This is just the beginning of a challenging yet rewarding journey we will have with Seedify Incubations. Today we’re ready to share with you our first four incubation projects, each one of them with its own features and innovation for the Blockchain and NFT Industry that will bring a lot of value to the SFUND holders and to the NFT Gamers community in general. As we have established our position as one of the lead Launchpads in the Industry, it’s time to push the boundaries even further and enter the incubation with full power. Trained over time, the algorithm could learn to detect a baseball and determine whether it was within a set strike zone, calling perfect balls and strikes each time.įittingly, baseball already has a sacrosanct strike zone: “That area over home plate the upper limit of which is a horizontal line at the midpoint between the top of the shoulders and the top of the uniform pants, and the lower level is a line at the hollow beneath the kneecap,” according to the Major League Baseball rulebook.As you have been following up in the past week, we have announced a lot of innovations and new areas of Seedify we will focus on from now on. Called YOLO (short for “you only look once”), the algorithm uses neural networks to deliver real-time object detection. Newer technology, including ultra-high speed cameras, is also used to calculate the point at which a baseball crossed the plate.Īn algorithm that’s already in use in some autonomous vehicles could provide an even more exact answer, Esslinger says. Radar systems placed strategically throughout baseball stadiums can triangulate the exact position of a ball as it crosses home plate, giving anyone watching at home an instant read on whether it was a ball or a strike. Photo by Matthew Modoono/Northeastern University Kevin Esslinger is a doctoral candidate in the Khoury College of Computer Science studying artificial intelligence at Northeastern. But largely, it’s unlikely fans even noticed a difference.Īnd, says Kevin Esslinger, a doctoral candidate studying artificial intelligence and computer science, the technology to calculate exact balls and strikes is already in use-look no further than the superimposed strike zone box on any major television network-just not by the umpires. The software allowed higher and lower strikes than a human would have normally called-a fact acknowledged by the players during the game who shook their heads at a couple of pitches, the Washington Post reported. If he didn’t like the call, he could simply overrule it, and call the pitch as he saw it. The software called balls and strikes, and communicated them to deBrauwere through his earpiece. In 2019, it became the first American professional baseball league to let a robot umpire call balls and strikes, and it’s unlikely fans even knew.ĭuring an All-Star game, home plate umpire Brian deBrauwere wore a Bluetooth-connected earpiece, connected to an iPhone in his back pocket that was connected to a software program in the press box. Take, for example, baseball’s Atlantic League, an independent circuit with teams on the East Coast and Texas. Lots of leagues are already experimenting with “AI augmentation” when it comes to refereeing. Photo by Alyssa Stone/Northeastern Universityīut perhaps the debate doesn’t have to be binary, Lebowitz says. Dan Lebowitz is the executive director of the Center for the Study of Sport in Society at Northeastern.
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