A High Paying Job

 
 
 

Vocabulary

bet	presence	artificial intelligence
stock	artificial	place a bet
scan	agenda	autonomous
giant	fruition	intelligence
lavish	reward	fresh out
earn	top end	executive
gadget	endeavor	division (3)
mega	catalyst	offensive (2)
array	exist (2)	branch out
confine	demand	know-how
employ	shortage	conduct (3)
talent	court (3)	cutting-edge
neural	algorithm	center around
overall	network	perpetual
pattern	post (2)	recognize
identify	translate	command
fringe	field (3)	date back to
recruit	specialize	relatively
siphon	available	academia
salary	leave (2)	take leave
way	full-time	compromise
split	hamper	turn down
allow	institute	fill in the ranks
in turn	run (3)	branch (2)
hire	after all	astronomer
wage	analyze	major (2)

 
 
 
 

Artificial Intelligence

Virtually all major technology companies have an artificial intelligence agenda, placing huge bets on developments ranging from face-scanning smartphones and conversational gadgets to computerized health care and autonomous vehicles.

AI Experts

To bring these visions into fruition, tech giants are courting AI experts with lavishing rewards. Both Ph.D.s fresh out of university and those with less education and just a few years of experience, can earn from $300,000 to $500,000 a year or more in salary and company stock.

At the top end are executives with experience managing AI endeavors. One of them is Anthony Levandowski. He Joined Google in 2007 and become one of the leaders of their self-driving-car division. During his time at Google, Levandowski received over $120 million, before joining Uber in 2016.

Demand

One of the catalysts for the mega salaries is demand. Companies like Facebook and Google are branching out, developing an array of products like digital assistants for smartphones and programs that spot offensive content.

And the need for tech know-how is not confined to Silicon Valley: the auto industry employs the same experts who create Google’s self-driving cars.

Supply

But most of all, there is a perpetual shortage of top talent. In the entire world, fewer than 10,000 people have the right intelligence and knowledge to conduct cutting-edge research in artificial intelligence.

Working on AI projects is not like building a game-of-the-month smartphone app, which many people could do.

Algorithms

Artificial intelligence R&D centers around deep neural networks. These are sets of techniques based on mathematical algorithms that can learn tasks on their own by analyzing data.

For example, by looking for patterns in millions of dog photos, a neural network can learn to recognize a dog. This process could also help recognize faces in photos posted to Facebook, translate foreign languages on Skype, and identify commands spoken to robots.

Neural networks dates back to the 1950s, but remained on the fringes of academia and industry — until about five years ago when Google, Facebook and a few other companies started to recruit the relatively few researchers who specialized in this field.

University Professors

Today with still so few AI specialists available, big tech firms are siphoning off the best and brightest from academia. But doing so hampers the teaching of the technology.

Over the last several years, four of the best-known AI researchers in have left or taken leave from their posts at Stanford University, and now work full-time for companies.

Some professors are finding a way to compromise, splitting their time between industry and academia. Luke Zettlemoyer of the University of Washington turned down a position at a Google-run laboratory that would have paid him more than three times his professor’s salary of $180,000. Instead, he chose a post at the Allen Institute that allowed him to continue teaching.

Alternatives

To fill in their AI engineering ranks, Google and Facebook run classes that teach “deep learning” to existing employees.

Smaller companies in turn are hiring physicists and astronomers who have the necessary math skills.

And US-based companies are recruiting specialists in Asia, Eastern Europe and other locations where wages are lower. Microsoft has long had a solid presence in China. Google is now hiring there as well.

Overall however, things will not get better any time soon said Yoshua Bengio, an AI researcher at the University of Montreal. “After all, it takes many years to educate a Ph.D.”

 

Questions

1. Is there tremendous growth in the artificial intelligence sector, or has it plateaued?

2. AI experts typically earn about $50 per hour. True or false? Do AI engineers earn the most?

3. Are tech giants like Google and Facebook sticking to their niche or are they diversifying their businesses?

4. Only hi-tech companies in Silicon Valley need AI specialists. Is this correct or incorrect?

5. Can any reasonably smart or average person become an AI guru?

6. What is at the heart of artificial intelligence? What are some examples of AI developments and programs?

7. Are companies turning to alternative sources for AI staff? How are they acquiring more AI personnel?

8. Will the situation improve in the future?

 

A. My company or organization deals with artificial intelligence. Yes or no?

B. My friends and I would like to become AI specialists.

C. Are there lots of hi-tech industries that depend on AI in your city or country?

D. Is there a good AI program at your local university?

E. What will happen in the future?

F. How can the shortage of AI experts be filled?