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2018's Biggest Moments In AI (Artificial Intelligence)
Well, let's take a look: AI-Driven Medical Diagnosis: “In 2018, we saw artificial intelligence leveraged extensively in healthcare to help medical professionals accelerate and improve diagnoses by combing through mountains of data within 3D and 2D medical imagery,” said Sujai Hajela, who is the president, cofounder and CEO of Mist.
“In most cases, the humans did not even realize they were speaking to a computer.” Translation: Microsoft leveraged AI to translate sentences of news articles from Chinese to English with the “same quality and accuracy as a person.” According Xuedong Huang, who is one of the company’s technical fellows: “Hitting human parity in a machine translation task is a dream that all of us have had.
“For the first time, conversational search -- the process of interacting with a technology and getting responses in the form of a natural conversation -- serves as a conduit for contextually relevant and personalized interactions,” said Nicolas Dessaigne, who is the co-founder and CEO of Algolia.
Now with workers and technology working hand-in-hand, manufacturers can monitor and adjust in real-time.” Recognition: This year Pindrop was granted the first ever patent on utilizing an end-to-end Deep Neural network for speaker recognition.
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Artificial Intelligence in NBA Basketball
The use of machine learning and AI in basketball represents only the latest chapter in the analytics revolution that has been transforming basketball over the last 15 or so years.
Tune into almost any basketball game or sports talk show today, and you'll likely hear terms like offensive efficiency and PER (player efficiency rating) rolling off the tongues of analysts as easily as 'layup.'
The task was to translate the tracking data into something searchable and digestible, and one major goal, in particular, was to identify specific actions like passes and common plays such as the pick-and-roll, a nuanced maneuver involving the ball-handler, a teammate and two defenders.
The resulting software can then go through all of the tracking data, identify and label every player and play, and create a database of searchable, annotated and animated diagrams of moving dots that represent each player.
What they want is contextual information that tells a more complete story of the game, information that requires increasingly detailed data -- numbers like the arc of a shot.
Marty's talking computer -- and steadily improved versions of it -- would follow her through high school and college, helping to train her teammates and even during her recovery from injury.
In 2001, her father, Alan, had turned his invention into a company called Noah Basketball, named so because in the Bible, Noah had the perfect “ark.” The newest version, which includes tools to analyze your data and is dubbed Noahlytics, is now used by half of NBA teams, dozens of top college programs, and hundreds of individuals around the country, said John Carter, the company's current CEO.
Their system consists of cameras attached 10 feet above the backboard that don't just track the ball's arc, but also its depth and left-right position as it approaches the rim.
The system collects data on every shot, adding to a database of more than 150 million shots already recorded during practice sessions around the country.
Using deep learning, a type of machine learning that mimics how a brain learns, the system can identify the particular type of shot taken -- moves that have varying degrees of difficulty that affect the likelihood that the ball goes in.
Rachel Marty, who recently earned a doctorate in bioinformatics, analyzed data from 22 million shots collected by Noah's system to find a more efficient way to evaluate a shooter's skill.
Since not every player has the opportunity to take thousands of shots, Marty trained an algorithm to recognize the characteristics of a made shot and predict a player's skill based on only a few attempts.
Stats' Lucey, and Panna Felsen, a graduate student at the University of California, Berkeley, have also analyzed how shooters' body positions -- whether the feet were set, or whether they were off balance, for example -- affects a 3-point shot.
In a case study with Stephen Curry, they quantified what most fans could already guess: He's in constant motion and shoots a lot of off-balance threes, which makes his uncanny accuracy even more remarkable.
An emerging market for these real-time probabilities is sports gambling, which is now legal in most states thanks to a Supreme Court ruling in May that struck down a ban on commercial sports betting.
But when she visits her parents' home, she tries to take the time to roll out the old shot-tracking system, just like those evenings she used to spend shooting with her dad.
- On 15. januar 2021
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