Communications of the ACM
Million-Dollar Babies
In the field of deep learning, where computers draw insights from large data sets using methods similar to a human brains neural networks, the share of papers written by authors with some corporate affiliation is up sharply.
Credit: The Economist
Experts in machine learning are in high demand because large technology companies use it in many activities, ranging from basic tasks such as spam-filtering and better targeting of online advertisements to futuristic projects such as self-driving cars or scanning images to identify diseases.
Tech companies offer academics the opportunity to see their research pay dividends quickly, and private-sector jobs also free academics from the uncertainty of securing research grants.
In addition, tech firms offer lots of computing power and large datasets, which are especially appealing to artificial intelligence (AI) researchers and are essential for modern machine learning, according to Baidu's Andrew Ng.
However, the private-sector hiring spree could hurt universities that cannot offer competitive salaries. For example, Canadian universities have long been at the forefront of AI development, but that could change if their best researchers leave to work at U.S. technology companies, says University of Toronto professor Ajay Agrawal.
Another potential negative impact of this trend is if AI expertise is concentrated in just a few companies, it could create an intellectual monopoly. The threat of having one company corner the market on AI influence prompted several technology executives, including Tesla's Elon Musk, to pledge more than $1 billion for OpenAI, a nonprofit initiative that will make its research public.
From The Economist
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