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Silicon Valley opens the battle for artificial intelligence experts
Silicon Valley opens the battle for artificial intelligence experts
Artificial intelligence has become the latest darling of Silicon Valley. Google, Facebook, Amazon and apple have applied artificial intelligence to their image recognition algorithms, voice virtual assistants, and help you sort out news and social media content. It's also a hot field for small startups. In the 5 months since the start of the year, venture capital has increased from $3 billion 200 million in 2014 to $9 billion 500 million. This is the largest investment area in the year, and the largest recruitment area.
Artificial intelligence
Although research in this field dates back to the 1950s, it has not been until recently that artificial intelligence has become a mainstream subject of computer science. In this case, the number of specialists in this field is limited (and relatively small), and the number of experts continuing to stay in academia is decreasing because of the huge profits provided by technology companies.
In a New York Times report this week, Cade Metz describes in detail how big technology companies attract artificial intelligence experts, who offer the annual salary of up to $500 thousand. "There are fewer than 10 thousand people in the world who have the skills needed to solve advanced AI research," Metz wrote. At Stanford University, four famous researchers have left or are ready to leave in the past few years. At another center for artificial intelligence, University of Washington, 6 of the 20 professors in the school went to work in the industry during the holidays. If professors and researchers leave academia, who will teach the next generation of artificial intelligence experts?
This is not the first time this has happened. In 2015, Uber poached the core personnel of the Robotics Laboratory at Carnegie Mellon University, responsible for the company's driverless car project. After initially attracting several developers from the national robotics Engineering Center, NREC hired 40 former CMU employees (about 1/3 of the total). It includes many senior staff and some department heads. "They took all the research team members away," one insider told theVerge.
This is what we want to see now. Technology companies (not just Uber) do not rely entirely on researchers dug from academic institutions, but in a more constructive way to get things in their hands.
Companies like Google and Facebook now offer training programs to help employees speed up research on artificial intelligence. Because few experts are able to succeed in this field, projects like Facebook AI Academy are designed to make engineers proficient in deep learning. Once trained, they can apply their new knowledge to the other engineering teams of the company. Strategic acquisitions also help to solve the problem of labor shortage in artificial intelligence, such as Google's acquisition of DeepMind in 2014, but the premise is that artificial intelligence startups can start from this field.
Even so, demand is far greater than the supply of companies that require doctoral professionals. If science and technology companies want to make sure that the future of AI is enough, they need to find a balance between hiring experts to meet their needs, and letting them continue to teach the next generation.
Artificial intelligence
Although research in this field dates back to the 1950s, it has not been until recently that artificial intelligence has become a mainstream subject of computer science. In this case, the number of specialists in this field is limited (and relatively small), and the number of experts continuing to stay in academia is decreasing because of the huge profits provided by technology companies.
In a New York Times report this week, Cade Metz describes in detail how big technology companies attract artificial intelligence experts, who offer the annual salary of up to $500 thousand. "There are fewer than 10 thousand people in the world who have the skills needed to solve advanced AI research," Metz wrote. At Stanford University, four famous researchers have left or are ready to leave in the past few years. At another center for artificial intelligence, University of Washington, 6 of the 20 professors in the school went to work in the industry during the holidays. If professors and researchers leave academia, who will teach the next generation of artificial intelligence experts?
This is not the first time this has happened. In 2015, Uber poached the core personnel of the Robotics Laboratory at Carnegie Mellon University, responsible for the company's driverless car project. After initially attracting several developers from the national robotics Engineering Center, NREC hired 40 former CMU employees (about 1/3 of the total). It includes many senior staff and some department heads. "They took all the research team members away," one insider told theVerge.
According to the Pittsburgh Post reported that as of March 2016, yuho employees leave position still vacant (although NREC at the time of the "Post-Gazette" reporter said that they plan to use $11 million in new funding to hire 15 to 20 new employees). But Andrew Moore, Dean of the school of computer science at Carnegie Mellon University, shrugged off it. Moore of the Pittsburgh Post said: "this kind of thing happens several times each year. What we should focus on is, "what should we do next?"
This is what we want to see now. Technology companies (not just Uber) do not rely entirely on researchers dug from academic institutions, but in a more constructive way to get things in their hands.
Companies like Google and Facebook now offer training programs to help employees speed up research on artificial intelligence. Because few experts are able to succeed in this field, projects like Facebook AI Academy are designed to make engineers proficient in deep learning. Once trained, they can apply their new knowledge to the other engineering teams of the company. Strategic acquisitions also help to solve the problem of labor shortage in artificial intelligence, such as Google's acquisition of DeepMind in 2014, but the premise is that artificial intelligence startups can start from this field.
Even so, demand is far greater than the supply of companies that require doctoral professionals. If science and technology companies want to make sure that the future of AI is enough, they need to find a balance between hiring experts to meet their needs, and letting them continue to teach the next generation.