Out of the more than 200 unique technologies that have ever appeared on a Gartner Hype Cycle for Emerging Technology, just a handful of technologies - Cloud Computing, 3D Printing, Natural Language Search, Electronic Ink - have been identified early and traveled even somewhat predictably through a Hype Cycle from start to finish. In general, we're bad at making predictions. No surprise to any experienced Silicon Valley hands. I've learned that lesson and seven more from my deep dive into the data. After analyzing every year from 2000 on, I think I can say with confidence that we are simply not very good at predicting the future. With some notable exceptions, such as the technology terms that Gartner coins itself, I think of the Gartner Hype Cycle as mostly a reflection of industry consensus.)īut our inability to remember the past in proper context is not the only lesson from taking a deep dive into Gartner's past Hype Cycles. (And incidentally, my intention is not to call out Gartner’s accuracy as a firm specifically. But yet, there it is in the 1995 Hype Cycle, important enough to merit one of just ten slots in that year's listing.
Today if I asked 20 Silicon Valley technologists to name which technologies succeeded and failed since 1995, I think I can guarantee that no-one would name Emergent Computation. (Emergent computing, by the way, is computing based on distributed evolutionary algorithms - a kind of cousin to neural network based machine learning.
I think of the Gartner Hype Cycle as a Hero's Journey for technologies. Today, twenty years later, we’re once again trying to build intelligent assistants, although now we call them Chatbots, and the core tech - contextual reasoning in a broad domain - is still a hard problem. Two years later, Office 97 introduced Clippy, the enthusiastic, but incompetent assistant which was so poorly received that it effectively killed off the idea for a generation. The most hyped technology in 1995 was Intelligent Agents.
Still others are technologies that we thought were almost baked but actually took decades longer to reach full maturity (Speech Recognition). Some technologies have simply disappeared from public consciousness (Emergent Computing). Some of its technologies that have become so ubiquitous, that they're now background noise (Object-Oriented Programming). And it's truly a fascinating historical document. Gradual, practical adoption: "The Slope of Enlightenment" and "The Plateau of Productivity"īy way of illustration, below is the first Hype Cycle - from 1995.Excessive disappointment : "The Trough of Disillusionment".Excessive enthusiasm: "The Peak of Inflated Expectations".In this model, technologies all go through a process of : First published in 1995, the Hype Cycle proposed a standard adoption model for new technologies. This article is the result.Īs most of you know, the Gartner Hype Cycle for Emerging Technologies is practically an institution in high tech. A quick Google search didn't turn up anything useful, so I decided I'd do the work and write it myself. 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". 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. 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.