GNY Launches Range Report

March 9, 2021

Combining the security of blockchain with the power of machine learning to help solve large and complex problems, GNY today opened public access to the world’s first blockchain that provides secure access to hundreds of on-chain algorithms.

Aiming to transform the way businesses and organizations share, collaborate, and analyze any kind of data, GNY’s Mainnet enables users to share their data on a blockchain architecture and use GNY’s machine learning services without risking sensitive data theft. It can then be used to analyze all kinds of data from financial records to public health information.

The launch comes after 18 months of development and rigorous testing. To demonstrate its potential impact, one GNY test revealed how researchers could use Mainnet to set up a private blockchain to run comparative analysis of daily COVID-19 mortalities from individual cities. Another test showed how the platform could be used to fight climate change by analyzing multiple sets of public and private data to predict when peak fossil fuel consumption will occur.

According to Cosmas Wong, the CEO of GNY, the platform represents a major step forward in efforts to make the power of machine learning accessible to organizations and groups of any size.

“Machine learning can be a force for good for solving the world’s most pressing problems, innovating industries, or simply growing a business, but it needs to be accessible, cost-effective, and secure,” says Wong. “Our goal is to democratize machine learning so that anyone can leverage all the opportunities made possible with this powerful technology.”

On GNY’s Mainnet, data is never stored in a central location, ensuring hackers have no server to attack. GNY’s machine learning platform processes the data where it is directly on the chain and shares the results back with the client. This means users worry about neither the data security nor the machine learning algorithms, as GNY offers both.

To ensure that the platform produces high-quality results, GNY’s machine learning technology and data diagnostic service prepares or “cleans” data for analysis, helps select which algorithms provide the best correlations, predictions and results, and then helps deploy those results to guide future actions.

“GNY’s level of data preparation is not to be underestimated as we know that clean results require clean data,” says Wong. “No other blockchain or machine learning project we know of offers this level of quality assurance.”

Customers access GNY’s Mainnet through a personal hub, known as the Webwallet, where they can use all of the on-chain functionality – from launching their own token to running machine learning contracts to voting for delegates. Webwallet breaks new ground with SwapGate, a first-of-its-kind feature which allows individual token holders to transfer from one token to another outside of an exchange.

Wang noted that in an industry where many blockchain projects raise significant money but fail to deliver, GNY stands out as Mainnet’s launch meets the deadline that the company laid out in its 2018 Initial Coin Offering.

In the coming year, Wong said the company plans to add dozens of additional features including the first-ever decentralized neural net where computation can be done across many machines as opposed to a centralized computer. It will also launch the GNYDataplace, which will introduce quality control and tested machine learning to the concept of data marketplaces.

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