Introduction
Blockchain technology helps us
meet many of AI’s current challenges. Using the blockchain, we can confidently
manage high-quality data labelling, security concerns, intellectual property
rights, and international micropayments. Using existing commercial computation
infrastructure allows us to build an affordable, scalable toolkit for
developing, integrating, and deploying AI apps.
We use blockchain protocols and an in-house cryptocurrency to power the AI production cycle. The SPOCK protocol validates data label quality, ensuring the most accurate datasets possible. The PICARD protocol ensures the security of confidential data and automatically manages relations and fair revenue distribution between stakeholders. Dbraincoin (DBR) is an ERC-20 cryptocurrency to exchange for work, datasets, and AI app usage.
Anyone with a connected device can join Dbrain and get a role in building Industry 4.0. Our platform connects exploding demand for hand-labeled AI data with the abundant supply of global crowdworkers. In particular, we reach 2 billion unbanked people in low-wage countries, offering them cryptocurrency income in exchange for data labeling and validation. Integrating this global workforce into its platform, Dbrain provides a secure, unified infrastructure to supercharge businesses through accessible, high-quality AI products.
Right now, AI is off limits to all but the wealthiest and most powerful operations. Dbrain makes AI affordable to more customers. We make AI buildable by more developers. We make AI profitable for more workers. We democratize AI.
Challenges
High-quality datasets
Large, high-quality datasets contribute more than 80% to AI
application success, making these data even more important for machine learning
than algorithms. Datasets are still labeled by hand and require a lot of human
effort. Regardless of size, poorly labelled datasets can nullify Neural Network
(NN) model function and impede AI progress in general. Leveraging the labor of
online crowdworkers is the most effective solution for creating large datasets.
However, existing data-labelling tools and platforms fail to ensure quality and
fail to meet the current demand for AI datasets.
Security and trust
Sharing sensitive data with third parties, and even in-house
developers, poses certain security risks. AI developers can replicate
third-party software within a very short time when given access to someone
else’s data. Labeled data, rather than software, are the defensible barrier for
many businesses. Data owners lose revenue when datasets are leaked to third
parties.
Abundant crowdwork supply
In the 10 largest developing countries, the total number of
internet users is close to 2 billion; with nearly 50% technology penetration,
the online population is growing rapidly. The number of internet users in these
countries is greater than in all other countries combined. At the same time,
the World Bank estimates that there are around 2 billion unbanked people in the
world. Clearly, internet connectivity reaches the developing world much faster
than the banking system, and many people connected to the internet are still
excluded from the global financial system. Cross-border payments via banks are
expensive, slow, and location dependent. Cryptocurrencies can solve this
problem by reaching any person connected to the internet.
Last-mile infrastructure
Even the most sophisticated AI platform is useless without
access to end users. To use AI solutions in the real world, businesses need to
find AI developers, the scarcest resource on the market. Developers need access
to scalable and affordable AI computation infrastructure to train and deploy
their AI Apps. They also need access to raw data and crowdworkers for data
labeling and model output validation. Labelers need simple, accessible
interfaces, and micropayment channels to be paid for their work.
Platform
AI production line
Dbrain levels the playing field
for all participants on the AI market.
For crowdworkers, we provide an opportunity to earn money for training and supervising AI networks and receive a fair share of future AI revenues securely via smart contracts. For AI developers, we lower barriers significantly for creating commercially viable AI products and provide scalable and elastic access to accumulated datasets, unique data providers, business clients, and a distributed pool of workers who create new and process existing data. We enable data providers to monetize their existing datasets and live data streams. For businesses, we offer a wide range of turnkey AI solutions, integration, and customization for particular needs.
Blockchain and crypto
The Dbrain platform works on the Ethereum network and relies on its smart contracts. We’re building a scalable permissioned blockchain anchored to the Ethereum network via state channels. Our solution can securely process thousands of transactions per second which all involved parties can verify independently. We implement two blockchain protocols for decentralized access to our platform and an in-house cryptocurrency.
