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DeviantCoin Website
DeviantCoin Whitepaper

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According to a recent JP Morgan report 90% of all Wall Street trading volume is attributed to automated HFT and Index Funds.1 Advanced learning algorithms have largely been the domain of trading banks and hedge funds that use AI as part of a larger strategy that employs a variety of trading tactics. Their types of models react to split second changes in relationships between different markets. The spoils go to the banks with the fastest models and the fastest execution that can take advantage of short term transient market inefficiencies. Because the markets traded are mature, the movements are usually minute, with huge transactions that drive correspondingly high profits.

On the other hand, cryptocurrencies are the brave new world of trading. The markets are relatively young and still very inefficient. It is not unusual to see bitcoins move 10% in a single day. In addition, due to size and potential regulatory conflicts, the cryptocurrency markets are largely shunned by established trading houses leaving the field open for dynamic young companies to take advantage of the opportunities in the markets. With market capitalization ballooning (cryptocurrency market capitalization has grown from $8.8bn to $80.6bn in the past year with no signs of a slowdown), the time is right for a dispassionate, selflearning trading engine to take advantage of an environment where less professional and less disciplined traders create many profit opportunities. Cryptocurrencies are obviously a natural fit for automated trading; the market volatility can be hugely profitable using AI-based trading and is rapidly gaining popularity. Automated trading is mainly achieved using scripts that need some coding experience and are devoid of GUI, or through one of about half a dozen commercial products requiring expensive memberships. Crypto trading may not be easy and sure-shot thing for everyone.

And, therefore we introduce AUTONIO

Autonio

Abstract

LiveEdu is a decentralized peer-to-peer project learning platform for people to improve
their job skills in future technologies. LiveEdu is building the YouTube for online
education and professional development and targeting the $306 billion professional
development market. We are taking one category out of YouTube and building it out into
a bigger category of its own. Just as Twitch took the category gaming out of YouTube
and built it into its own large vertical, LiveEdu is taking the category professional
development out of YouTube. The main participants in the LiveEdu network are project
creators, viewers, moderators, API developers, colleges, schools, libraries, businesses
and third-party online education companies. We are an existing business, with team
members from Amazon and Y-combinator. LiveEdu is building the world’s largest
project learning network starting with the eight topics: artificial intelligence,
cybersecurity, game development, data science, cryptocurrencies, programming,
design, and augmented and virtual reality. Our network will be all opened for all topics in
2019. We aim to develop a decentralized online learning network that is not reliant on
learning theory, but practical career skills by using real complete projects. Project
creators create educational projects and are paid monthly, lifelong royalty fees as
viewers learn from their projects. We are emulating the token model of Steemit and
applying it to LiveEdu. In this paper we explain the token mechanics for the blockchain
LEDU smart contract tokens and how we intend to fully integrate LEDU into the whole
product, internal and external ecosystem.

Education Ecosystem Website
Education Ecosystem Whitepaper

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