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Tech Giants Are Paying Huge Salaries For Scarce AI Talent (santafenewmexican.com)
jmcbain writes: Machine learning and artificial intelligence skills are in hot demand right now, and it's driving up the already-high salaries in Silicon Valley. "Tech's biggest companies are placing huge bets on artificial intelligence (Warning: may be paywalled; alternative source)," reports the New York Times, and "typical AI specialists, including both Ph.D.s fresh out of school and people with less education and just a few years of experience, can be paid from $300,000 to $500,000 a year or more in salary and company stock." The New York Times notes there are several catalysts for rocketing salaries that all come down to supply and demand. There is competition among the giant companies (e.g. Google, Facebook, and Uber) as well as the automative companies wanting help with self-driving cars. However, the biggest issue is the supply: "Most of all, there is a shortage of talent, and the big companies are trying to land as much of it as they can. Solving tough A.I. problems is not like building the flavor-of-the-month smartphone app. In the entire world, fewer than 10,000 people have the skills necessary to tackle serious artificial intelligence research, according to Element AI, an independent lab in Montreal."
In the entire world, fewer than 10,000 people have the skills necessary to tackle serious artificial intelligence research, according to Element AI, an independent lab in Montreal
In the entire world, fewer than 1000 people have the skills necessary to do unstructured tetrahedral finite element mesh generation. It is possible there are fewer than 1000 people who have the skills necessary to understand what exactly we mesh makers do. And, Surprise! there is demand for fewer than 1000 people to write unstructured tetrahedral finite element mesh generation. And far fewer than 1000 people are needed to manage them.
I am glad the periodical bubbles that infect Wall Street and venture capitalists benefits PhDs once in a while. Most of the time it benefits hedge fund monkeys or stock market cheats or lottery winners with delusions of grandeur or plain sociopaths. Happy for my grad school classmates. Enjoy the windfall while lasts, Ramachandran\s, Yang\s, Hsu\s, Gupta\s, Parpia\s and Wickramasinghe\s.
sed -e 's/Chuck Norris/Rajnikant/g' joke > fact
You should at least try to understand what you are talking about. Deep learning, aka neural networks, are not "algorithms and programs". They are part of the machine learning branch of AI. The computer is not programmed but learns by itself. People in computer science have been trying to do that for as long as computers have been around but were never quite successful until about 2012. Deep learning excels at tasks which are too complicated for humans to write code such as detecting objects in picture and analyzing recordings of voices or translating text. This is revolutionary. Even the primitive neural net technology we currently have will transform many applications in the next few years, in that they perform much better than what humans used to code and they require just a handful of AI specialists to train instead of team of 100 programmers. If the technology continues to improve, it could take over just about every field: driving, medicine, law, manufacturing, etc. But the current technology has limitations and it's not clear how much it can progress further.
Computer programmer could be one of the first job to be made obsolete by deep learning. Programmers will have retrain themselves as teachers to neural nets instead.