Mini Computing Utilizing Centralized Model of Dumb Terminals

Mainframe and mini computing utilize the centralized model where the distributed dumb terminals offer I/O, but computing resources and software are centralized. By virtue of this, both standalone and networked architectures in the kind of client/server and peer-to-peer software were embraced. Then came the Web technologies of the'90s, which made it feasible to deploy the server applications in one place and Internet clients were deployed as needed in remote, distributed places.

This brought back the centralized version again that's still continued today via the cloud. By creating differentiated cloud models for human-centric vs. machine-centric through the use of centralized and decentralized computing, respectively, cloud sellers can take the market positions and value they have already established and evolve to be futuristic.

To answer this question, we need to comprehend from a historic perspective of how the different computing models were adopted as new technologies emerged. There have been primarily two models that have been playing out rather since the mainframe was introduced to the business world. Cloud computing has helped start, grow and alter several organizations across many industry segments contributing significantly to global economic growth.

One of the important areas that cloud catalyzed growth and adoption is large data. No blockchain currently aims to accommodate enormous information and this is where DXChain plans to make an impact. Big data has helped derive insights from enormous data (with quantity, variety and speed ) sources that are both structured and unstructured, and more data sources are being added at a much faster rate daily through the rapid adoption of IoT.

Adding the decentralized model as a separate offering to address machine and distributed data needs won't only be expensive but also be technically very challenging for cloud vendors. It will require embeddable or separate edge resources (software and hardware) distributed with seamless interconnection with one another.

There are billions of links, and all of those are linked to cloud backbone for bigger offline data processing. And I believe today's cloud models will continue to evolve with more innovation to build on the centralized cloud models for human-centric applications, but it'll be interesting to see how things will play out in the future.

There are other emerging regions popping up everywhere like cryptocurrencies, the machine economy (i.e., a combination of IoT and cryptocurrencies), distributed applications like Ethereum DApps and a whole slew of peer-to-peer applications. However, the majority of these emerging areas need a computing model that appears to be incompatible with the present cloud compute model. Can cloud providers do something about this incompatibility and change the cloud to provide comprehensive services in the future, or will they fall prey to disruption? My perspective on the debate as to whether machines will take over people is that it's absurd.

If we built AI properly, then the machines will know that coexistence and peace is the right way and will figure out ways to achieve that by guiding humans and not try and take over the world. With the recent advancements we've made in machine learning, it is clear now more than ever before that AI will play a critical role in the evolution of humanity.

Now is about the time that we ought to start yielding to machine intelligence by building and positioning our compute models that could recognize the requirements of machines as a separate and essential factor. This means we should expect to see both centralized and decentralized models (and some other future versions ) to live and coexist to serve dedicated purposes seamlessly. I feel that the centralized cloud model will work well for human-centric use and the decentralized model for machines and distributed data applications. at the edge.

Referral Link: https://t.me/DxChainBot?start=shsxa1-shsxa1
DxChain: https://www.dxchain.com/