A little over thirty years ago, when he was in his mid-forties, my friend David Howorth lost all hearing in his left ear, a calamity known as single-sided deafness. "It happened literally overnight," he said. "My doctor told me, 'We really don't understand why.' " At the time, he was working as a litigator in the Portland, Oregon, office of a large law firm. His hearing loss had no impact on his job--"In a courtroom, you can get along fine with one ear"--but other parts of his life were upended. The brain pinpoints sound sources in part by analyzing minute differences between left-ear and right-ear arrival times, the same process that helps bats and owls find prey they can't see.

Fox News senior White House correspondent Jacqui Heinrich speaks with White House National Security Communications Adviser John Kirby about the mysterious drones in the Garden State on'The Story.' A U.S. Senator from Connecticut said the mysterious drones spotted recently flying over states in the mid-Atlantic region should be "shot down, if necessary." In an interview on Capitol Hill Thursday, Sen. Richard Blumenthal, D-Conn., said intelligence analysis is needed on the drones and the U.S. must act "more aggressively" against the sightings that have been reported. "We should be doing some very smart intelligence analysis and take them out of the skies, especially if they're flying over airports or military bases," the senator said. "They should be shot down, if necessary, because they're flying over sensitive areas."

Statistical agencies rely on sampling techniques to collect socio-demographic data crucial for policy-making and resource allocation. This paper shows that surveys of important societal relevance introduce sampling errors that unevenly impact group-level estimates, thereby compromising fairness in downstream decisions. To address these issues, this paper introduces an optimization approach modeled on real-world survey design processes, ensuring sampling costs are optimized while maintaining error margins within prescribed tolerances. Additionally, privacy-preserving methods used to determine sampling rates can further impact these fairness issues. The paper explores the impact of differential privacy on the statistics informing the sampling process, revealing a surprising effect: not only the expected negative effect from the addition of noise for differential privacy is negligible, but also this privacy noise can in fact reduce unfairness as it positively biases smaller counts. These findings are validated over an extensive analysis using datasets commonly applied in census statistics.

Everyone from Beyoncé to Cardi B to Bella Thorne has been talking about the adult content site OnlyFans. The latter two actually setting up their own pages on the platform to earn a little extra income. The site, in which creators invite users to subscribe to pages featuring their sexually explicit content, has exploded in the past few years. The number of OnlyFans creators worldwide has increased ten fold from 2019 to 2022 - from only 348,000 creators to 3,182,000. Much of the content is home-grown: 67 percent of the 1.9 billion net revenue generated on the platform in 2022 came from US content creators, Variety reported.

AI expert Marva Bailer explains how Will.i.am's app, FYI, powers his AI co-host for his radio show and why the platform has different capabilities than ChatGPT While artificial intelligence made headlines with ChatGPT, behind the scenes, the technology has quietly pervaded everyday life -- screening job resumes, rental apartment applications, and even determining medical care in some cases. While a number of AI systems have been found to discriminate, tipping the scales in favor of certain races, genders or incomes, there's scant government oversight. Lawmakers in at least seven states are taking big legislative swings to regulate bias in artificial intelligence, filling a void left by Congress' inaction. These proposals are some of the first steps in a decades-long discussion over balancing the benefits of this nebulous new technology with the widely documented risks. "AI does in fact affect every part of your life whether you know it or not," said Suresh Venkatasubramanian, a Brown University professor who co-authored the White House's Blueprint for an AI Bill of Rights.

Six years ago today, Joaquin Oliver was killed in a hallway outside his Florida classroom, one of 17 students and staff murdered in the worst high school shooting in the US. On Wednesday, lawmakers in Washington DC will hear his voice, recreated by artificial intelligence, in phone calls demanding to know why they've done nothing to tackle the plague of gun violence. "It's been six years and you've done nothing. Not a thing to stop all the shootings that have happened since," the message from Oliver, who was 17 when he died in the 2018 Valentine's Day's tragedy at Parkland's Marjory Stoneman Douglas high school, says. "I'm back today because my parents used AI to recreate my voice to call you. Other victims like me will be calling too, again and again, to demand action. How many calls will it take for you to care? How many dead voices will you hear before you finally listen?"

