The United States space agency says the study of UFOs will require a science-based approach and new techniques as NASA appointed a director to lead research on objects that the US government calls unidentified anomalous phenomena (UAP). The agency has found no evidence that UAP have extraterrestrial origins, NASA Administrator Bill Nelson said on Thursday after it released a years-long study. In a 33-page report, an independent team commissioned by NASA cautioned that the negative perception surrounding UFOs – short for unidentified flying objects – poses an obstacle to collecting data. But the panel said NASA's involvement should help reduce the stigma around the issue, and it recommended the agency increase its efforts to gather information on UAP and play a larger role in helping the Pentagon detect them. On my travels, one of the first questions I often get is about these sightings, and much of that fascination is due to the unknown nature of it," Nelson said.

Fox News White House correspondent Peter Doocy provides details on the latest revelations from the Hunter Biden investigation. Hunter Biden filed a lawsuit against former President Donald Trump aide Garrett Ziegler on Wednesday, alleging that Ziegler had violated federal computer laws by hacking into the now-infamous laptop that was left in a Delaware repair shop in 2019. The lawsuit, filed in Los Angeles, accuses Ziegler and his company -- Marco Polo USA -- and 10 unidentified associates of spreading "tens of thousands of emails, thousands of photos, and dozens of videos and recordings" that were considered "pornographic" on the laptop. Ziegler's company website claims to be a nonprofit research group "exposing corruption & blackmail." The website has several sections pertaining to Biden's laptop, including his emails, text messages, phone calls and financial data that culminates into a massive "online searchable database."

Seventy-six years after the infamous Roswell incident, when a high-altitude balloon--or something--crashed in southeastern New Mexico, the US National Aeronautics and Space Administration (NASA) has now officially weighed in on UFO sightings. Don't get too excited: They haven't proven, or disproven, the existence of aliens. Instead, the report released today by the agency's independent study team describes how NASA should assess new reports of "unidentified anomalous phenomena" (UAP), a term that federal agencies use in place of UFOs (unidentified flying objects). It stresses that the agency should make use of machine learning and artificial intelligence as analytical tools, but that first it needs higher quality data to analyze. It's in our DNA," said NASA administrator Bill Nelson, speaking at a press conference this morning. "The top takeaway from the study is that there is a lot more to learn.

In the film "2001: A Space Odyssey," an astronaut travels through a seeming tunnel of light. Earlier this summer, Artechouse, an organization producing immersive, technology-based art, started offering a science-backed version of a similar trip at its New York venue. The show, titled "Beyond the Light," is a looping twenty-six-minute journey through space and other realms inspired by images from the James Webb Space Telescope (J.W.S.T.). Artechouse began talks with NASA about a show in 2018, and started pulling this one together earlier this year, after the first images captured by J.W.S.T. were released to the public last July. More than sixteen thousand years ago, cave explorers in what's now Lascaux, France, painted animals that are believed to represent the constellations.

Alice Globus, head of Nanotronics, said AI could minimize the damage done by recent malware attacks on hospitals and the Colonial Pipeline shutdown in 2021. Germany has invested heavily into what officials say will help them find the future of combat through an artificial intelligence (AI) virtual training area some have dubbed a military "metaverse." "We compete with the big ones in the industry," GhostPlay project manager Gary Schaal, a professor at Helmut Schmidt University in Hamburg, wrote in a press release. "Our [Unique Selling Point]: agility and the ability to quickly show results." Developer 21strategies pulled together a mix of start-ups and defense academics to create the virtual battlefield GhostPlay, which allows developers to test out different weapons and systems inside a risk-free environment.

The United States military has resumed operations in Niger, flying drones and other aircraft out of airbases in the country more than a month after a coup halted activities, the head of Air Forces in Europe and Air Forces Africa said. Since the July coup that removed President Mohamed Bazoum, the approximately 1,100 US soldiers deployed in the West African country have been confined to their military bases. General James Hecker said on Wednesday that negotiations with the military rulers of Niger resulted in some intelligence and surveillance missions resuming. "For a while, we weren't doing any missions on the bases, they pretty much closed down the airfields," Hecker told reporters at the annual Air and Space Forces Association convention. "Through the diplomatic process, we are now doing, I wouldn't say 100 percent of the missions that we were doing before, but we're doing a large amount of missions that we're doing before," he said.

