QUADRANT PROTOCOL-ADDRESSING ISSUES WITH DATA AUTHENTICITY

Have you ever thought of the essence of intelligence that distinguishes intelligent systems from non-intelligent systems? If there is, then what is it? This article suggests an answer to these questions by introducing you to some peculiar ideas. The essence of intelligence is the ability to adapt with insufficient knowledge and resources. According to this belief, the author has designed a novel formal logic, and implemented it in a computer system. Such as “logic of intelligence” provides a unified explanation for many cognitive functions of the human mind, and is also concrete enough to guide the actual building of a general purpose “thinking machine”.

OVERVIEW

There has been a huge amounts of real data that are needed to power today’s algorithms, however the current data economy is troubled with challenges. There is an ever-widening gap between those with the resources to collect and store their own data and those that do not. The data these have-nots do have access to be often fragmented and of questionable authenticity—the kind of data that produces poor results when fed to algorithms. Part of the reason why the data lacks authenticity is because the suppliers of it are not properly incentivized. Fair revenue distribution does not exist for both data producers and vendors. Without a healthy and transparent data economy, the increasing demand for authentic data will not be met.
The Quadrant Protocol foresaw as a blockchain-based network protocol that enables the access to, creation and distribution of data products and services with authenticity and provenance at its core. It is envisioned to act as a blueprint that provides an organized system for the utilization of decentralized data. Quadrant maps disparate data sources so that new, innovative data products can potentially be created to help companies meet their data needs

** Problems Facing Data Economy**

1. Gaping AI data gap between the haves and have-nots
2. Universal fake and unauthentic data destroying the usefulness of any algorithm
3. Untenable data feeds breaking production systems when they go offline
4. Partial revenue distribution for the original data producers

VISION
Major aim of Quadrant is to solve these problems by providing a blueprint for mapping disparate data sources. It will support proof of data authenticity and provenance via data stamping, the creation of “Constellations” (data smart contracts) for disparate data sources, and fair remuneration and incentive sharing. Data Consumers can trust the authenticity of the data they purchase, “Nurseries” (Data Producers) are compensated fairly every time their data is used, and “Pioneers” (Data Vendors) have the incentive to create innovative Constellations. This new transparent ecosystem ensures that companies get the authentic data they need.Whitepaper

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Author: Kapee

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