kantor
Soros DA put murder case on 'back burner' because it doesn't 'fit' liberal agenda: victim's family
Thomas Villarreal of the Austin Police Association discusses the police department's decision to implement artificial intelligence software in an effort to alleviate their officer shortage on "Fox & Friends Weekend." The family of a man killed in one of Austin, Texas' most infamous shootings blasted the local district attorney for putting the case on the "back burner" because it didn't fit his progressive agenda. Travis County District Attorney Jose Garza, funded by left-wing billionaire George Soros, is letting the nearly two-year case languish and is instead prioritizing cases that fit a political agenda, said Nick Kantor, whose brother, Doug, was killed in gang crossfire on June 12, 2021, that left more than a dozen innocent bystanders wounded. Doug Kantor, then 25 and working for Ford Motor Co., was visiting Austin from Michigan to celebrate earning his master's degree with friends when two rival gangs of teenagers from Killeen, Texas, opened fire on each other in the city's packed Sixth Street entertainment and nightlife hub. Doug Kantor, a New York native who had just bought a new home and was set to marry his high school sweetheart, was killed in the shooting and 13 other innocent bystanders were injured in the hail of bullets from both gangs that became the largest mass casualty incident in Austin in about a decade.
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- Law > Criminal Law (1.00)
- Law Enforcement & Public Safety > Crime Prevention & Enforcement (1.00)
To feed a growing population, scientists want to unleash AI on agriculture
Agriculture has come a long way in the past century. We produce more food than ever before -- but our current model is unsustainable, and as the world's population rapidly approaches the 8 billion mark, modern food production methods will need a radical transformation if they're going to keep up. But luckily, there's a range of new technologies that might make it possible. In this series, we'll explore some of the innovative new solutions that farmers, scientists, and entrepreneurs are working on to make sure that nobody goes hungry in our increasingly crowded world. Ever since American citizens' industrial age migration from the country to the city, urban areas have tended to be associated with cutting-edge technologies.
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Agriculture gets even smarter
The matter of growing enough food to feed the planet is a serious issue. Already, one in nine people lack sufficient sustenance, according to the United Nations--and the problem is only going to get worse. Mix a global population projected to reach 9 billion in 20 years, from 7.5 billion today, with drought and other effects of climate change, and a farm labor shortage in places like California, and there's a crisis in the making. Now a growing number of researchers and are turning to robotics to address the problem. Specifically, they're combining the sensing abilities of robots with data analysis made possible by artificial intelligence technology to improve farmers' ability to grow and manage their crops more intelligently.
- North America > United States > California (0.25)
- North America > United States > Washington (0.05)
- North America > United States > Texas (0.05)
Farm Researchers Are Using Military Face-Recognition Software to Inspect Grapes
The robot scans the stalks of sorghum, photographs them, looking for disease. It uses laser scanning to estimate their height and volume. And, every now and then, it reaches out a robotic arm, grabs hold of one of the stalks, and stabs it with a probe to measure the thickness of the rind. Welcome to the farm of the future. This little robo-farmer is just one project developed by FarmView, a multidisciplinary, multi-institution effort to put advanced technology to use on the farm.
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- Asia > India (0.05)
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How Sensors, Robotics And Artificial Intelligence Will Transform Agriculture
"Plant breeding is another interesting application we're pursuing, where robotically gathered plant phenotype data can be collected over much larger breeding experiments that current manual measurement techniques allow," said Kantor. "Machine learning tools can then combine the collected phenotype data with genetic and environmental data to help a breeders and geneticists better understand the relationships between genetics, environment, and plant performance." "This in turn accelerates the breeding process, allowing breeders to evaluate many more plants each season so that they can more quickly select for desirable traits such as yield or disease resistance," adds Kantor. Kantor says this kind of accelerated breeding program could have significant benefit in the developing world such as Subsaharan Africa. The FarmView initiative wants to develop inexpensive robotic systems that small- to medium-scale growers can afford to implement.
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