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Innovating at The Edge — Decentralized Cloud Computing With DeepCloud AI 

It is the Cloud that you are referring to whenever you save a note to Google Keep or use a server-hosting service (such as AWS). The Cloud is an umbrella term that refers to a variety of networking, storage, and computation services that are available on-demand and provided by organizations all over the world. The concept is based on pooling the resources of computers to achieve economies of scale and to enable a large portion of the services, applications, and infrastructure that are available on the contemporary Internet.

During the past few years, there has been an explosion of cloud infrastructure and services, with Amazon Web Services (AWS), Microsoft Azure, and Google Cloud leading the charge into the software-as-services (SaaS) paradigm, which is the fastest-growing sector of a $3.76 trillion industry in global IT spending.

The rapid expansion of cloud computing, on the other hand, has come at a significant expense. Among the collateral consequences of a market controlled by tech giants in an era of surveillance capitalism are latency, high pricing, lost privacy, incompatibility with emerging technology, and increasingly centralized stores of sensitive user data.

“Centralized solutions are not suited for developing decentralized, peer-to-peer, and Internet of Things applications that require processing resources to be located close to the edge devices,” explains Max Rye, CEO of DeepCloud AI. As devices communicate with one another and automate operations, cost-effective solutions for payment flow and machine-to-machine micropayments are required to handle the enormous volume of data created at the edge. “…

DeepCloud AI is a new initiative that is bringing together cloud computing, blockchain-based decentralization, and artificial intelligence in a single framework (AI). What is their vision?

Democratize cloud computing and level the playing field for all participants, including consumers, developers, resource suppliers, and small businesses.

The Process of Recognizing and Addressing a Problem

At first sight, it would appear strange to identify areas of friction in the cloud computing landscape that are either insufficient or causing negative collateral effects, given the overwhelming magnitude, ubiquity, and power of cloud computing today. While there is some validity to the fallacy of techno-optimism, our capacity to recognize downstream problem areas is frequently lacking.

“As a result of the sharing economy, aggregation firms such as Uber and Airbnb have gained a significant amount of market share,” explains Rye. In the same way that many other technologies have, their novelty frequently outweighs any consideration of their future evolution to the huge, centralized behemoths that they have become today.

Rye is completely correct in this regard. 69 percent of the ride-hailing business is controlled by Uber, and Airbnb hosted 80 million guests in 2016. It is possible to demand large fees as a result of market domination, while at the same time raising concerns about data privacy when data is in the hands of centralized walled gardens. While these are not life-threatening issues, they do present chances for change, particularly as decentralization and privacy become increasingly important to mainstream people who are tired of huge tech companies abusing their data.

The blockchain, according to Rye, is “an emergent technology that is disrupting existing aggregative and cloud centralization paradigms.” “Blockchains give us the ability to usher in a new era of the ‘Internet of Value,’ in which data, marketplaces, and access to resources are democratized following the original concept of the Internet,” says the author.

That is precisely where DeepCloud AI enters the picture to help out. DeepCloud AI is working to create an ecosystem where the barrier to entry in developing and deploying decentralized applications is significantly reduced. DeepCloud AI is flattening the cloud computing landscape with an infrastructure built on a blockchain and resource allocation dictated by artificial intelligence.

The Internet of Things (IoT) “edge” devices, in particular, are an area where DeepCloud AI is ready to make an immediate impact. This is where a new generation of cost-effective yet powerful applications can emerge.

“DeepCloud AI provides a novel cloud infrastructure for decentralized apps that can fulfill enterprise performance expectations,” says Rye. “DeepCloud AI provides a revolutionary cloud architecture for decentralized applications.”

Integrating DeepCloud AI with Real-World Internet of Things Applications

Essentially, DeepCloud AI is a blockchain-based modular platform that extends to three key target areas: infrastructure as a service, application marketplaces, and a developer community. DeepCloud AI is built on the Ethereum blockchain. Following that, the model is divided into a dual-sided architecture, with network resource providers on one end and decentralized application developers on the other end.

In a mutually advantageous partnership, Rye explains, “Network resource providers supply computing and storage power to application developers, who in turn populate application marketplaces.”

One of the most important components of constructing a decentralized cloud infrastructure that may lower costs without sacrificing performance is the efficiency with which resources are allocated, which is managed by artificial intelligence in the DeepCloud platform. An overview of the AI can be summarised as follows: it is a matching algorithm for network resources that maps effective pathways to demands for those resources. In turn, edge devices (such as Internet of Things devices) receive efficient and consistent resource allocation, allowing them to tap into the enormous potential of increasingly networked devices and their protected, private data.

DeepCloud AI’s whitepaper explains how “we enable resource providers close to the edge,” such as retail shopping malls or apartment complex residents, to share the excess capacity of their computer resources on the decentralized cloud, close to city traffic lights, making it possible to do these local computations close to the source and enabling such use cases.” “With our artificial intelligence matching engine, we can match the appropriate resources to the appropriate applications based on real-time analytics of data from throughout the network.”

DeepCloud AI, by leveraging encryption and the upcoming SGX Enclave Computing technology, can also give such resources to edge devices securely and privately, without revealing sensitive user information. This is a watershed moment in the history of edge devices, which has been marred by security and privacy blunders in the past.

DeepCloud AI is already putting their network’s real-world IoT applications to work, and it’s not just any old use case either; it’s a joint initiative with the Mexican Federal Government, according to the company.

According to Rye, “We recently announced the creation of Mexican on the DeepCloud AI platform.” The Mexican Car IoT platform is built on our infrastructure and saves, records, and secures ownership and car registration information using our tamper-proof blockchain, which is integrated with the Federal District Government Transport and Highway Department in Mexico.

Car owners can utilize MexiCar for digital documentation to safeguard their vehicle registration, which can then be certified by third parties, such as the government and insurance companies, to simplify collision reporting and reduce the likelihood of fraud or corruption occurring. Mexican can overcome latency and connectivity issues in remote locations because it is built on DeepCloud AI, while also providing users with a censorship-resistant registry of their data.

The prototype is anticipated to be unveiled in the Mexican state of Coahuila in July 2019, and it will be developed in collaboration with the company Xilinx, which is a leading manufacturer of FPGA Accelerator Cards. DeepCloud AI can process massive computational loads at the edge with the support of Xilinx’s FPGA cards, resulting in a design that is friendly to autonomous vehicles and forward-thinking in its approach.

Ultimately, DeepCloud AI hopes to expand its decentralized cloud computing infrastructure beyond the Internet of Things devices and into other industries such as supply chains, smart cities, and television service providers.

“There is the possibility for significant disruption,” adds Rye. In the meanwhile, we must focus on execution as we get closer to Web 3.0 and a new version of the Internet landscape,” says Smith.