Carnegie Mellon computer science PhD student Noam Brown (center) helps poker player Daniel McAulay get started during a match against an artificial intelligence program at Rivers Casino

Daniel McAulay is one of the most brilliant poker players in the world, but he has never played against an opponent quite like the one he just faced at Rivers Casino, in Pittsburgh.

“It was stunning,” said McAulay, who lost after 20 days of intense playing at the casino to an unusual opponent, a computer program called Libratus.

Libratus, an artificial intelligence (AI) program developed by Carnegie Mellon University, crushed McAulay, and three of the best human poker players in Heads-up, No-Limit Texas Hold’em, winning by $1.7 million in chips.

Carnegie Mellon has been a leader in AI research since Herbert Simon and Allen Newell invented the field in the 1950s. Tuomas Sandholm, a professor of computer science at Carnegie Mellon and Noam Brown, a PhD student in computer science, designed Libratus, Latin for “balance.”

Sandholm called the 20-day tournament a “once-in-a-lifetime event” for artificial intelligence, and another step toward applying AI to business negotiations, military strategy, medical-treatment planning, cyber-security and other areas. That a computer program can crush the world champions at poker, a complex game which requires a certain degree of intuition, is a coup for the fast-moving field of AI.
 

Hot Area of Computer Science
Technology giants, including Google, Facebook, Microsoft, Amazon and Baidu, are scrambling to push the bounds of artificial intelligence. These companies have been working on AI projects as eclectic as self-driving cars and intelligent personal assistants.

“Tech firms are battling for artificial intelligence talent, and they are filling their own research centers with big-name AI academics and aspiring PhD candidates,” said Rohan Bhargav who specialises in machine learning at Stanford University, and has himself had job offers from several tech firms.

Artificial intelligence is a broad academic field and includes techniques aimed at giving computers the ability to make decisions that a human might, based on data analysis. Machine learning, robotics and other subsets are a more-targeted discipline inside the broader AI field. 

Students wanting to enter the artificial intelligence field often wonder whether they should major in computer engineering or computer science.

“I would recommend computer engineering only if you’re interested in robotics. That will have a greater emphasis on the “EE” aspect of the field,” said AI educator Brittany Darby. 

“If you’re interested in the software side of AI, which constitutes programming the brains, whether or not it’s in a robot, then computer science is the way to go. Either way, you should be taking all the AI classes you can,” added Darby.
 

Hiring Rush
Universities have always had professors engaged in cutting-edge research in artificial intelligence. With AI gradually moving out of the realm of academia to more hard-nosed commercial applications, tech firms are plundering university robotics and machine learning departments, for the highest-flying faculty and students.

“I cannot even hold onto my grad students,” Pedro Domingos, a professor at the University of Washington who specializes in artificial intelligence, machine learning and data science, told The Economist.

“Companies are trying to hire them away before they graduate.” 

Facebook recently hired Yann LeCun, one of the world’s most prominent AI academics, from New York University (NYU). LeCun still works for NYU part time. Facebook partnered with NYU on a new center dedicated to data science, a key element of AI research. In keeping with the spirit of collaboration, Facebook scientists lecture at NYU, and Ph.D. students from NYU can apply for long-term internships at Facebook’s AI lab.

Experts in machine learning are in strong demand. Big tech firms use it in many activities, from basic tasks such as spam-filtering and better targeting of online advertisements, to futuristic endeavors such as self-driving cars or scanning images to identify disease. According to Glassdoor, a machine learning engineer can make $125,496 in New York City.

Similarly, an artificial intelligence research scientist can earn $143,000, while an AI and process control manager can earn $100,000. Companies like Amazon and Google are snapping up graduates for AI positions in the US and Europe, hunting for doctorate-holders in fields like machine learning, information science and statistics.

Uttara Choudhury is a writer for Forbes India and The Wire. In 1997, she went on the British Chevening Scholarship to study Journalism in the University of Westminster, in London.