How the data center boom plunged one small Pennsylvania town into chaos. Valley View Estates is set to be surrounded by data centers. Get your news from a source that's not owned and controlled by oligarchs. "I don't like to see anyone upset," said Nick Farris of Provident Real Estate Advisors. He was sitting in the front of a crowd of roughly 150 inside Valley View High School's auditorium in Archbald, a town of about 7,500, huddled between two mountain ranges in Pennsylvania's Lackawanna Valley. Farris was there to represent the developer for Project Scott, one of many data center campuses coming to town. "I think that this is the best data center site in this area of the country, by far." The audience had been fairly quiet, bundled in thick coats against the late January cold. But as Farris spoke about data centers as a boon for communities, they began to laugh, drawing a rebuke from town officials. "What about the children?" someone shouted from the crowd. The children were watching from the walls; long banners of Valley View Performing Arts students hanging around the auditorium like championship pennants. Project Scott and four other data facilities will sit just a few thousand feet from the middle and high schools. He was referring to Lockheed Martin's 350,000-square-foot Missiles and Fire Control facility directly next to the high school, parts of which are highly contaminated . "That sucks too!" another attendee yelled back.

The recent growth in renewable energy development in the United States has been accompanied by a simultaneous surge in renewable energy siting ordinances. These zoning laws play a critical role in dictating the placement of wind and solar resources that are critical for achieving low-carbon energy futures. In this context, efficient access to and management of siting ordinance data becomes imperative. The National Renewable Energy Laboratory (NREL) recently introduced a public wind and solar siting database to fill this need. This paper presents a method for harnessing Large Language Models (LLMs) to automate the extraction of these siting ordinances from legal documents, enabling this database to maintain accurate up-to-date information in the rapidly changing energy policy landscape. A novel contribution of this research is the integration of a decision tree framework with LLMs. Our results show that this approach is 85 to 90% accurate with outputs that can be used directly in downstream quantitative modeling. We discuss opportunities to use this work to support similar large-scale policy research in the energy sector. By unlocking new efficiencies in the extraction and analysis of legal documents using LLMs, this study enables a path forward for automated large-scale energy policy research.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. City lawmakers in Brazil have enacted what appears to be the nation's first legislation written entirely by artificial intelligence -- even if they didn't know it at the time. The experimental ordinance was passed in October in the southern city of Porto Alegre and city councilman Ramiro Rosário revealed this week that it was written by a chatbot, sparking objections and raising questions about the role of artificial intelligence in public policy. Rosário told The Associated Press that he asked OpenAI's chatbot ChatGPT to craft a proposal to prevent the city from charging taxpayers to replace water consumption meters if they are stolen.

Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on talented data scientists to help us develop and improve the models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers. DoorDash users use the DoorDash app in two modes: 1) to search for specific dishes and products, restaurants, grocery or convenience stores when they have something in mind; 2) to discover new dishes and products for delivery when they do not have something specific in mind. Both use cases are very important to our users. As a recommendation and search-focused Machine Learning Scientist you will have the opportunity to identify and prioritize machine learning investments to address both of these use cases.

Come help us build the world's most reliable on-demand, logistics engine for delivery! We are bringing on talented senior Data Scientists to help us develop and improve the models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers. We are looking for Economists, Physicists, Mathematicians, Statisticians, and senior quantitative researchers from all disciplines. You can read more about the types of Data Scientists we are looking for in our blog post Wanted: Data Scientists with Technical Brilliance AND Business Sense. As a senior Data Scientist, you will have the opportunity to leverage our robust data and machine learning infrastructure to develop inference and optimization models that impact millions of users across our three audiences and tackle our most challenging business problems.

Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on talented data scientists to help us develop and improve the models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers. As a support-focused Machine Learning Scientist you will have the opportunity to identify and prioritize machine learning investments across our support ecosystem. You will leverage our robust data and infrastructure to develop natural language processing and causal inference models that impact millions of users across our three audiences. You will partner with an engineering lead and product manager to set the strategy that moves the business metrics which help us grow our business.

Come help us build the world's most reliable on-demand, logistics engine for delivery! We are bringing on talented senior Data Scientists to help us develop and improve the ETA and Routing models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers. As a fundamental area of investment for DoorDash, ETA/Routing has among the coolest problems to solve at scale and creates a major impact on the company and its businesses. We are looking for Machine Learning Scientists, Economists, Physicists, Mathematicians, Statisticians, and Senior Quantitative Researchers from all disciplines. You can read more about the types of Data Scientists we are looking for in our blog post Wanted: Data Scientists with Technical Brilliance AND Business Sense.

Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on talented data scientists to help us develop and improve the models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers. As a support-focused Machine Learning Scientist you will have the opportunity to identify and prioritize machine learning investments across our support ecosystem. You will leverage our robust data and infrastructure to develop natural language processing and causal inference models that impact millions of users across our three audiences. You will partner with an engineering lead and product manager to set the strategy that moves the business metrics which help us grow our business.

Come help us build the world's most reliable on-demand, logistics engine for delivery! We are bringing on talented senior Data Scientists to help us develop and improve the supply lever models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers. Dasher pay and incentives is a fundamental area of investment for DoorDash to enable high-quality deliveries with maximum efficiency. The Supply-Demand DSML team has among the coolest problems to solve at scale, optimizing budget spend over multiple channels for delivering dasher incentives. We are looking for Operations Research Scientists, Economists, Mathematicians, Statisticians and other quantitative disciplines to drive system-wide changes and create major business impact.

Takamatsu – The Takamatsu District Court upheld Tuesday the constitutionality of a local ordinance placing limits on video game playing to combat gaming addiction, rejecting a lawsuit by a man and his mother who sought damages for alleged violations to their right to self-determination. Implemented in Kagawa Prefecture in April 2020, the ordinance set guidelines on when and for how long children would be allowed to play games. It was the first ordinance of its kind to be implemented in Japan. This could be due to a conflict with your ad-blocking or security software. Please add japantimes.co.jp and piano.io to your list of allowed sites. If this does not resolve the issue or you are unable to add the domains to your allowlist, please see this support page.