Beverly Hills police drone captures slip and fall. The affluent 90210 zip code is often associated with a hit television show that aired in the 1990s. It is also where an alleged burglar fell off a ladder into a pool. The Beverly Hills Police Department (BHPD) shared drone footage of the incident from Jan. 6 on Instagram with the caption, "Burglar caught in 4K. The video first shows a man crawling out of a home's window before being seen atop a tall ladder over what appears to be a garage.

Comedian Adam Corolla discusses how self-driving cars are causing chaos in San Francisco on'Jesse Watters Primetime.' A former interim mayor of San Francisco announced Tuesday he's running for his previous job, joining a competitive field of candidates who say the city has crumbled under the watch of Mayor London Breed, who is up for reelection this year. Mark Farrell served as interim mayor of San Francisco from January to July 2018, when Breed was elected to finish the term of Ed Lee, who died in office. The lawyer and former city supervisor said he had not planned to return to politics but feels he has the right skills to turn San Francisco around. "It is really painful to watch the city you love and you grew up in maligned across the globe," he said in an interview with The Associated Press.

Unlike previous techniques, which could identify DNA from, say, a single organism, the method also collects the swirling cloud of other genetic material that surrounds it. It can serve as a surveillance tool, offering researchers a means of detecting the seemingly undetectable. By sampling eDNA, or mixtures of genetic material in water, soil, ice cores, cotton swabs, or practically any environment imaginable, even thin air, it is now possible to search for a specific organism or assemble a snapshot of all the organisms in a given place. It offers a thrilling -- and potentially chilling -- way to collect information about organisms, including humans, as they go about their everyday business. The world of AI has produced some depressing headlines recently, from the Taylor Swift AI-generated porn scandal to the proliferation of political deepfakes as election campaigns get underway in many countries around the world.

European politicians in two key committees have approved new rules to regulate artificial intelligence (AI) ahead of a landmark vote that could pave the way for the world's first legislation on the technology. On Tuesday, two committees in the European Parliament – on civil liberties and consumer protection – overwhelmingly endorsed the provisional legislation to ensure that AI complies with the protection of "fundamental rights". A vote in the legislative assembly is scheduled for April. The AI Act will aim to set guardrails on a technology being used in several industries, ranging from banking and cars to electronic products and airlines, as well as for security and police purposes. "At the same time, it aims to boost innovation and establishing Europe as a leader in the AI field," the parliament said in a statement.

On February 6, Meta said it was going to label AI-generated images on Facebook, Instagram, and Threads. When someone uses Meta's AI tools to create images, the company will add visible markers to the image, as well as invisible watermarks and metadata in the image file. The company says its standards are in line with best practices laid out by the Partnership on AI, an AI research nonprofit. Big Tech is also throwing its weight behind a promising technical standard that could add a "nutrition label" to images, video, and audio. Called C2PA, it's an open-source internet protocol that relies on cryptography to encode details about the origins of a piece of content, or what technologists refer to as "provenance" information.

Tech companies have been under pressure from regulators, AI researchers and political activists to rein in the spread of fake election content. The new agreement is similar to a voluntary pledge the same companies, plus several others, signed in July after a meeting at the White House, where they committed to try to identify and label fake AI content on their sites. In the new accord, the companies also commit to educating users on deceptive AI content and being transparent about their efforts to identify deepfakes.

Independent presidential candidate Robert F. Kennedy, Jr. tells'Jesse Watters Primetime' it may be Biden's time to retire. Independent presidential candidate Robert F. Kennedy, Jr., was asked whether he believes President Biden should step aside at the end of his first term after a special counsel's report found him to be an "elderly man with poor memory." Kennedy told Fox News if he were in Biden's position, he would hope someone in his own family would politely suggest he step away from the political limelight if his mental acuity is as diminished as special counsel Robert Hur suggested. "I think anybody can make up their mind about [Biden's situation] as well as I can. I hope that if he has the kind of cognitive challenges that the special counsel indicated he has, and if I were in that position, a member of my family or staff would approach me and assist me in gently stepping down," Kennedy said on "Jesse Watters Primetime."

The advent of generative artificial intelligence and the widespread adoption of it in society engendered intensive debates about its ethical implications and risks. These risks often differ from those associated with traditional discriminative machine learning. To synthesize the recent discourse and map its normative concepts, we conducted a scoping review on the ethics of generative artificial intelligence, including especially large language models and text-to-image models. Our analysis provides a taxonomy of 378 normative issues in 19 topic areas and ranks them according to their prevalence in the literature. The study offers a comprehensive overview for scholars, practitioners, or policymakers, condensing the ethical debates surrounding fairness, safety, harmful content, hallucinations, privacy, interaction risks, security, alignment, societal impacts, and others. We discuss the results, evaluate imbalances in the literature, and explore unsubstantiated risk scenarios.

How can firms optimally negotiate bilateral contracts with each other in a financial network? Every firm seeks to maximize the utility it gains from its portfolio of contracts. We focus on mean-variance utilities, where each firm has its own beliefs about the expected returns of the contracts and the covariances between them (Markowitz, J. Finance 7(11), 1952). Instead of revealing these beliefs, a firm may adopt a different negotiating position, seeking better contract terms. We formulate a contract negotiation process by which such strategic behavior leads to a network of contracts. In our formulation, any subset of firms can be strategic. The negotiating positions of these firms can form Nash equilibria, where each firm's position is optimal given the others' positions. We give a polynomial-time algorithm to find the Nash equilibria, if they exist, and certify their nonexistence otherwise. We explore the implications of such equilibria on several model networks. These illustrate that firms' utilities can be sensitive to their negotiating position. We then propose trade deadlines as a mechanism to reduce the need for strategic behavior. At the deadline, each firm can unilaterally cancel some or all of its contracts, for a penalty. In our model networks, we show that trade deadlines can reduce the loss of utility from being honest. We empirically verify our insights using data on international trade between 46 large economies.

To create early warning capabilities for upcoming Space Weather disturbances, we have selected a dataset of 61 emerging active regions, which allows us to identify characteristic features in the evolution of acoustic power density to predict continuum intensity emergence. For our study, we have utilized Doppler shift and continuum intensity observations from the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO). The local tracking of 30.66 x 30.66-degree patches in the vicinity of active regions allowed us to trace the evolution of active regions starting from the pre-emergence state. We have developed a machine learning model to capture the acoustic power flux density variations associated with upcoming magnetic flux emergence. The trained Long Short-Term Memory (LSTM) model is able to predict 5 hours ahead whether, in a given area of the solar surface, continuum intensity values will decrease. The performed study allows us to investigate the potential of the machine learning approach to predict the emergence of active regions using acoustic power maps as input.