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As Companies Embrace AI, It's a Job-Seeker's Market (reuters.com)
An anonymous reader shares a report: Artificial intelligence is now being used in an ever-expanding array of products: cars that drive themselves; robots that identify and eradicate weeds; computers able to distinguish dangerous skin cancers from benign moles; and smart locks, thermostats, speakers and digital assistants that are bringing the technology into homes. At Georgia Tech, students interact with digital teaching assistants made possible by AI for an online course in machine learning.
The expanding applications for AI have also created a shortage of qualified workers in the field. Although schools across the country are adding classes, increasing enrollment and developing new programs to accommodate student demand, there are too few potential employees with training or experience in AI. That has big consequences. Too few AI-trained job-seekers has slowed hiring and impeded growth at some companies, recruiters and would-be employers told Reuters. It may also be delaying broader adoption of a technology that some economists say could spur U.S. economic growth by boosting productivity, currently growing at only about half its pre-crisis pace.
[...] U.S. government data does not track job openings or hires in artificial intelligence specifically, but online job postings tracked by jobsites including Indeed, Ziprecruiter and Glassdoor show job openings for AI-related positions are surging. AI job postings as a percentage of overall job postings at Indeed nearly doubled in the past two years, according to data provided by the company. Searches on Indeed for AI jobs, meanwhile increased just 15 percent.
The expanding applications for AI have also created a shortage of qualified workers in the field. Although schools across the country are adding classes, increasing enrollment and developing new programs to accommodate student demand, there are too few potential employees with training or experience in AI. That has big consequences. Too few AI-trained job-seekers has slowed hiring and impeded growth at some companies, recruiters and would-be employers told Reuters. It may also be delaying broader adoption of a technology that some economists say could spur U.S. economic growth by boosting productivity, currently growing at only about half its pre-crisis pace.
[...] U.S. government data does not track job openings or hires in artificial intelligence specifically, but online job postings tracked by jobsites including Indeed, Ziprecruiter and Glassdoor show job openings for AI-related positions are surging. AI job postings as a percentage of overall job postings at Indeed nearly doubled in the past two years, according to data provided by the company. Searches on Indeed for AI jobs, meanwhile increased just 15 percent.
No it doesn't require much. What they call "AI" isn't very complex at all - they are just applying well known techniques to data. Same crap that people were doing in the 1960s.
You are somewhat correct, if esoteric research in the 1960's is what you are referring to as 'known techniques'. Modern AI techniques weren't truly implemented until the mid 70's, with broader acceptance and applications demonstrated in the mid 80's: https://en.wikipedia.org/wiki/...
If you are referring to the 1960's symbolic (lisp) techniques espoused by the disgraced Marvin Minsky, nearly fired from MIT for borderline fraud, a case that saw MIT forced to repay DARPA millions in wasted research money, then you are a bit behind the times. Modern AI techniques are now quite far from Minsky's self-aggrandized approach. Modern techniques were pioneered more by Minksy's high-school rival and a victim of Minky's petulant personal and private bullying, the truly brilliant Frank Rosenblatt. Frank was so close. Had he lived just a few more years and kept his confidence, he would have seen his dream realized.
Why it took the span of a human lifetime for people to see through Marvin is baffling: https://www.reddit.com/r/Machi...
Anyway, modern AI takes a bit of calculus to truly understand, and some statistics. An undergraduate with a solid math foundation should be able to derive the backprop algorithm and explain it. Then there's catastrophic forgetfulness, SLAM techniques with grid and place cells... probably things beyond a typical undergraduate curriculum, but possible.
Any technician can be trained to push buttons. It might take a bit more fundamental understanding of what is going on under the covers to catch training pitfalls and prevent inefficiencies. Maybe this is what companies hiring for AI work are after.
"Every time I see an adult on a bicycle, I no longer despair for the future of the human race." - H. G. Wells