Using the Blockchain for AI and Machine Learning
The rise of cryptocurrencies: from their inception with the likes of Bitcoin, to date have been astronomical overall. This comes despite hiccups such as impending regulation, price volatility and hacks, all of which challenges their viability as stable form of tender.
Traditional financial institutions — including prominent investment banks and wealth management firms have finally acknowledged the significant role cryptocurrencies are likely to play in the future, based on their market trajectory. One such example is JP Morgan, whose acknowledgement came only this year, in early February, when they which published the 70-page report entitled the ‘Bitcoin Bible’.
The Decentralized Solution that FinTech didn’t know it needed
Decentralized blockchain technology has lowered the barrier to entry for technological experts and investors across the world to either purchase or provide currency and / or services worldwide; avoiding the traditional restrictions posed by existing centralized industries. Just look at the founder of Ethereum Vitalik Buterin, who is currently only 24 years old — as well as the average age and growing population of “bitcoin millionaires”.
We at TradeRiser believe that the financial data analysis sector is under developed, especially when it comes to the cryptocurrency community. With the demands for traders to diversify their portfolio especially in the retail sector our technology will help to address this need.
TradeRiser’s Solution
With the rise of artificial intelligence across the board, TradeRiser is looking to bring financial data analytics to the masses through natural language questioning and answering. This is achieve through the following means:
Firstly, the ‘Research Assistant’ is an AI based questioning and answering system. It combines machine-learning algorithms to resolve natural language questions, furthermore it conducts analytics on the dataset from which the question is based on. The data and level of analytics will be significantly improved with the more data it is trained on. It is for this reason that the financial analysts will be taking part in an ecosystem that will exist to improve and support the technology.
When the Research Assistant reaches maturity it will be like Siri or Alexa but one that focuses on financial and investment trading based queries.
The second USP is the ‘Research Marketplace’: a place where financial analysts and content producers can create articles and reports. They will be able to do so using data and queries from the Research Assistant which they can feature within their articles. These articles can be sold and bought within the Research Marketplace.
Both system will be supported and maintained using a token-based incentive economy called XTI.
An Open Infrastructure Platform, for Financial Data Analytics
TradeRiser (much like Ethereum, upon which it is based) will act as an infrastructural platform upon which other developers and entrepreneurial groups can build their own financial analysis solutions;
Utilising the Research Assistant AI’s ground truth in their own developments via an API.
In this sense, the machine learning AI ‘Research Assistant’ service can be fully integrated with existing systems utilised by either individual traders. Furthermore by utilising the API: solutions such as the processing of mass data calculation queries can be resolved by professional and amateur investors in order to greatly speed up productivity in their investment research — amongst many others.
To find out more about TradeRiser, check out their website — as well as their social media channels (Twitter / LinkedIn). You can also see their tech in action by signing up for their Alpha
