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HYPE CYCLE: What is it & Why does it MATTER?

Last Updated on July 5, 2020 by TechStrain

What is the hype cycle?

The hype cycle is actually a graphic representation of technologies that show the complete life cycle, from the very beginning of its birth to the widespread adoption of the technology. Technology does not just get widespread all of a sudden, it goes through various stages like technology trigger to the plateau of productivity. The hype cycle represents every stage of the technology it passes through.

Gartner, a famous technology research company provides insight into the hype cycle as they created the term ‘hype cycle’ thus it is also known as Gartner Hype Cycle.

What are the five components of Gartner’s hype cycle?

The Gartner hype cycle consists of five components. The components are the phases or stages a technology goes into its life cycle. Every technology goes through these phases, the five component of Gartner’s hype cycle is

5 components pf Garner's hype cycle

Innovation Trigger:

This is the very initial phase as the technology concept is introduced via this early stage with proof-of-concept which gains media interest at this stage. In this stage, no usable product is available, or a prototype may be available sometimes.

This is a very early stage when the tech starts to take place in the real world with a boom. One real-life example would be flying automated vehicles technology which concept was introduced a couple of years ago which attracted a lot of attention to media.

Peak of Inflated Expectations:

The media interest and publicity create a lot of buzz in this stage. Some early adopters adopt it for some early advantages. In this stage, the buzz keeps soaring pretty high. A Deep Neural network is one example of it.

Trough of Disillusionment

So after the peak, the interest starts to go down gradually. Experiments and implementation take place in this phase; some of them fail to deliver. When flaws and failures are screened in this stage, producers step back or put importance on solving the problems. Blockchain is one example of a Trough of Disillusionment.

Slope of Enlightenment

As technology survives in the previous phase, it gets to the widespread understanding. More funding takes place in this stage, as the technology shows its potential. Predictive analytics is one example of the Slope of Enlightenment.

Plateau of Productivity

In this stage, widespread implementation of technology takes place. So many companies start to implement which makes it more widespread. Speech Recognition is one example of Plateau of Productivity.

Hype Curve

The Gartner hype cycle follows a curve in itself. As the hype follows certain stages and certain stages go with ups and downs. From the conception stage, the hype goes upward when it reaches its peak, after reaching its peak its starts to go down. When a technology passes the trough of disillusionment, it starts to go a little high again where it reaches its plateau and stands still there for a quite amount of time.

All the stages combine a curve which looks like that

Hype curve of Gartner hype cycle
Source

Gartner hype cycle 2020

Some of the digital technology trends for 2020 are

Hyper automation

Hyper automation is kind of associated with Murphy’s Law

Anything that can go wrong will go wrong

Just like that, not in the wrong aspect though; whatever can be automated will be automated. It means the broader expansion of automation in the industry. As if there is more scope of automation, there will be automation.

Multi-experience

Multi experience means the combined experience of all the other possible services altogether. For an example of food ordering, you order food over your Smartphone apps and the food is being delivered using an automated vehicle, a multi-experience for a single service.

Democratization

Democratization means the users are getting easier access with a more simplified user interface

Human Augmentation

Human augmentation combines all the automation and other features so that humans can gain much better cognitive and physical experiences.

Transparency and Traceability

There always has been some trust crisis on the technology issue regarding some of the complex technology like explainable AI, ethical AI, etc. Transparency and traceability will ensure the transparency of data on how the data are being used and traceability would provide insight into what will happen upon the usage of data.

Empowered Edge

Empowered edge will be beneficial and helpful for achieving higher security and efficiency goals. The conversational system would be more efficient if it held on the edge of the network rather than in the central cloud.  

Distributed Cloud

Cloud computing is already in its plateau of productivity, the next big thing for cloud would be distributed cloud as cloud computing is seeing some challenges with latency and some other means. Distributed cloud would lower the latency which is a major deal for the Internet of Things (IoT).

Autonomous Things

Autonomous things are a result of artificial intelligence and machine learning enabling a better autonomous action which will be a massive part of our future.

Practical Blockchain

BlockChain has been a major tech, although it was struggling a little. Practical blockchain will be a better solution to the current blockchain poor technical issues.

Artificial Intelligence Security

AI security involves securing Ai models and training data, AI-powered security tools for better security, and addressing AI attacks as hackers also using AI to enhance their attack methods.

 How long does hype last?

The hype cycle is a model, not all the technologies follow the timeline of the hype cycle. Some technologies get to the peak hype and stay there for quite some time.

Artificial intelligence has been its peak for quite some time and it is nowhere near slowing down yet. And it is most likely to be at a peak in the next couple of decades, as it is getting connected everywhere. But also we can see some other subsets of AI are taking place and gaining a lot of momentum like machine learning and deep learning.

Not every new technology on earth is going to follow the timeline of the hype cycle, some will advance at a pretty fast pace while some will fail to deliver. Overall, the maximum number of techs almost follows the curve most of the time.

Although, there are some time categories of time for the hype cycle from the innovation to widespread adoption. These time categories are

  • Less than 2 Years
  • 2 to 5 years
  • 5 to 10 Years
  • More than 10 Years
  • Obsolete before Plateau

Why does the hype cycle matter?

The hype cycle is really important for people who are in business and looking to invest in the technology market. There are several examples where the tech came up with way much hype and failed to deliver causing massive loss to the investors.

Two major examples would be,

  • 3D printing
  • Cryptocurrency
cryptocurrency

3D printing created a lot of buzz in the tech world as it first seems like a very promising tech which would change the way of manufacturing that a lot of households could potentially own 3D printing. The stock prices increased rapidly and also went down rapidly too, as it is yet not ready to change the course of manufacturing.

The same goes for cryptocurrency, it has been in the market for quite some time. It created a lot of buzzes yet it is still not as widespread as it was supposed to be. Typically in the market, there is an overestimation for the short term potential where there also an underestimation for long time potential.

That is where, understanding the hype cycle is important, especially for business persons and investors.

Conclusion

Technology plays a pretty massive role in our life and emerging technologies are on the top of our curiosity. We are always looking for new revolutionary technologies which are going to change the course of our future. That is where the Gartner Hype Cycle comes in handy as they provide the most likely insights of the new and latest technologies that are going to rule in the tech industry.

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