Original article by EVALUAPE

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A. Introduction

Hadron is a large-scale decentralized AI computing platform.

Advantages:

(1) The team has pioneering experience in building distributed platform.

(2) The beta test for mining has been launched.

Disadvantages:

(1) The white paper has not been disclosed, the community operation is inactive, and the development progress is unknown in the near future.

(2) The code is not open source.

B. Industry

The cloud computing market is now dominated by centralized cloud server providers, represented by Amazon’s AWS, which occupies half of the market. The distributed computing platform aims to take advantage of the redundant computing power of personal computer devices, and to seize the market and coordinate resources with price-centered superiority. Golem and RRchain are Hadron’s main competitors in decentralized computing offering. Compared to Hadron’s refinement on the market and the focus on AI calculations, it is Golem’s vision to provide a platform that can run all Dapps. But the corresponding technical adaptation is also much more difficult, so Golem’s recent destination is machine learning, which may, in the future, become a direct competition with Hadron. RRC chose Map Reduce in the short-term period seeking adaptation efficiency. In the AI market, a good support for GPU computing has been a key competency, while the difficulty lies in the collection, confirmation and trading of data. (7/10)

C. Mode

In terms of platform products, Hadron wants to establish an AI computing market, and provide a low-cost AI training platform through the scale of the userbase, so as to connect people in demand of AI computing power to available suppliers. In terms of the underlying architecture, Hadron establishes WorkforceChain to provide computing power and build the protocol framework into the browser. Any platform can realize the exchange of redundant computing power and tokens only by accessing the browser. The application scenarios of AI include image recognition and semantics recognition, etc. Highly concurrent tasks will be completed by different computing platforms through distributed computing, and new agreements will be approved through the equity voting mechanism. Some data sets will also be tokenized on the platform for buyers to purchase and rent.

The token Hadron Coin is used as the currency for the payment of computing power and transactions. The appreciation logic lies in the increase in demand for tokens on the platform. In the highly competitive market of computing power, Hadron focuses on certain application scenarios of AI, embedding a trusted environment architecture in web pages, which is highly feasible to implement. The shareholder voting mechanism of the protocol and the use of tokens have revealed the nature of decentralization, but more specific mechanisms for task distribution, rewards, and confirmation have not yet been clarified. (7/10)

D. Technology

Hadron adopts the DPOS model as its technology framework, in which the transaction and network information will be recorded in the block. The design principle is simple, clear and applicable. The Hadron platform now supports popular frameworks such as Tensorflow, and is widely used in machine learning. Hadron’s positioning is not for low-concurrency tasks, and there is no introduction to the task distribution mechanism. Source codes and technical details are not disclosed, and the official whitepaper has not been released, but the network beta version has been launched online, and ready for internal testing. The administrator disclosed that many companies including NASA telescope have been using the technical support provided by Hardron. (7/10)

E. Ecosystem

There are 7073 followers on Twitter, but the administrator has not posted any information for two months. There are 16724 people discussing on Telegram, and the administrator publishes product testing related matters within the group, actively answers the questions. Since the project has no crowdfunding plans, it has been understated for a period of time. Customers can apply for the Beta version test on Bitcointalk. (8/10)

F. Team

There are 9 disclosed team members who has rich experience in large-scale distributed system development, project management and entrepreneurship. About half of the team are technical engineers, but they lack experience in blockchain sector. The main members include:

Cliff Szu, CEO of Hadron. One of the co-founders of Fanpop, a million-level P2P lending network. Darick Tong, graduated from Stanford University, was a Google engineer and a founding member of Gmail, and he has extensive experience in large-scale distributed system development. David Papandrew, co-founder of Fanpop and Chief Product Officer, has 20 years of product management experience. (8/10)

G. Conclusion

Hadron is a distributed computing platform focused on the AI market. Among the similar projects, it stands out with its high degree of completion of the AI calculation adaptation. But as for the computing power market, the distributed platform of redundant computing power solves the problem of excess performance of personal devices. However, in the face of mature and highly utilized server providers, it is still a question that whether its only advantage — price can be achieved. The project team has a strong lineup and the test network usage has been proven mature, but the technical details have not been disclosed. The team is not keen on operation, resulting in the lag of information disclosure. The community mainly discusses its product and technology, and the style is more pragmatic.

Hype Score: Medium High

Risk Score:Medium

Expectation:High

Total Score: 7.5

All information in this article is provided for reference only and does not constitute investment advice.