Researchers Using AI To Fight Against The ICO Frauds
Posted By : Anirudh Bhardwaj | 16-Mar-2018
Initial Coin Offering or ICO has turned out to be a game-changer when it comes to raising funds for a cryptocurrency project by means of crowdfunding. The Cryptocurrency market is a flourishing industry which is highly leveraged by ICO development companies given it is expanding exponentially. Seeing this phenomenal growth, every other person wants to invest in this transpiring domain. While most people go after trading in cryptocurrencies, there are also many who intend to build their own cryptocurrency platform. Of course, it’s going cost you a fortune and you may fall into a financial crisis unless you are very rich. Thankfully, you can leverage the benefits of crowdfunding by running ICO campaigns. However,
As a matter of fact, there is no subtle way to know if an ICO token sale is real or fake. Most of the times, people just end up losing their money when they get into the trap. As it turns out, a team of researchers is working on making a Machine Learning based research system which could help in detecting whether an ICO is real or not.
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Who’s Behind The Project
The project is initiated by a Chinese startup called Shannon.AI, an Artificial Intelligence-oriented company that focuses on creating smart AI algorithms to analyze and extract the information out of various financial resources. The company is working with the researchers from Stanford, University of California Santa Barbara and the University of Michigan. Lately, Shannon.AI released a white paper describing a new AI model that will focus on tracking down the cryptocurrency scams.
How These Incidents Take Place?
As it turns out, counterfeiting websites and white papers
How Shannon.AI Aims To Fix This?
Shannon.AI released a White Paper which outlines a Machine Learning model that will help in identifying the authenticity of an ICO. The project is called ICO Rating and it talks of a Machine Learning model to automate the tasks of an investor by extracting the publicly available information. The company proclaims that the new
First off, you need to feed in a lot of information to the ordinary rating systems which means it will have huge storage requirements. On the other hand, Machine Learning models are smarter and require less prior knowledge. They have the ability to automatically upgrade themselves based on user interaction. Plus, it can also help in reducing