Last December, I had an abortion. Most unwanted pregnancies set a panic-timer ticking, but I was almost counting down the seconds until I had to catch a flight from London, where I live, to Texas, where I grew up, and where the provision of abortion care was recently made a felony. You bleed for a while after most abortions, and I was still bleeding when I boarded the plane home for Christmas. Going to Texas so soon after the procedure made me consider where the record of my abortion – my health data – would end up. When I phoned an abortion clinic in late November to book an appointment, one of the first questions staff asked was: "May we share a record of your treatment with your GP?" It's not just that a complete health record helps my GP treat me. My Texan parents, both scientists, taught me that sharing information with organisations like the NHS can help it plan services and research ways to improve care. I've joined clinical studies in the past. But I also help run a legal campaign group, Foxglove, that takes action against the government and tech companies when they infringe people's rights. In a series of cases about NHS data since the start of the pandemic, we have defended people's right to a say about who sees their medical information. This work has exposed me to worrying details about how our medical data can be used, including the Home Office practice of tracking migrants using their health records. For decades the government has required GPs to store patients' records in a standardised way: as well as longhand notes, every interaction with a GP is saved on a computer database in a simple, consistent code.

The manifestation and effect of bias in news reporting have been central topics in the social sciences for decades, and have received increasing attention in the NLP community recently. While NLP can help to scale up analyses or contribute automatic procedures to investigate the impact of biased news in society, we argue that methodologies that are currently dominant fall short of addressing the complex questions and effects addressed in theoretical media studies. In this survey paper, we review social science approaches and draw a comparison with typical task formulations, methods, and evaluation metrics used in the analysis of media bias in NLP. We discuss open questions and suggest possible directions to close identified gaps between theory and predictive models, and their evaluation. Figure 1: Two articles about the same event written These include model transparency, considering from different political ideologies. Example taken from document-external information, and AllSides.com.

From power grids to transportation and logistics systems, autonomous systems play a central, and often safety-critical, role in modern life. Even as these systems grow more complex and ubiquitous, we have already observed failures in autonomous systems like autonomous vehicles and power networks resulting in the loss of human life [1]. Given this context, it is important that we be able to verify the safety of autonomous systems prior to deployment; for instance, by understanding the different ways in which a system might fail and proposing repair strategies. Human designers often use their knowledge of likely failure modes to guide the design process; indeed, systematically assessing the risks of different failures and developing repair strategies is an important part of the systems engineering process [2]. However, as autonomous systems grow more complex, it becomes increasingly difficult for human engineers to manually predict likely failures. In this paper, we propose an automated framework for predicting, and then repairing, failure modes in complex autonomous systems. Our effort builds on a large body of work on testing and verification of autonomous systems, many of which focus on identifying failure modes or adversarial examples [3, 4, 5, 6, 7, 8], but we identify two major gaps in the state of the art. First, many existing methods [4, 5, 9, 7] use techniques like gradient descent to search locally for failure modes; however, in practice we are more interested in characterizing the distribution of potential failures, which requires a global perspective. Some methods exist that address this issue by taking a probabilistic approach to sample from an (unknown) distribution of failure modes [6, 10].

Summarization is an important application of large language models (LLMs). Most previous evaluation of summarization models has focused on their performance in content selection, grammaticality and coherence. However, it is well known that LLMs reproduce and reinforce harmful social biases. This raises the question: Do these biases affect model outputs in a relatively constrained setting like summarization? To help answer this question, we first motivate and introduce a number of definitions for biased behaviours in summarization models, along with practical measures to quantify them. Since we find biases inherent to the input document can confound our analysis, we additionally propose a method to generate input documents with carefully controlled demographic attributes. This allows us to sidestep this issue, while still working with somewhat realistic input documents. Finally, we apply our measures to summaries generated by both purpose-built summarization models and general purpose chat models. We find that content selection in single document summarization seems to be largely unaffected by bias, while hallucinations exhibit evidence of biases propagating to generated summaries.