Magos - Edge-seeking Oracle

Our vision is to combine highly accurate forecasting ability of Neural Networks with blockchain technology. MAGOS fund, managed by AI and supervised by our team, will be deployed on the Ethereum platform. Initially operating on prediction markets and sportsbooks, it will evolve and expand into other fields, such as Digital Asset Management, where the forecasts of MAGOS will be applicable and valuable.

STO/ICO Status

Status
Successful
Symbol
MAG
Start Date
2017-08-16
End Date
2017-09-30
Amount Raised
3,497 ETH
Soft Cap
3,400 ETH
Hard Cap
22,640 ETH
Token Supply
38,595,000
STO/ICO Website Owner of Magos?
Claim this listing and publish updates.

Basics

PlatformEthereum
TypeERC20
AcceptingBTC, ETH
Circulating SupplyN/A
KYCN/A
Restricted AreasN/A
HomepageWebsite URL
White PaperView/Download

Bonus

  • < 3000 ETH - 1995 MAG/ETH
  • 3000-6000 ETH - 1875 MAG/ETH
  • 6000-9000 ETH - 1800 MAG/ETH
  • 9000-12000 ETH - 1725 MAG/ETH
  • 12000-15000 ETH - 1650 MAG/ETH
  • 15000-22640 ETH - 1500 MAG/ETH

About

MAGOS is a complex AI forecasting model, based on a collaborative system of neural networks. It serves as a core for a fund that operates on Ethereum blockchain. By using the latest developments in AI and neutral networks, MAGOS is able to forecast the outcome of an event with a high degree of accuracy. The model was open tested earlier this year, and showed a significant forecasting edge that anyone can verify. This edge is used by the fund to generate profits from multiple platforms, including prediction markets. Share of profits is distributed between the holders of MAG tokens. The backbone of MAGOS is its modular architecture. It allows the development and implementation of individual forecasting modules, targeting different kinds of forecasting domains, from business and finance to sports and politics.

Team View All

Ante Magnusson
Ante Magnusson
CEO, Co-Founder
Andreas Theiss
Andreas Theiss
CTO, Co-Founder
Daniel Kim
Daniel Kim
Data Engineer
Isaac Welch
Isaac Welch
Solidity Developer
Christopher Davison
Christopher Davison
Sports Statistical Analyst
Kim Seung Ho
Kim Seung Ho
E-Sports Advisor