Radio remains a pervasive medium for mass information dissemination, with AM/FM stations reaching more Americans than either smartphone-based social networking or live television. Increasingly, radio broadcasts are also streamed online and accessed over the Internet. We present WavePulse, a framework that records, documents, and analyzes radio content in real-time. While our framework is generally applicable, we showcase the efficacy of WavePulse in a collaborative project with a team of political scientists focusing on the 2024 Presidential Elections. We use WavePulse to monitor livestreams of 396 news radio stations over a period of three months, processing close to 500,000 hours of audio streams. These streams were converted into time-stamped, diarized transcripts and analyzed to track answer key political science questions at both the national and state levels. Our analysis revealed how local issues interacted with national trends, providing insights into information flow. Our results demonstrate WavePulse's efficacy in capturing and analyzing content from radio livestreams sourced from the Web. Code and dataset can be accessed at \url{https://wave-pulse.io}.

Human experts write summaries using different techniques, including extracting a sentence from the document and rewriting it, or fusing various information from the document to abstract it. These techniques are flexible and thus difficult to be imitated by any single method. To address this issue, we propose an adaptive model, GEMINI, that integrates a rewriter and a generator to mimic the sentence rewriting and abstracting techniques, respectively. GEMINI adaptively chooses to rewrite a specific document sentence or generate a summary sentence from scratch. Experiments demonstrate that our adaptive approach outperforms the pure abstractive and rewriting baselines on three benchmark datasets, achieving the best results on WikiHow. Interestingly, empirical results show that the human summary styles of summary sentences are consistently predictable given their context. We release our code and model at \url{https://github.com/baoguangsheng/gemini}.

Michael Williams' wife pleaded with him to remember their fishing trips with the grandchildren, how he used to braid her hair, anything to jar him back to his world outside the concrete walls of Cook County Jail. His three daily calls to her had become a lifeline, but when they dwindled to two, then one, then only a few a week, the 65-year-old Williams felt he couldn't go on. He made plans to take his life with a stash of pills he had stockpiled in his dormitory. Williams was jailed last August, accused of killing a young man from the neighborhood who asked him for a ride during a night of unrest over police brutality in May. But the key evidence against Williams didn't come from an eyewitness or an informant; it came from a clip of noiseless security video showing a car driving through an intersection, and a loud bang picked up by a network of surveillance microphones. Prosecutors said technology powered by a secret algorithm that analyzed noises detected by the sensors indicated Williams shot and killed the man. "I kept trying to figure out, how can they get away with using the technology like that against me?" said Williams, speaking publicly for the first time about his ordeal. Williams sat behind bars for nearly a year before a judge dismissed the case against him last month at the request of prosecutors, who said they had insufficient evidence.

As digital giants swallow a growing share of shoppers' spending, thousands of stores have closed and tens of thousands of workers have lost their jobs. Belinda Duperre, who sold jewelry at Sam's Club in Fall River, Mass., was one. In early 2016, the struggling store closed. But Ms. Duperre, a lifelong resident of the once-thriving factory town an hour south of Boston, went from victim of the digital revolution to beneficiary. Inc. announced plans to hire 500 full-time workers for a new 1.2-million square foot fulfillment center on the outskirts of town.

Thousands of people showed up Wednesday for a chance to pack and ship products to Amazon customers, as the e-commerce company held a giant job fair at nearly a dozen U.S. warehouses. Although the wages offered will make it hard for some to make ends meet, many of the candidates were excited by the prospect of health insurance and other benefits, as well as advancement opportunities. It's common for Amazon to ramp up its shipping center staff in August to prepare for holiday shopping. But the magnitude of its current hiring spree underscores Amazon's growth when traditional retailers are closing stores -- and blaming Amazon for a shift to buying goods online. Amazon said it received "a record-breaking 20,000 applications" and hired thousands of people on the spot, and will hire more in the coming days.

Amazon.com will hire thousands of new full-time employees on-the-spot to fill 50,000 available fulfillment network positions during its first "Amazon Jobs Day," August 2, 2017. Amazon is holding a giant job fair Wednesday, Aug. 2, and plans to make thousands of job offers on the spot at nearly a dozen U.S. warehouses. Though it's common for Amazon to ramp up its shipping center staff in August to prepare for holiday shopping, the magnitude of the hiring spree underscores Amazon's growth when traditional retailers are closing stores -- and blaming Amazon for a shift to buying goods online. Amazon planned to hire thousands of people on the spot. Nearly 40,000 of the 50,000 packing, sorting and shipping jobs at Amazon will be full time.