The Dbrain platform works on the Ethereum network and relies on its smart contracts. We’re building a scalable permissioned blockchain anchored to the Ethereum network via state channels. Our solution can securely process thousands of transactions per second which all involved parties can verify independently. We implement two blockchain protocols for decentralized access to our platform and an in-house cryptocurrency.
SPOCK protocol
To align the incentives of
crowdworkers, validators, AI developers and dataset owners, Dbrain implements
the Subjective Proof of Crowdwork Protocol (SPOCK), which automatically
verifies data quality and guarantees real-time, fair and transparent billing to
workers and task requesters.
All work tasks performed on the Dbrain platform require multiple validations by other random labelers. Validators either do the same work for the simplest tasks such as image classification, or confirm the correctness of complex tasks. When the majority of validators agree on the task result quality, then the original worker receives a payment and a higher rating. Workers get a lower rating and no payment for rejected tasks.
We have several requirements for our rating and task validation
system to be able to process task completion and validation in real time:
Online calculations. We need to evaluate work results as
they arrive using only data stored publicly in our Ethereum smart contracts and
in our permissioned blockchain that is accessible to relevant task requesters
and workers.
Transparency. All rating changes and billing events
should be visible to task requesters and workers online.
Reproducibility. Calculations must be simple enough
that an involved party can reproduce them independently.
Aligned incentives. The system should motivate workers to
behave diligently and conscientiously by providing a good reward and punishment
balance.
PICARD protocol
The Protocol for indirect
controlled access to repository data (PICARD) protects datasets and AI applications hosted
on the Dbrain platform and allows data scientists to train AI models using the
datasets without downloading them, and to sell AI solutions to business clients
later. The protocol allows data scientists to work on a contract basis as well
as to contribute to community owned datasets and public kernels. It also allows
participation in Kaggle-like competitions on openly listed challenges.
Use cases
Image recognition
Image recognition (including classification and tagging) is one of the
most commonly applied AI use cases today. Image recognition is an area that is
developing rapidly and that will have a major impact on the consumer,
automotive, advertising, healthcare, defense, media, and entertainment
industries. People communicate in images, and images are essential for product
discovery nowadays. Businesses spend billions every year on repetitive graphic
design tasks.
Natural language processing
NLP is an AI application that recognizes not only formal content of texts, but also their sentiment and meaning. AI can also detect messages that signal dangerous situations, for example, a terrorist threat or suicide intention. Telegram is one of the leading messengers worldwide. It has more than 100 million active users and delivers over 15 billion messages daily. Telegram has recently been blocked in Indonesia by the government, which said that the messenger is "full of radical and terrorist propaganda". The developers of Telegram do not provide access to users’ messages to any governments or officials. Therefore, AI in combination with a human feedback loop is the only possible solution for content moderation.
NLP is an AI application that recognizes not only formal content of texts, but also their sentiment and meaning. AI can also detect messages that signal dangerous situations, for example, a terrorist threat or suicide intention. Telegram is one of the leading messengers worldwide. It has more than 100 million active users and delivers over 15 billion messages daily. Telegram has recently been blocked in Indonesia by the government, which said that the messenger is "full of radical and terrorist propaganda". The developers of Telegram do not provide access to users’ messages to any governments or officials. Therefore, AI in combination with a human feedback loop is the only possible solution for content moderation.
JOIN The Bounty Program at https://bountyhive.io/join/Dbrain
OR (bountyhive.io/join/Dbrain)
MORE INFORMATION :
Website: https://dbrain.io/
Telegram: https://t.me/joinchat/BSBzPk1gyw5grXyvBslXdg
Facebook : https://www.facebook.com/dbrainio
Twitter: https://twitter.com/dbrainio
Whitepaper : http://whitepaper.dbrain.io/
Authorized By:
My Bitcointalk account : jagadlangit
My ETH address : 0xA2BFa48A6AfEFaBF498B6541f609E6cef4700D91
Bountyhive referral link : bountyhive.io/r/juponkatana
