How AI and Automation Can Help Crypto Investors Trade Better

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Hundreds of new cryptocurrencies have been created and offered to investors through initial coin offerings (ICOs) over the past year. Millions of new users entered the crypto space in 2017 during this ICO boom. More are jumping on the bandwagon this year. Most people who've heard of cryptocurrencies – and many who have put money into it – only have a vague understanding of how these work as investment vehicles. Confusion among new investors has been high due to the abundance of coins and their fluctuating valuations.


Blockchain Projects Are Rising to the Challenges of Big Data

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Big data, the data sets that are too large even for standard data processing software, is set to become even more prevalent over the coming years, with forecasts that the market will more than double within a decade. And with that growth will naturally come challenges. Securing and interpreting such large amounts of information is no easy task, which is why many see that blockchain technology is poised to grow in lockstep with the advent of big data. Businesses are rushing to embrace big data due to its power in helping them make smarter decisions. According to EY, data analytics "has become the key to corporate competitive advantage" because of its role in identifying emerging market trends.


Transforming Big Data Processing Through Blockchain and AI

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Big data is currently on everybody's lips with stringent regulations the order of the day and security breaches happening on a regular basis. A company called Endor has come up with a blockchain and AI based solution to manage and process data. After years of research at MIT, Endor claims to have invented the "Google for predictive analytics*", providing automated AI predictions for companies. Endor can process Encrypted Data, without ever decrypting it, on and off blockchain and it enables business users to ask predictive questions and get automated accurate predictions. No data science expertise is required.


Inventing the "Google" for predictive analytics

MIT News

Companies often employ number-crunching data scientists to gather insights such as which customers want certain services or where to open new stores and stock products. Analyzing the data to answer one or two of those queries, however, can take weeks or even months.