Should-Read: "Enhancing" or "replacing"? Machines enhancing human brain power has been a thing ever since the first human notched a stick every time there was a new moon. If "AI" is to have a meaning, it will need a less all-inclusive definition...

Jacques Bughin and Eric Hazan: The new spring of artificial intelligence: "The Industrial Revolution was about machines enhancing human muscle power. The AI revolution is about machines enhancing human brain power... http://voxeu.org/article/new-spring-artificial-intelligence-few-early-economics

Computer vision, natural language processing, virtual assistants, smart robotics, and autonomous vehicles [are] all... underpinned by a new generation of machine-learning algorithms.... There are three reasons why AI is experiencing a new spring and will not go way:

  • First, more and more of clever investors, from venture capital and private equity, have tripled their AI investments over the past three years are now investing billions in AI. And even if this is small option bets–about 3% of total venture capital funding today–it is growing very quickly, even faster than biotech.

  • Second, while private equity and venture capital firms can still be wrong, of course, we found that corporate investment in AI is already three times the amount of private equity and venture capital firms. Among the corporations betting on AI, the most bullish are high-tech companies such as Intel and Samsung, along with the digital native players, such as Alphabet, Facebook and Amazon. Automotive companies are active, too—think about GM acquiring Cruise Automation for more than $1 billion last year. For anyone questioning the wisdom of paying so much for relatively new companies, it is worth noting that AI investments are already paying off—remember Kiva, the robotics company Amazon bought for $775 million in 2012? Kiva robotics used for logistics in Amazon reported to generate returns on investment of 50% for its new owner.

  • Third, the set of AI technologies we focus on are actually being deployed.... We found two-thirds of the companies are AI-aware... three clusters.... 20%... already serious adopters–mostly deploying machine learning or computer vision technologies.... 40% of firms have begun to experiment or are partial adopters.... Out of the 40% who are not adopting, the main reason isn’t that they don’t believe in AI. Our research shows there is a mix of commercial and technical obstacles; regarding the later, 28% of firms don’t feel they have the technical capabilities to implement...

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