Aug.19, 2013

The key theme of the 2013 edition of Gartner's long-running "Hype Cycle for Emerging Technologies" is "the evolving relationship between humans and machines due to the increased hype around smart machines, cognitive computing and the Internet of Things."

Analysts believe that the relationship is being redefined through emerging technologies, narrowing the divide between humans and machines.

Jackie Fenn, vice president and Gartner fellow who came up with the hype cycle idea in 1995, says "In fact, by observing how emerging technologies are being used by early adopters, there are actually three main trends at work. These are augmenting humans with technology — for example, an employee with a wearable computing device; machines replacing humans — for example, a cognitive virtual assistant acting as an automated customer representative; and humans and machines working alongside each other — for example, a mobile robot working with a warehouse employee to move many boxes."

"Enterprises of the future will use a combination of these three trends to improve productivity, transform citizen and customer experience, and to seek competitive advantage," said Hung LeHong, research vice president at Gartner.

"These three major trends are made possible by three areas that facilitate and support the relationship between human and machine. Machines are becoming better at understanding humans and the environment — for example, recognizing the emotion in a person's voice — and humans are becoming better at understanding machines — for example, through the Internet of things. At the same time, machines and humans are getting smarter by working together."

Figure 1. Hype Cycle for Emerging Technologies, 2013

Gartner Hype Cycles 2013 Source: Gartner

The three main trends are:

1. Augmenting humans with technology

The main benefit to enterprises in augmenting humans with technology is to create a more capable workforce. For example, consider if all employees had access to wearable technology that could answer any product or service question or pull up any enterprise data at will. The ability to improve productivity, sell better or serve customer better will increase significantly.

Enterprises interested in these technologies should look to bioacoustic sensing, quantified self, 3D bioprinting, brain-computer interface, human augmentation, speech-to-speech translation, neurobusiness, wearable user interfaces, augmented reality and gesture control.

2. Machines replacing humans

There are clear opportunities for machines to replace humans: dangerous work, simpler yet expensive-to-perform tasks and repetitive tasks. The main benefit to having machines replace humans is improved productivity, less danger to humans and sometimes better quality work or responses. For example, a highly capable virtual customer service agent could field the many straightforward questions from customers and replace much of the customer service agents' "volume" work — with the most up-to-date information.

Enterprises should look to some of these representative technologies for sources of innovation on how machines can take over human tasks: volumetric and holographic displays, autonomous vehicles, mobile robots and virtual assistants.

3. Humans and machines working alongside each other

The main benefits of having machines working alongside humans are the ability to access the best of both worlds (that is, productivity and speed from machines, emotional intelligence and the ability to handle the unknown from humans). Technologies that represent and support this trend include autonomous vehicles, mobile robots, natural language question and answering, and virtual assistants.

A new generation of robots is being built to work alongside humans. For example, IBM's Watson does background research for doctors, just like a research assistant, to ensure they account for all the latest clinical, research and other information when making diagnoses or suggesting treatments.

Enterprises should consider quantum computing, prescriptive analytics, neurobusiness, NLQA, big data, complex event processing, in-memory database management system (DBMS), cloud computing, in-memory analytics and predictive analytics.

Hype Cycles estimates how long technologies and trends will take to reach maturity and helps organizations decide when to adopt. It represents the five stages of new technology adoption and starts with a Technology Trigger: a new invention or innovation. It goes then all the way up to a "peak of inflated expectations" and then down to a "trough of disillusionment". Successful innovations could climb the "slope of enlightenment" and, finally reach to "plateau of productivity".

In the 2013 hype cycle, Technology Triggers include 3D bioprinting, 3D scanners, autonomous vehicles and biochips etc, all of which Gartner reckons are 5-10 years from the plateau.

Consumer 3D printing, together with "big data", gamification, and wearable user interfaces are listed at the overhyped stage.

Mr. LeHong and Ms. Fenn will provide additional analysis during the Gartner webinar "Emerging Technologies Hype Cycle for 2013: Redefining the Relationship" on August 21, at 10 a.m. EDT and 1 p.m. EDT. registration required.

 


Posted in 3D Printing Technology

 

 

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Michael Raphael wrote at 8/22/2013 2:17:14 PM:

Excellent observation about the differentiation between the two types of 3D printing by Gartner from last year to this year. Question - do you think this will therefore be the case at some point for 3D scanning? I do.

Susanne Kahle wrote at 8/21/2013 1:26:47 PM:

The Gartner Hype Cycle obviously is nothing new (but kind of an "institution"). Regarding 3D printing it´s interesting that related items of the 3d manufacturing supply chain have been separated once more. I am not sure when it "happened" but take the same cycle 1 year earlier (http://speck-informatik.ch/2/wp-content/themes/webmagazine/images/Gartner-Hype-Cycle-2012.png) and you'll find 3D scanners, 3D printing, 3D bio printing as well as internet of things (ofc) but a very important distinction wasn´t part of it; 3D printing now exists in two versions: (1) consumer 3D printing and (2) enterprise 3D printing - each with its own "plateau estimation" 5-10 years years vs. 2-5 years. This is an important correction and so far is not part of most market estimations regarding market growth and size. Definitely both - consumer and enterprise 3D printing - are closley connected to each other (e.g. accessible technologies and materials as well as pricing) but don´t take the same course towards target groups, distribution and connected timeframes. This may also apply on an even deeper level when viewing possible developments in the small and medium-sized enterprises vs. micro business sector (which so far is more or less "untried").



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