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}.

Walmart has transformed an ordinary grocery store into a 50,000-square-foot AI lab that tests new retail technologies in a real-world setting. The Intelligent Retail Lab is located in Levittown, New York, and is equipped with AI-powered sensors that keep track of the inventory and the freshness of the produce.

Nvidia has announced the launch of EGX Edge Supercomputing Platform designed to let organisations easily deploy the hardware and software necessary for high-performance, low-latency AI workloads. Instead of being deployed inside big data centres, an EGX deployment is designed to sit at the edge of the cloud which, Nvidia believes, makes it ideal for the next generation of use cases. "We've entered a new era, where billions of always-on IoT sensors will be connected by 5G and processed by AI," Jensen Huang, Nvidia founder and CEO, said at a keynote ahead of MWC Los Angeles earlier this week. "Its foundation requires a new class of highly secure, networked computers operated with ease from far away. "We've created the Nvidia EGX Edge Supercomputing Platform for this world, where computing moves beyond personal and beyond the cloud to operate at planetary scale," he added. The EGX stack includes an Nvidia driver, Kubernetes plug-in, Nvidia container runtime, and GPU monitoring tools, delivered through the Nvidia GPU Operator, which allows you to standardise and automate the deployment of all necessary components for provisioning GPU-enabled Kubernetes systems. Nvidia will certify hardware as'NGC Ready for Edge' that customers will be able to buy from partners such as Advantech, Altos Computing, ASRock RACK, Atos, Dell Technologies, Fujitsu, GIGABYTE, Hewlett Packard Enterprise, Lenovo, MiTAC, QCT, Supermicro, and TYAN. Nvidia says EGX is already being used by customers. At Walmart's Intelligent Retail Lab in Levittown, New York, for example, EGX enables real time processing of more than 1.6 terabytes of data generated each second to "automatically alert associates to restock shelves, open up new checkout lanes, retrieve shopping carts, and ensure product freshness in meat and produce departments." The EGX platform features software to support a wide range of applications, including Nvidia Metropolis, which can be used to power smart cities and build intelligent video analytics applications. The city of Las Vegas, for example, is using EGX to capture vehicle and pedestrian data to make its streets safer. San Francisco's Union Square Business Improvement District is using EGX to capture real-time pedestrian counts for local retailers. "We use our smartphones sporadically -- we type into it, or watch a movie now or then -- and frankly there are only seven and a half billion of us," Huang said. "In the case of sensors, it will be streaming all the time.

Walmart has opened a store in Levittown, N.Y. that is intended to showcase the power of artificial intelligence. The store, announced last week, is packed with video cameras, digital screens, and over 100 servers, making it appear more like a corporate data center than a discount retailer. All that machinery helps Walmart automatically track inventory so that it knows when toilet paper is running low or that milk needs restocking. The company's goal is to create "a glimpse into the future of retail," when computers rather than humans are expected to do a lot of retail's grunt work. Walmart's push into artificial intelligence highlights how retailers are increasingly adding data crunching to their brick and mortar stores.

Walmart isn't going to let Amazon's AI-powered stores go unanswered, although it's not exactly cloning the concept. The big-box chain has unveiled a publicly accessible concept store, the Intelligent Retail Lab (IRL for short), in Levittown, New York. The location uses computer vision and a vast array of cameras not to handle purchases, like Amazon Go does, but to help employees restock empty shelves and corral shopping carts. There are still checkout lines and floor staff, Walmart notes -- this is meant to minimize drudgery for workers and free them for tasks "humans can do best," like helping customers. The retailer is aware of the potential worries about privacy, and is determined to be as open about what's going on as possible.

Walmart this morning unveiled a new "store of the future" and test grounds for emerging technologies, including AI-enabled cameras and interactive displays. The store, a working concept called the Intelligent Retail Lab -- or "IRL" for short -- operates out of a Walmart Neighborhood Market in Levittown, N.Y. The store is open to customers and is one of Walmart's busiest Neighborhood Market stores, containing more than 30,000 items, the retailer says, which allows it to test out technology in a real-world environment. Similar to Amazon Go's convenience stores, the store has a suite of cameras mounted in the ceiling. But unlike Amazon Go, which is a grab-and-go store with smaller square footage, Walmart's IRL spans 50,000 square feet of retail space and is staffed by more than 100 employees.

Inside one of Walmart's busiest Neighborhood Market grocery stores, high resolution cameras suspended from the ceiling point to a table of bananas. They can tell how ripe the bananas are from their color. When a banana starts to bruise, the cameras send an alert to a worker. Normally, that task would have relied on the subjective assessment of a human, who likely doesn't have time to inspect every piece of fruit. Welcome to Walmart's Intelligent Retail Lab -- the retail giant's biggest attempt to digitize the physical store.

Walmart has a vision for its store of the future. Sure, it includes the kinds of things you'd expect -- clean floors, well-stocked aisles, and plenty of shopping carts at the entrance -- but the remarkable part of this vision is how the retail giant plans to monitor all of those things: using an omnipresent artificial intelligence. In 2017, Walmart launched Kepler, a team focused on reimagining the shopping experience using the latest tech innovations. A small Walmart in Levittown, New York serves as the team's testing laboratory. According to TechCrunch, Kepler's next project will be the creation of a Intelligent Retail Lab right inside the Levittown location.

Growth of the artificial intelligence market for healthcare is expected to reach $6.6 billion by 2021, according to Accenture, and the combined deployment of key clinical health AI applications could potentially create $150 billion in annual savings for the U.S. healthcare economy by 2026. In line with that growing trend, Rockville Centre, New York-based Precision Innovation Network, a physician-centric group purchasing organization focused on strengthening the patient-physician relationship by making it easier to practice, has tapped Splice Machine's big data and artificial intelligence data platform to develop its new Treatment Advisor application. The Treatment Advisor app will leverage multi-dimensional data – such as medical records, quantified measured performance obtained from digital devices, patient perspectives from questionnaires and demographic information – and use machine learning to help clinicians learn the trajectory of a disease and gather predictions for what may be the best treatment for each individual. It also will enable physicians to analyze the data to target disease-modifying therapies and better understand how a patient might feel – a patient-reported outcome – in the future. Splice Machine will allow Precision Innovation Network to apply machine learning to the data and gain insights that will help provide more precise medical treatment to patients, officials said.

Keith Kirkpatrick is principal of 4K Research & Consulting, LLC, based in Lynbrook, NY. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and full citation on the first page. Copyright for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or fee. Request permission to publish from permissions@acm.org or fax (212) 869-0481. The Digital Library is published by the Association for Computing Machinery.