Machine Learning Times
Machine Learning Times
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3 years ago
8 Lessons from 20 Years of Hype Cycles

Originally published in LinkedIn, Dec 7, 2016

As a VC at Icon Ventures and a twenty year veteran of productizing and marketing high tech for VMware, Netscape and others, I’ve always been fascinated by how new technologies emerge and come to market. One of the major artifacts that tries to capture the state of our market and industry each year is the annual Gartner Hype Cycle – which I always read with interest. Just last month, I had an interesting thought: “Has anyone gone back and done a retrospective of Gartner Hype Cycles – because I’d totally read that article”. A quick Google search didn’t turn up anything useful, so I decided I’d do the work and write it myself. This article is the result.

As most of you know, the Gartner Hype Cycle for Emerging Technologies is practically an institution in high tech. First published in 1995, the Hype Cycle proposed a standard adoption model for new technologies. In this model, technologies all go through a process of :

  1. Emergence: “The Technology Trigger”
  2. Excessive enthusiasm: “The Peak of Inflated Expectations”
  3. Excessive disappointment : “The Trough of Disillusionment”
  4. Gradual, practical adoption: “The Slope of Enlightenment” and “The Plateau of Productivity”

By way of illustration, below is the first Hype Cycle – from 1995. And it’s truly a fascinating historical document. Some of its technologies that have become so ubiquitous, that they’re now background noise (Object-Oriented Programming). Some technologies have simply disappeared from public consciousness (Emergent Computing). Still others are technologies that we thought were almost baked but actually took decades longer to reach full maturity (Speech Recognition).

To continue reading this article, click here.

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