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Bye bye blockchain developer, hello artificial intelligence specialist.
That role, A.I. specialist, is the fastest growing U.S. job in terms of number of hires, at least according to LinkedIn, which published its annual emerging jobs report on Tuesday.
Hirings for A.I. specialists on the career networking service have grown 74% annually over the past four years, LinkedIn said. But it didn’t reveal how many jobs that represents, only that demand for that job role is growing faster than other emerging jobs.
What’s noteworthy about this year’s survey is that last year’s top job role, blockchain developer, is absent from the latest list. It highlights how the recent craze over cryptocurrencies and blockchain created a brief demand for blockchain-related jobs, but as the hype died down, so too did demand for people with blockchain skills.
“It was spectacular, but vanished very quickly,” LinkedIn’s principal economist Guy Berger said. The fact that blockchain developers did not make this year’s emerging job list caused Berger to say that it validates his company’s data by showing it accurately reflects “a failed trend or a flash in the pan.”
No. 2 on the list was “robotics engineer,” an umbrella term for both physical robotics and so-called robotic process automation, a trendier technology that involves software automating basic tasks like entering data into a table. The third fastest growing job in terms of hiring was “data scientist.”
A.I. specialist is an evolution of other machine-learning and data-crunching job titles that have topped the list before. Although A.I. specialists may share some traits with data scientists, the work of data scientists involves a wider set of statistical or data visualizations tools versus just machine learning software, Berger said.
The top metropolitan areas where A.I. specialists are in demand include the San Francisco Bay Area, New York, Boston, Seattle, and Los Angeles. Computer software, Internet, information technology, higher education, and consumer electronics are the industries with the biggest appetite.
The most common jobs that A.I. specialists held prior to labeling themselves with the title include “software engineer,” “data scientist,” “research assistant,” and “data engineer,” a LinkedIn spokesperson said. This suggests that people may be updating their job titles to include artificial intelligence, to put themselves in a better position to capitalize on the current A.I. boom.
“When you talk about A.I., again it’s super high in demand,” Berger said. “I think there’s more and more interest in taking data science to the next level.”
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A.I. IN THE NEWS
Seeing big bucks. SenseTime, a Chinese startup specializing in facial recognition technology, could make $750 million in sales during fiscal 2019, a 200% year-over-year increase, Reuters reported, citing unnamed sources. Although SenseTime’s sales are growing slower than they were in previous years, the company is still making a lot of money despite being blacklisted by the U.S. government, the report added.
Hungry for A.I. chips. Intel could spend $1 billion to $2 billion to acquire Israeli A.I. computer chip company Habana Labs, according to Israel business news publication Calcalist, as recounted by The Times of Israel. “If the deal goes through, it would make it Intel’s second-largest acquisition in Israel,” the report said.
Keeping up with Amazon. Amazon’s plans to become a supermarket titan has caused traditional grocers to invest in and experiment with cutting-edge technology like shelf-scanning robots and automated warehouse systems, Bloomberg News reported. “In their backrooms, some food retailers are building automated warehouses that prepare online grocery orders, eliminating the need for the expensive armies of human shoppers who currently troll the aisles harvesting products for Instacart and other services,” the report said.
The VA goes bets on A.I. The U.S. Department of Veterans Affairs debuted the National Artificial Intelligence Institute (NAII), an A.I. research group intended to help the federal agency embark on cutting-edge data-crunching projects that help veterans. “The NAII designs and collaborates on large-scale AI R&D initiatives, national AI policy, and partnerships across agencies, industries, and academia,” according to the NAII’s website.
RECOGNIZING A.I. SNAKE OIL
Arvind Narayanan, a Princeton University associate computer science professor, wrote a guide about how to cut through A.I.’s hype. For instance, people shouldn’t assume that business applications will be immediately supercharged by A.I. just because researchers have developed A.I. systems that master board games like Go. He writes: “For example, AlphaGo is a remarkable intellectual accomplishment that deserves to be celebrated. Ten years ago, most experts would not have thought it possible. But it has nothing in common with a tool that claims to predict job performance.”
EYE ON A.I. RESEARCH
Hanabi as an A.I. test bed. Facebook researchers presented a paper, to be published in 2020 by the Association for the Advancement of Artificial Intelligence, detailing an A.I. system that learned to master the Solitaire-like card game Hanabi. Using a combination of reinforcement learning and a variant of the “Monte Carlo” search technique, the researchers were able to create digital bots that could work in tandem to beat the game at a high score.
FORTUNE ON A.I.
IBM Trials A.I. That Can Do Soccer Commentary—By Jeremy Kahn
China’s ‘Big Gamble’: Lessons From the Bike Sharing Bust May Hang Over Its A.I. Boom—By Grady McGregor
Why I Opt Out of Facial Recognition—By Robert Hackett
Amazon Touts Machine Learning, ‘Local Zones,’ and A.I. Tool as Cloud Competition Heats Up—By Jonathan Vanian
Keeping tabs of LEGOS with A.I. Children (and adults) love assembling Lego blocks to create castles and spaceships. But sorting through all those multi-colored blocks can be a chore when it’s time to put the toys away. Enter an A.I.-powered LEGO sorting machine built by Australian software developer Daniel West, as LEGO fan website The Brother’s Brick noted. Using neural networks trained to recognize different LEGOs, the contraption scans LEGO blocks and separates them into their appropriate buckets. As West says in his YouTube video, the machine “can take the human element out of sorting completely by recognizing almost 3,000 different types of Lego parts.”