Quadrant Protocol ICO

Major tech companies have actively reoriented themselves around AI and machine learning: Google is now AI-first, Uber has ML running through its veins and internal AI research labs keep popping up.

They’re pouring resources and attention into convincing the world that the machine intelligence revolution is arriving now. They tout deep learning, in particular, as the breakthrough driving this transformation and powering new self-driving cars, virtual assistants and more.
But at which specific situation are we going to use ML or AI in or daily life, you may ask. But the real question is, which applications are you using in your daily life that contains Machine Learning or AI algorithm. Because ML and AI are in our daily life already. The only thing is they needed to be worked on more, to be able to be more useful.

Today, an AI and ML contained programs can
Recognize objects in images
Navigate a map of the London Underground
Translate between languages
Recognise emotions in speech
Fly a Drone
Discover new uses for existing drugs
The list can go on and on. I just wanted to pick the most interesting ones, but if I write here the ones that I know or like to use, you may never read this post due to the situation that it never ends. But the fact is, the things that AI and ML can do today is only the beginning of the tunnel. There are tons of applications we may ask for help from ML and AI.

Well, you may get the idea that why Facebook, Google, Amazon kind of huge companies are working on AI and ML with almost full power. Obviously, ML and AI will shape the future for us. But you may notice that there are only a few companies who work ML and AI projects.
So apart from the long list that we can do today with AI, and despite this hype around the state of the art, the state of the practice is less futuristic.

We need small players too in the field. Lack of data and access difficulty of it making small players to step back. And when they find the necessary data, being unorganized is forcing them to spend more money to make it organized. Their newly formed strengths are not enough for them to pay for the data or making it organized. Which is why the industry lacks a new perspective. As in every situation, while small players easily spotting the daily problems better, big players are focusing bigger problems. Which forces us to wait for them to see those big players to see daily problems.
To provide needed info to small players, blockchain based initiatives must define proper and precise strategies to democratize data.

What is Quadrant Protocol
As in their description, Quadrant is a blockchain-based protocol that enables the access, creation, and distribution of data products and services with authenticity and provenance at its core. The data economy is similar to space; unmapped and chaotic. Quadrant serves as the blueprint that provides an organized system for the utilization of decentralized data.
Right now data economy is disorganized and little known. Quadrant promises a properly organized system that will facilitate utilization of data which is decentralized. Quadrant Protocol creators believes that data has to be accurate and original in order to improve its economy. The company claims to have a simple yet effective tool that proves data integrity. To enable the exchange of services like DaaS and Al between organizations, the company provides the infrastructure. It facilitates the selling of data by data vendors based on contracts. At the same time, it enables the buyers to purchase it and also provide them the added facility of tracing data’s accuracy. Here, data stamping verification procedure comes in handy.
Quadrant envisions itself creating a promising future for the quality, transparency, and authenticity of the data received by AI companies, helping them create insights and services that have far-reaching effects.

Which is why we can call it a blueprint for mapping decentralized data.
Features of Quadrant Protocol
Data Stamping
They stamp for authenticity, allowing data buyers to trace and have proof of who created the data.

Constellation Creation
They are daring Pioneers to venture, enabling them to create the first Data Smart Contracts and are deployed to create new data products
Enriched data and services
They are empowering the brightest minds to work on creating Mega Constellations - new products and services on top of Quadrant.

Business Cases
Quadrant maps disparate data sources so that new, innovative data products can potentially be created to help companies meet their data needs. This is intended to be made possible through the participation of the following stakeholders:
Nurseries— the Atomic Data Producers (ADPs) that create the original data records. They create Stars (raw data), which can then be grouped into Constellations.
Pioneers— the Data Vendors that create data products with the smart contracts on Quadrant.
Elons— the visionaries that utilize the created data products and with them, build new and unique products and services. They rely on Constellations and Constellation blueprints to make sense of the data space, which they will travel through.
Guardians— the master nodes that protect the integrity of the chain, ensuring that it is not compromised. The Guardians ensure that the Constellations created by the Pioneers are not compromised and provide the services of stamping, authenticating and verifying data.
ICO Metrics
Here are the token metrics for Quadrant Protocol.

Ticker: EQUAD
Token type: ERC20
ICO Token Price: 1 EQUAD = 0.0500 USD
Fundraising Goal: 20,000,000 USD
Total Tokens: 1,000,000,000
Available for Token Sale: 40%
Accepts: ETH

Website: https://www.quadrantprotocol.com
Telegram: https://t.me/quadrantprotocol
ANN Thread: https://bitcointalk.org/index.php?topic=3676988.0


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