Powerful machine learning (ML) requires robust data and precise responsive algorithms. The GNY platform was designed to provide businesses with all of the ML tools they need to prepare data, analyze it and generate pioneering predictions. However, that is only half the equation.
LML is relaunching to provide all of the connective tissue required to harness powerful datasets from external sources including leading data oracles and APIs, and bring them into the GNY Dataplace. As the complementary data aggregation toolkit to Dataplace, LML will provide businesses an impressive toolkit for data collection, aggregation, crowd sourced data and data sharing that will in themselves create new economies.
conduct opinion and observation-based research and reward contributors for doing so.
gather true crowd sourced opinions and observations from smartphone and computer users around the world
geotag data submissions, with user consent.
create NFC tags that a contributor can scan to load a particular survey to their cell phone.
monetise gathered data in order to incentivise and reward the people who contribute it.
create a decentralised tool to provide simple probability distribution modelling in order to flag outliers and assign indicative probability scores to submitted data.
be able to create smart contracts that are triggered by a pre-identified outcome of a particular gathered data set.
embed incentivized browser plug ins for voluntary compensated data tracking
Using the LML toolset, companies, students & research organisations will be able to capture public opinions on any subjects of interest to them. For example, a company wishing to test the water for possible future product developments would be able to harness the wisdom of the LML user base to ask questions about how useful a future product might be to them and reward the LML users who participate.
The power and capabilities of any Machine Learning system depend on the quality, diversity and veracity of available data. The LML toolset will promote data diversity by providing connectors from outside data sources to the LML and GNY data realms.
For example, using the LML DOA toolkit it will be possible to import datasets from third party repositories for use with LML and GNY machine learning and to write conditional smart contracts that could be triggered by values such as Ethereum price or market capitalization value fed from the Coinmarketcap API.
If the data exists, LML will be able to bridge to it and allow you to harness the power of LML and GNY machine learning to utilize that data to its full potential. From harnessing the data from IoT mesh networks to pulling data from historical weather almanacs for climate modelling, LML will be the link to the data you need.
“The wisdom of the crowd” is the theory that the collective opinion of a group of individuals is in some cases superior to the opinion of an individual expert. The effectiveness of WotC varies depending on a wide range of factors but when done right it is a powerful tool to use. The LML toolkit will allow companies and individuals to crowd source data and opinions from the LML user base so that they can be fed into the LML machine learning system to make informed decisions about the likelihood of future events happening.
One example of this would be a company asking for opinions on future Bitcoin price movement to harness the collective opinion of a large group of LML users with knowledge of chart analysis. The LML model would allow a company to do this and reward LML users for their participation. To take this concept further, a company could create a service using LML so that LML users can trade smart contracts between each other on the probabilities of various events occurring in the future.
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GNY ERC-20 contract code:
GNY ERC-20 contract code: