Human Centric

Cloud computing has helped start, grow and transform many organizations across many business
segments contributing significantly to global economic growth. One of the key areas that cloud
computing expansion and adoption is large data. No blockchain currently intends to accommodate big
information and this is where DXChain intends to create an impact.

Big data has helped derive insights from enormous data (with volume, variety and velocity) sources that
are both structured and unstructured, and more data resources are being added at a much faster rate
daily during the rapid adoption of IoT. With the recent advancements we have made in machine
learning, it is clear now more than ever before that AI is going to play a critical role in the evolution of
humanity. Now is about the time that we ought to begin inventing to machine intelligence by building
and positioning our compute models that could recognize the needs of machines as a separate and
necessary factor.This means we should expect to see both centralized and decentralized models (and some other future
models) to live and coexist to serve dedicated purposes seamlessly. I believe that the centralized cloud
model works well for human-centric use and the decentralized model for machines and distributed data
applications.Mainframe and mini computing utilize the centralized model where the distributed dumb
terminals offer I/O, but computing resources and applications are centralized.In there's, and including the later variants,
Unix introduced the idea of decentralized computing where
software was deployed on several computers/workstations on a LAN/WAN network. By virtue of this,
both standalone and networked architectures in the kind of client/server and peer-to-peer software
were adopted.Then came the Web technologies of there's, which made it possible to deploy the server applications in
1 place and Web clients were deployed as needed in remote, dispersed places. This brought back the
centralized model again that is still continued today via the cloud. Adding the decentralized model as a
separate offering to tackle machine and dispersed data needs won't only be expensive but also be

technically very challenging for cloud sellers. It will require embedded or independent border
resources (hardware and software ) distributed with seamless interconnection with one another.

There are potentially 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 cloud models for human-centric applications, but it'll be interesting to see how things will play out
later on. There have been primarily two versions that have been playing out alternatively since the
mainframe was introduced to the business world. 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.My perspective on the debate as to whether machines will take over people is that it';s absurd. If we
built AI correctly, then the machines will know that coexistence and peace is the ideal way and will
figure out ways to accomplish this by directing humans and not attempt and take over the world. There
are other emerging regions popping up everywhere like cryptocurrencies, the machine market (i.e., a
blend of IoT and cryptocurrencies), distributed applications such as Ethereum DApps and a whole host
of peer-to-peer applications.However, most of these emerging areas need a computing model that appears to be incompatible withthe current cloud compute model. Can cloud suppliers do something about this incompatibility and
transform the cloud to offer comprehensive services in the future, or will they fall prey to disturbance?

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