Artificial intelligence—in the guises of personal assistants, bots, self-driving cars, and machine learning—is hot again, dominating Silicon Valley conversations, tech media reports, and vendor trade shows.AI is one of those technologies whose promise is resurrected periodically, but only slowly advances into the real world.
I remember the dog-and-pony AI shows at IBM, MIT, Carnegie-Mellon, Thinking Machines, and the like in the mid-1980s, as well as the technohippie proponents like Jaron Lanier who often graced the covers of the era’s gee-whiz magazine like Omni.[ Learn how to write apps that take full advantage of machine learning: Data in, intelligence out: Machine learning pipelines demystified • Google’s machine-learning cloud pipeline explained • R and Python drive SQL Server 2017 into machine learning. | Keep up with hot topics in programming with InfoWorld’s App Dev Report newsletter. ]
AI is an area where much of the science is well established, but the implementation is still quite immature.
It’s not that the emperor has no clothes—rather, the emperor is only now wearing underwear.

There’s a lot more dressing to be done.To read this article in full or to leave a comment, please click here

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