation of the tails. Once trained, the model can be used to efficiently generate thousands of realistic compound hazard events, which can inform climate risk assessments for climate adaptation and disaster preparedness. The method developed is flexible and transferable to other multivariate and spatial climate datasets.

As the deployment of computer vision technology becomes increasingly common in science, the need for explanations of the system and its output has become a focus of great concern. Driven by the pressing need for interpretable models in science, we propose the use of Explainable Boosting Machines (EBMs) for scientific image data. Inspired by an important application underpinning the development of quantum technologies, we apply EBMs to cold-atom soliton image data tabularized using Gabor Wavelet Transform-based techniques that preserve the spatial structure of the data. In doing so, we demonstrate the use of EBMs for image data for the first time and show that our approach provides explanations that are consistent with human intuition about the data.

Former USS Cole commander Kirk Lippold discusses how released Hamas hostages are arriving at an Israeli hospital on'Your World.' The U.S. Navy destroyer USS Carney has shot down an Iranian-made Houthi drone launched from Yemen, a military official confirms to Fox News. There was no damage to the Carney or any injuries to the U.S. personnel onboard. The warship had been sailing near the Bab el-Mandeb Strait at the time of the attack. The USS Carney shot down 15 drones and four cruise missiles fired from Yemen in the northern Red Sea last month during a nine-hour span, using its SM-2 surface-to-air missiles.