How a Machining Learning Platform Delivers Transparency to Crypto Investors [INTERVIEW]

Following the ICO fervor of 2017, investing in decentralized projects has become a highly cautious endeavor requiring immense scrutiny and research to avoid fraud. Integrating blockchain and machine learning, Decentralized Analysis System (DAS) aims to resolve the lack of transparency within the blockchain industry through a tokenized database powered by its users.

Co-founder Albert Lin shares his outlook on the future of DAS and its impact on venture capital firms worldwide.

Database Built on Blockchain, Machine Learning, and AI

Founded in 2015, DAS was originally a cloud-based data system that aggregated data from centralized resources to give investors and institutions access to sensitive company information. Over time, DAS became a platform serving a large portion of the venture capitalist market in China.

In an interview with BitcoinLinux, Lin stated:

“We have over 40% of all the venture capitalists in China using our system. We have over 800 hard copies of our software in use. We are a cloud-based platform, so we have over 8000 institutions using our system.“

According to Lin, the DAS Brain technology takes a unique approach to data collection through a combination of machine learning, AI and distributed ledger technology. This allows the system to offer detailed insights into an array of data points, including team formation, public opinion, and project code. Lin mentions that the DAS platform can also be used inversely for companies seeking funding from investors.

“We have been developing the system for 3 years, and we wanted the platform to be more than a software system so we combined the machine learning and AI technology on top of the system. So if you’re an investor and your doing a venture capital analysis and you want to get an updated report on a company, such as Uber, you can use our API to call information on Uber, including founder’s age, founder’s income, what he used to do before uber… It’s basically just a recommendation algorithm based on data gathered from updated information on companies. On the other side, we also recommend investors to the companies. So it’s a two-way recommendation algorithm.”

Transition to Tokenization

Following a successful early launch, Lin and his team quickly realized that the costs of purchasing data from centralized resources would be unsustainable, requiring nearly 60 percent of revenue to maintain. In 2018, DAS made a pivot towards decentralization and tokenized its platform – enabling users to input relevant company data in exchange for tokens.

“We can use a token system to pay the 60 percent back to the users who, after they get an incentive of tokens, can share their own data into our blockchain system, removing wasted capital to centralized databases… Most importantly, we want to pay our users instead of paying data resources. And with a token incentive algorithm running on our system, we can gather more testing data and motive more users into using our system, which trains our algorithm and makes it smarter.”

DAS currently offers industry insights and business forecasts on decentralized application (DApp) projects to individual investors and institutions worldwide. For more information on DAS, you can visit their website here.

The post How a Machining Learning Platform Delivers Transparency to Crypto Investors [INTERVIEW] appeared first on BitcoinLinux.

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