When auditing a redistricting plan, a persuasive method is to compare the plan with an ensemble of neutrally drawn redistricting plans. Ensembles are generated via algorithms that sample distributions on balanced graph partitions. To audit the partisan difference between the ensemble and a given plan, one must ensure that the non-partisan criteria are matched so that we may conclude that partisan differences come from bias rather than, for example, levels of compactness or differences in community preservation. Certain sampling algorithms allow one to explicitly state the policy-based probability distribution on plans, however, these algorithms have shown poor mixing times for large graphs (i.e. redistricting spaces) for all but a few specialized measures. In this work, we generate a multiscale parallel tempering approach that makes local moves at each scale. The local moves allow us to adopt a wide variety of policy-based measures. We examine our method in the state of Connecticut and succeed at achieving fast mixing on a policy-based distribution that has never before been sampled at this scale. Our algorithm shows promise to expand to a significantly wider class of measures that will (i) allow for more principled and situation-based comparisons and (ii) probe for the typical partisan impact that policy can have on redistricting.

Fox News correspondent Molly Line has more on the search to rescue the five individuals on the Titanic voyage on'Special Report.' BOSTON – Three new vessels arrived "on-scene" in the Atlantic Ocean Wednesday morning to join search and rescue efforts for the missing OceanGate Titan sub as the estimated oxygen supply on board continues to dwindle. The U.S. Coast Guard said the new vessels bring additional tools to scan the ocean floor as they race against the clock to save the five people onboard: OceanGate CEO Stockton Rush, British businessman Hamish Harding, father-and-son Shahzada and Suleman Dawood, who are members of one of Pakistan's wealthiest families, and Paul-Henry Nargeolet, a former French navy officer and leading Titanic expert. "The John Cabot has side-scanning sonar capabilities and is conducting search patterns alongside the Skandi Vinland and the Atlantic Merlin," the Coast Guard said. The John Cabot is a Canadian coast guard vessel, the Atlantic Merlin is a Canadian remotely operated vehicle (ROV), and the Skandi Vinland is a commercial ROV, authorities said.

Traffic state prediction in a transportation network is paramount for effective traffic operations and management, as well as informed user and system-level decision-making. However, long-term traffic prediction (beyond 30 minutes into the future) remains challenging in current research. In this work, we integrate the spatio-temporal dependencies in the transportation network from network modeling, together with the graph convolutional network (GCN) and graph attention network (GAT). To further tackle the dramatic computation and memory cost caused by the giant model size (i.e., number of weights) caused by multiple cascaded layers, we propose sparse training to mitigate the training cost, while preserving the prediction accuracy. It is a process of training using a fixed number of nonzero weights in each layer in each iteration. We consider the problem of long-term traffic speed forecasting for a real large-scale transportation network data from the California Department of Transportation (Caltrans) Performance Measurement System (PeMS). Experimental results show that the proposed GCN-STGT and GAT-STGT models achieve low prediction errors on short-, mid- and long-term prediction horizons, of 15, 30 and 45 minutes in duration, respectively. Using our sparse training, we could train from scratch with high sparsity (e.g., up to 90%), equivalent to 10 times floating point operations per second (FLOPs) reduction on computational cost using the same epochs as dense training, and arrive at a model with very small accuracy loss compared with the original dense training

The DIY art world hasn't been the same since the passing of Bob Ross (rest in peace in a forest of happy little trees, king), but AI art creation tool Dall-E at least offers an entertaining and quicker way to generate masterpieces that seem appropriate for the bizarro timeline we all now share. AI researcher Janelle Shane has made a hobby of prompting machine learning systems to engage in the 2022 equivalent of some very weird improv comedy. Her interactions with AI prompt plenty of hilarity -- including a charming set of Valentine's Day cards that almost work. Her latest bit is simply asking Dall-E to paint a picture of the most popular Halloween candies in each US state. The results are filled with lots of odd gibberish and overflowing with candy corn like any child's basket on Nov. 1 when all the good stuff from the previous night's haul has already been devoured. The first thing that becomes clear as Shane starts to work her way through all 50 states alphabetically is that Dall-E associates Halloween treats very strongly with candy corn, which is pretty fair given its abundance this time of year.