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Neuroseed

Decentralized Marketplace for AI Solutions

NeuroSeed is a platform that combines Big Data suppliers, ML algorithms developers, computing power suppliers, data storage suppliers, validators with domain expertise, distributors and customers. As a result of a synergy there is a creation of the unified ecosystem that provides incentive mechanisms for all participants in the machine learning market.

3.6
1 0 expert ratings
Benchy 3.6
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Starts in 9 days 23 hours
2018-06-05 - 2018-07-05
Token
NSD
Price
1 NSD = 0.04 USD
Bonus
Available
Platform
Accepting
ETH, BTC, DASH, LTC
Soft cap
42,000,000 USD
Hard cap
70,000,000 USD
Country
Whitelist/KYC
None
More on ICO
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About Neuroseed

The Fourth Industrial revolution brings the implementation of such technologies like Big Data, Internet of Things, Virtual Reality, Augmented Reality, Machine Learning and Artificial Intelligence. Current market requirements are changing rapidly and use of machine learning algorithms based solutions can significantly increase business competitive advantages in the context of globalization. Back in 1995 on “Neural Information Processing Systems Workshops” an idea of creating a platform that could provide a reliability of data sources and trained neural networks has been declared. Platform implementation would lead to the rapid development of the whole stack of machine learning based technologies and help to reduce the cost of its development, mass adoption and significant growth of derived systems efficiency. The concept of rationality of several machine learning models merging with their further transfer learning has been proposed and proved later. The common limiting factor of development and implementation of similar systems was the lack of reliable technology that could provide a decentralised digital trustworthiness for final machine learning models and data sources.

NeuroSeed platform solves this problem by means of combining cryptography and blockchain technologies and providing a reliable tool for creation, validation, trading and reusing of datasets and uniform reusable clusters of final machine learning models.

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