ICO Review: DML
This article will review the DML project (decentralizedml.com) and will be the first of a series of reviews. It was made by our team and will give our opinion on it: why we think it’s a bad or a good project.
What is DML and what problems are they solving?
Data quality and relevancy are essential to make further reliable analysis and generate usable applications of high quality. Thus, AI and Machine Learning algorithms need good data quality and accuracy as well as computer resources. The problem that many companies face when they need to make AI predictions is that they need not only computing power but also data analysts and of course the most important piece of the puzzle: the data itself. Owning or buying all these needed parts is very expensive. The high costs of asking for predictions prevent small or medium companies to use these technologies. Accessing data may even be a very serious problem because it’s majorly held by big giants like Google or Facebook. They could choose to keep it for themselves if they wanted to.
This is where DML comes in: By allowing billions of users to share their data — anonymously — on the network, DML is offering to solve for a reasonable price the very common problem a lot of small and medium-sized firms are facing: the lack of quality data in quantity.
DML protocol is a scalable decentralized infrastructure that aims to connect potentially billions of devices and developers to facilitate Machine Learning development.
How does it work?
DML is not just a platform but an ecosystem where you will find three interacting parties:
- Algo Marketplace: where developers can submit their algorithms and get paid when they are used. This encourages constant innovation and helps the ecosystem have the most up to date and precise technology.
- Decentralized Nodes: machines that anyone can host. They will run the algorithms and compute the predictions in exchange for tokens. They can be considered as miners.
- Multiple Devices: can be phones, tablets, laptops or desktop computers that will run the DML app (with the consent of the user). They will be able to convert raw user data to another type which will preserve the privacy of the user. It may be something like how many happy smileys can be found on your data, what colors appears the most, number of outdoor vs indoor photos… This will be fed to the algorithms to obtain precise predictions. Users who share their data will get some tokens in return. There will be no background or battery-consuming tasks here, the app will only run when the users wants it to (once per day for instance).
These elements will be connected with each other according to this workflow:
The team
2017–2018: Blockchain developer at DML
2015–2018: Co-Founder, CTO at Capheart
2014–2017: Co-Founder, Technology Director at OiKa
2011–2015: Analyst Programer at We Software Limited
2010–2011: C# Programer at NetAGE Development ltd.
2010–2010: C++ Programer at DoubleD Advertising Limited
Victor has more than a decade of programing experience. He’s been leading tech departments for 2 successful startups.
2017–2018: Project Lead Director at DML
2015–2018: Co-Founder at Capheart
2014–2017: Co-Founder at OiKa
2012–2015: Relationship Manager, Commercial Clients, Wholesale Banking at Standard Chartered Bank
2011–2012: VP, Relationship Management, Commercial Banking at Hang Seng Bank
2007–2011: Financial Analyst, Corporate Banking and Financial Institutions at Bank of China
Michael has extensive knowledge of the banking industry. He now focuses on business development, branding, marketing and community management.
2017–2018: Software Engineer at DML
2017–2018: VP of Engineering at Kyokan
2016–2017: Software Engineer at Uber
2015–2016: Frontend Software Engineer at Secure Seamless Communication
2011–2014: Lead Accountant at Vine Solutions
2009–2011: Personal Banker at JPMorgan Chase
Jacky has acquired programing experience in top companies and has technical knowledge of the blockchain.
2017–2018: Machine Learning Engineer at DML
2013–2018: Project Manager at Playbasis
2011–2013: IT Manager at Sandbox Global
2009–2011: CTO at Alkia IT Services Co., Ltd.
2001–2009: Technical Project Manager at Alcatel-Lucent Enterprise
1999–2001: Software Engineer at OSIS
Pascal is experienced both in the technology and managing fields. He is an expert in ML.
Other members have experience in software and blockchain development.
Token Metrics
Max Cap: 28 000 ETH
Token Type: ERC20 on Ethereum
Total Token Supply: 330,000,000 DML (100%)
Token Distributed to Public: 178,860,000 DML (54.2%)
Token Available for Sale: 118,800,000 DML (36.0%)
Token Price: 1 ETH = 3,780 DML
Our Opinion
We are bullish on this project for multiple reasons:
- Good idea: We didn’t find any other idea that solves the problem of data. For instance, if you read the white paper of Endor, you will find that they are just saying that some IT guys will upload the data (which makes it less decentralized by the way).
- Good Technology: The ecosystem is designed in ways that will make the predictions very precise. There will be an algorithm to answer every question.
- Good Team: The team is good, competent and has already ran businesses.
- A fair amount of telegram members: 9200
- Low Cap : 28 000 Eth
Some points that may need to be dealt with:
- Partners: Even if they are building an infrastructure project, they may still need to get some partners on board to be able to face future challenges. But it’s still acceptable to not have partners for this type of project.
- There’s no prototype already developed but the whitepaper is dense enough from a technical standpoint to prove they know what they’re doing.
Our Grades
As we said before, the project looks interesting and we are very bullish on it:
- Long Term: 9/10
- Flipping: 7/10
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Lotfi Zouad Community Manager & Reda SABIR Technical Advisor