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ASTRA is a revolutionary project which aims to integrate the computing power of the world’s billions of computers and devices into a single supercomputer with massive computing capacity running into exaFLOPS in processing capacity and with storage capacity in zettaFLOPS. The project intends to seamlessly combine the computing capacity of these devices to enable researcher access to much needed high computing capacity, while compensating contributing entities whose devices are part of the network.
The Astra native token STARs will be the internal currency of the ecosystem. Contributing entities earn social rewards and consequently they are incentivized to contribute their computing devices to the project. The Astra project is anticipated to help researchers in specialized fields such as Subatomic Physics, Medicine, Astronomy, Machine Learning, Genomics, Materials Science, Humanities and other fields that need unlimited storage and computing capacities.
The Astra Supercomputer also has the objective of building and supporting Trust Machines, especially social trust machines which would ensure transparency in governance, create efficiency in economies and enhance corruption-free operating systems.

Target Markets

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Researchers generally need large computing and storage capacities to work effectively. This is due to the fact that most of their works are data-driven. The need to collate and study large amount of data and quickly choose a promising path makes the computing and storage need of research immense. As various fields advance, the need for data storage will grow more in the future necessitating massive supercomputing capacity such as Astra.
High compute and storage need arises from trust machines developed to enable publicly auditable trustworthy data repositories. These trust machines with their trustworthy data makes it possible for people to cooperate with others whom they’ve not met before. Trust machines however require numerous copies of a piece of information or data to be constantly synchronized in communication intensive operation and needs high compute enhancement to perform efficiently.
Insight into massive amount of data involves analysis to understand patterns of this big data. Due to the continuous streaming of big data, it is practically impossible for this process to be undertaken efficiently by humans. This is the genesis of the evolution of machine learning in which mountains of repetitious data are fed to machines so that they can automatically learn the patterns and intelligently use the learning to respond to future events. Continuous streaming of big data with which machines are trained requires large compute, storage networking resources which requires immense capacity supercomputer to meet.

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Website: https://www.goastra.network/

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Unlike existing sharing networks that require that contributors’ devices download needed software to activate the utilization of their terminal equipment, the Astra project makes use of an intuitive interface that connects with the numerous sharing networks excluding the need for arrays of software and necessary switching from one to another.
ASTRA utilizes an easy-to-use interface that enables users to switch easily to a preferred sharing platform without technical challenges. The migratory option is to enable ‘donors’ of devices maximize their earnings in digital currencies for their contributions to the computing network.
The project creates an effective monetary system that incentivizes the global network in the form of virtual coins and tradable assets. The community is encouraged to be interactive and economically profiting even as end users can utilize the platform to build and launch a distributed computing network.

Astra Introduction Video

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ASTRA [STAR] Token Pre-Sale Soon

Additional Information

Website: https://www.goastra.network/
WhitePaper: https://www.goastra.network/whitepaper/

BitcoinTalk [Ann]: https://bitcointalk.org/index.php?topic=4430682
Telegram: https://t.me/joinchat/GNbSLAxLtSll3H0yjkpPFw

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Article written by @justiceforall

Bitcointalk user: Mr.Ease
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