This article excerpt is from eFinancialCareers. Forget all the hype around artificial intelligence (A.I.): If you’ve really got the skills that Silicon Valley and Wall Street need, you could haul in millions of dollars a year. “Right now, A.I. is an elitist sport – there are very few people who know how to practice it,” said Tom Eck, the CTO of industry platforms at IBM and a software developer who has been involved in A.I. as far back as the early ’90s. “The top-tier A.I. researchers are getting paid the salaries of NFL quarterbacks, which tells you the demand and the perceived value.” While Eck, speaking at the Markets Media’s Summer Trading event in New York, didn’t specify whether he meant starting quarterbacks or their backups, he did say that the best A.I. researchers are earning as much as the highest paid position in the National Football League. For reference, there are 31 quarterbacks who will make more than $5 million this year, and the highest-paid QB in the league – the Oakland Raiders’ Derek Carr, fresh off signing a new contract last month – will get a cool $25 million this year. He’ll earn a minimum of $70 million over three years and could get up to $125 million over five. Financial services, healthcare and advertising are the three biggest adopters of A.I. at this stage, according to Eck. A.I. is the process of imbuing a machine or a piece of software with the capabilities that we consider human cognition, basically making a machine act like a human brain. If we take neurons and model them mathematically as a simple formula with nonlinear components, we can create an interesting rules-based system using “if this, then that” algorithms capable of pattern recognition, Eck said. But it’s still at the early stage. “A.I. is statistics-based – here’s a set of data; take the data, extrapolate and give me a prediction of the most likely thing to happen,” he says. “That’s about model-generating, given a set of data. “The machine learning system has to come up with a generator that would spit out that dataset, working backwards from the data to a mathematical model, and then it is no longer limited to the data you’ve observed – A.I. can predict what tomorrow’s equity prices will be.” For more on artificial intelligence and salaries, as well as explanations of deep learning and cognitive computing, check out the article on eFinancialCareers. It was originally written by Dan Butcher. A.I. Specialists Can Earn as Much as NFL Players
This article excerpt is from eFinancialCareers. Forget all the hype around artificial intelligence (A.I.): If you’ve really got the skills that Silicon Valley and Wall Street need, you could haul in millions of dollars a year. “Right now, A.I. is an elitist sport – there are very few people who know how to practice it,” said Tom Eck, the CTO of industry platforms at IBM and a software developer who has been involved in A.I. as far back as the early ’90s. “The top-tier A.I. researchers are getting paid the salaries of NFL quarterbacks, which tells you the demand and the perceived value.” While Eck, speaking at the Markets Media’s Summer Trading event in New York, didn’t specify whether he meant starting quarterbacks or their backups, he did say that the best A.I. researchers are earning as much as the highest paid position in the National Football League. For reference, there are 31 quarterbacks who will make more than $5 million this year, and the highest-paid QB in the league – the Oakland Raiders’ Derek Carr, fresh off signing a new contract last month – will get a cool $25 million this year. He’ll earn a minimum of $70 million over three years and could get up to $125 million over five. Financial services, healthcare and advertising are the three biggest adopters of A.I. at this stage, according to Eck. A.I. is the process of imbuing a machine or a piece of software with the capabilities that we consider human cognition, basically making a machine act like a human brain. If we take neurons and model them mathematically as a simple formula with nonlinear components, we can create an interesting rules-based system using “if this, then that” algorithms capable of pattern recognition, Eck said. But it’s still at the early stage. “A.I. is statistics-based – here’s a set of data; take the data, extrapolate and give me a prediction of the most likely thing to happen,” he says. “That’s about model-generating, given a set of data. “The machine learning system has to come up with a generator that would spit out that dataset, working backwards from the data to a mathematical model, and then it is no longer limited to the data you’ve observed – A.I. can predict what tomorrow’s equity prices will be.” For more on artificial intelligence and salaries, as well as explanations of deep learning and cognitive computing, check out the article on eFinancialCareers. It was originally written by Dan Butcher. 
