Algorand is blockchain 4.0 after the dotcom bubble 2.0

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The proliferation of Information and Communications Technology over the last 30 years, has allowed us to witness an exponential increase in the use of a myriad in smart applications such as smart farming, smart healthcare, supply-chain & logistics, business, tourism and hospitality, energy management, and the list goes on. However, for all the aforementioned applications, security and privacy are major concerns keeping in view of the usage of the open channel, for example, the Internet for data transfer. Although many security solutions and standards have been proposed over the years to enhance the security levels of the aforementioned smart applications, the existing solutions are either based upon centralized architecture (having a single point of failure) or having high computation and communication costs. Moreover, most of the existing security solutions have focussed only on a few aspects and fail to address scalability, robustness, data storage, network latency, auditability, immutability, and traceability. To handle the aforementioned issues, blockchain 4.0 technology can be the ideal solution. Motivated by these facts, Silvio Micali, founder of Algorand presents a systematic blockchain based solution, applicable in various Industry 4.0-based applications. His contributions are absolutely paramount, short of disruptive.

Firstly, it's important to explore and compare the current state-of-the-art solutions in the blockchain sphere and the technology for smart applications. By illustrating the reference architecture used for the blockchain applicability in various Industry 4.0 applications, it's crystal clear to see who the sleeping giant and second mouse is. Algorand will be the one that gets the cheese.

Now according to Harvard Business Review, there are four dominating business models in today's rapidly smart and connectedly changing world that's learning to adapt much quicker than any expert previously anticipated.

Asset Builders: These companies build, develop, and lease physical assets to make, market, distribute, and sell physical things. Examples include WeWork, Tesla, Ford, Wal-Mart, and FedEx.

Service Providers: These companies hire employees who provide services to customers or produce billable hours for which they charge. Examples include United Healthcare, Accenture, Experian PLC, and JP Morgan.

Technology Creators: These companies develop and sell intellectual property such as software, analytics, pharmaceuticals, and biotechnology. Examples include Microsoft, Oracle, and Amgen.

Network Orchestrators. These companies create a network of peers in which the participants interact and share in the value creation. They may sell products or services, build relationships, share advice, give reviews, collaborate, co-create and more. Examples include eBay, Red Hat, and Visa, Uber, Tripadvisor, and Alibaba.

Algorand has positioned itself to be a Disruptive Technology provider for Governments to introduce their own CBDCs through 2022 and a Network Orchestrator for developers and entrepreneurs.

To mention a few Algorand was recently featured as a Symposium Partner and speaker at OMFIF and DMI.

What Blockchain technology is ready for Industry 4.0?

Not just to launch central bank digital currencies, but to meet smart contract demands through virtual machines in blockchain 2.0, be able to scale efficient DApps in blockchain 3.0, while at the same time lead the future as an infrastructure based Blockchain 4.0 ecosystem?

I can only think of Algorand. A triple AAA long term investment.
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Algorand Ranked Top 3 Worth Trillions: Altseason Roadmap
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This fractal has been very precise so far, be on the look out
December 2016 Trend: Consolidation followed by ALTSEASON
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Algo broke both the daily descending triangle and the 4 hour one as well, had a successful bounce on retest too, that's very bullish, if this is a fakeout it's a very good one
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Altseason has officially started
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Buckle your seatbelt Dorothy, cause Poverty is going bye bye!
algoalgorandALGOUSDTChart PatternsTrend Analysis

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