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Adults like to use a lot of complicated words to say something. This could be because they want to show their impressive vocabulary. It gets worse in technical fields like Computer Science which have a lot of big technical words. These technical words are supposed to help differentiate between similar ideas. But most often it complicates simple ideas. In this article, I'll try not to use these complicated words.

Who's doing this? 75% of the Fortune 500 companies have some kind of smart data or semantics program underway, most under the banner of 360 initiatives, comprehensive enterprise data systems, or machine learning/data science projects. Amazon has recently added linked data capabilities to their AWS infrastructure with the Neptune project, and social media giants have built their entire data infrastructure around smart ontological data. Moreover, China, Japan, England, the OECD, and the United States have all moved critical data resources into semantic form, and semantics has become one of the hottest areas for investment banks such as Wells Fargo, Morgan Stanley, Citigroup, Goldman Sachs and others. It even ties into such cutting edge technologies as Blockchain and the Internet of Things.

We have had many previous hype cycles around AI. As I wrote in Silicon Collar: "Since the 1950s! That is when Alan Turing defined his famous test to measure a machine's ability to exhibit intelligent behavior equivalent to that of a human. In 1959, we got excited when Allen Newell and his colleagues coded the General Problem Solver. In 1968, Stanley Kubrick sent our minds into overdrive with HAL in his movie, 2001: A Space Odyssey. We applauded when IBM's Deep Blue supercomputer beat Grandmaster Garry Kasparov at chess in 1997. We were impressed in 2011 when IBM's Watson beat human champions at Jeopardy! and again in 2016 when Google's AlphaGo showed it had mastered Go, the ancient board game. Currently, we are so excited about Amazon's Echo digital assistant/home automation hub and its ability to recognize the human voice, that we are saying a machine has finally passed the Turing Test. The good news is over the seven decades, the AI community has gifted us a wide range of big words like deep learning, neural networks, cognitive computing and natural language processing. Yale computer science professor David Gelernter thinks we have only scratched the surface. In his book The Tides of Mind, he calls it "the spectrum of consciousness," which is "essentially a range of mental states through which all humans cycle each day.