It’s hard not to get excited about projects that utilize blockchain for the purpose it was intended for. Allowing a decentralization of information, hosted in a way where both data owners and customers can come together to maximize information and profits, is textbook blockchain decentralization, and why I’m excited about what Decentralized Machine Learning is building for blockchain enthusiasts.
One of the first things I noticed about Decentralized Machine Learning’s (DML) team is the abundance of developers and machine learning engineers. I have stumbled on other ICO companies in this industry that often times produce a large team, yet very few are specialized in the areas of machine learning. DML’s core team boasts Blockchain Developers, Software and Security Engineers along with Machine Learning Engineers. After looking over their Kyokan Labs Team and Advisers, I expected to find more Business Development and Marketing roles but was genuinely impressed to find yet more team members with tech backgrounds. This to me is always a confidence booster in what I am investing in. It shows that the company has fully committed to the development of their product and is relying on the technology to speak to the consumer, rather than a team filled with mostly roles in business development.
So what is Machine Learning and the importance of decentralization via the blockchain? Here is a link to the white paper for anyone that wants to get into the technical details White Paper, but for those new to machine learning, let’s break this down in simple terms. When you go on to a centralized service like Facebook, they are constantly collecting your data. You agree to these terms and conditions when you sign up and in return Facebook offers you a free social media platform to post pictures and interact with your friends and family. Every time that you are on Facebook, using their system, they collect data using machine learning artificial intelligence (AI). They then take this stored information and use it to help promote the right products and services, tailored to what consumer’s data they are able to retrieve. So if you have ever been shopping for a coat and all of a sudden see the exact coat you were looking for on Facebook, this is due to their machine learning AI. The downside of this is that you are not given any type of compensation for providing them with your data. The use of their site is essentially their payment to you. And for protocol customers (the people who will pay for your information) they are only getting a fraction of the information that you may have to sell, thus preventing both the customer from obtaining thorough information, and you, the data owner, from fully capitalizing on monetization.
How does DML change this? DML looks to make the process of both data collection and sales detailed and profitable, all while using blockchain technology so that no centralized service can be the unnecessary “middle-man.” Protocol Customers ( Companies, research, government,etc) will request specific information from DML’s Algorithm Market Place, this request will then be sent to the nodes via a smart contract and then sent out to devices that host DML’s apps(Data owners like you or me). This is how DML’s token will be a real use case currency: Protocol Customers will purchase $DML tokens and use these to pay for the data they are requesting. Data Owners will then be paid for running the DML app so that aggregated information can be retrieved. This data collection and sharing ecosystem revenue is predicted to be over 210 Billion dollars by 2020, so you can see how much of a demand there is for this industry and how much money data collectors are missing out on by allowing 3rd party vendors to access this information and in return keep the funds for themselves. For a detailed breakdown on how DML looks to run manage the project, check out this quick 3:30 video below.
DML has a total token supply of 330,000,000, with a target token sale of 28,000 ETH. To be added to the Whitelist, you must go through the typical KYC, the link for the signup is here: Whitelist. A detailed breakdown of the token distribution is below:
DML’s approach to making the ecosystem user friendly for the customers and collectors of data, will be appealing to both sides. Along with the business approach, tech wise, DML will build this platform on the Ethereum network, eventually adding multi-blockchain migration capabilities in the future, so that way other currencies can integrate within the system. Having the vision to expand beyond Ethereum is a positive sign as a lot of ICO’s are built on and lifelong dependent of ETH. Their algo marketplace is scheduled to be launched by June-July of this year and I really look forward to seeing what kind of UI they are able to put into place.
Projects like this are exciting to me. When I think of decentralization and giving people back the control of their data, this is exactly what I have in mind. Machine Learning and AI is still very young and will have many years of growth ahead of it. While there are other competing companies with similar projects, it’s important to allow such new technology to grow as much as possible. Much of what we do in the future will be dependent on these types of protocols and Decentralized Machine Learning will be one of the driving forces behind this technology.