Artificial intelligence has for the first time predicted the reproductive behaviour of Yellowtail Kingfish by tracking their movements as part of new research revealed on #WorldOceanDay. The new study published in Movement Ecology used machine learning algorithms to identify and distinguish between behaviours including courtship, feeding, escape, chafing, and swimming to showcase how technology can offer greater understanding of marine life. The results revealed spawning behaviour of Yellowtail Kingfish within the Neptune Islands Group Marine Park and Thorny Passage Marine Park in South Australia. Researchers tagged captive Kingfish and filmed their behaviour in tanks to identify the acceleration signatures and applied artificial intelligence to identify behaviour in free-ranging fish. Flinders University PhD student, Thomas Clarke, in the College of Science & Engineering, says it's the first study to use machine learning to identify spawning behaviours in wild Kingfish and demonstrates how artificial intelligence can be used to better understand reproductive patterns.

The new study, published in Movement Ecology, used machine learning algorithms to identify and distinguish between behaviors including courtship, feeding, escape, chafing, and swimming to showcase how technology can offer greater understanding of marine life. The results revealed spawning behavior of yellowtail kingfish within the Neptune Islands Group Marine Park and Thorny Passage Marine Park in South Australia. Researchers tagged captive kingfish and filmed their behavior in tanks to identify the acceleration signatures and applied artificial intelligence to identify behavior in free-ranging fish. Flinders University Ph.D. student, Thomas Clarke, in the College of Science & Engineering, says it's the first study to use machine learning to identify spawning behaviors in wild kingfish and demonstrates how artificial intelligence can be used to better understand reproductive patterns. "Through direct observations of courtship and spawning behaviors, our findings provide the first study to predict natural reproduction of yellowtail kingfish, via the use of accelerometers and machine learning. The new study, published in Movement Ecology, used machine learning algorithms to identify and distinguish between behaviors including courtship, feeding, escape, chafing, and swimming to showcase how technology can offer greater understanding of marine life. The results revealed spawning behavior of yellowtail kingfish within the Neptune Islands Group Marine Park and Thorny Passage Marine Park in South Australia. Researchers tagged captive kingfish and filmed their behavior in tanks to identify the acceleration signatures and applied artificial intelligence to identify behavior in free-ranging fish. Flinders University Ph.D. student, Thomas Clarke, in the College of Science & Engineering, says it's the first study to use machine learning to identify spawning behaviors in wild kingfish and demonstrates how artificial intelligence can be used to better understand reproductive patterns. "Through direct observations of courtship and spawning behaviors, our findings provide the first study to predict natural reproduction of yellowtail kingfish, via the use of accelerometers and machine learning.

Artificial intelligence has for the first time predicted the reproductive behavior of yellowtail kingfish by tracking their movements as part of new research revealed on #WorldOceanDay. The new study, published in Movement Ecology, used machine learning algorithms to identify and distinguish between behaviors including courtship, feeding, escape, chafing, and swimming to showcase how technology can offer greater understanding of marine life. The results revealed spawning behavior of yellowtail kingfish within the Neptune Islands Group Marine Park and Thorny Passage Marine Park in South Australia. Researchers tagged captive kingfish and filmed their behavior in tanks to identify the acceleration signatures and applied artificial intelligence to identify behavior in free-ranging fish. Flinders University Ph.D. student, Thomas Clarke, in the College of Science & Engineering, says it's the first study to use machine learning to identify spawning behaviors in wild kingfish and demonstrates how artificial intelligence can be used to better understand reproductive patterns.

Self-driving cars have been given the green light to traverse well-trafficked roads in the Seaport and Fort Point areas of South Boston, according to a letter sent by the city last night. NuTonomy, which has driven more than 230 miles on public roads in Boston since the beginning of the year, will be allowed to drive its autonomous vehicles as far south as West First Street and to cross the Fort Point Channel to Dorchester Avenue. The company asked for and was granted approval to expand by Boston officials, under the terms of a testing agreement signed last year. "For autonomous vehicles to be able to deliver on the crash-reduction and network efficiency promises, we know that testing must gradually increase in complexity, while still maintaining safety as our paramount focus," Boston Transportation Commissioner Gina Fiandaca wrote in the approval letter. NuTonomy previously had been restricted to the Raymond L. Flynn Marine Park, a relatively quiet industrial and business area with no stoplights.