Decentralized Machine Learning
DML is looking to use Machine Learning to generate an unbiased and accurate crowd sourced analytics and predictions. The protocol is designed for providing economic incentives and protecting data privacy. It is designed to reach untapped private data and unravel potential to enable machine learning development. With this, both the private data and processing power for machine learning are decentralized as algorithms and they’re run directly on individual devices by utilizing their idle processing power.
• DML is looking to reach the goal of creating a block-chain based decentralized machine learning protocol and ecosystem. And for that, they’re utilizing untapped private data for machine learning while protecting data privacy.
• They’re connecting and leveraging idle processing power of individual devices for machine learning.
• Also, encouraging involvement from the periphery by creating a developer community and algorithm marketplace that promotes innovation to build machine learning algorithms that match practical utilities.
• The team is improving and correcting existing machine learning algorithms and models through crowdsourced fine-tuning model trainers.
• Its creating a new utility token for DML and leveraging it on blockchain smart contract technology to provide a trustless and middle-man free platform that connects potential contributors in machine learning from all aspects.
DML and its Market Potential
• Application of Big Data for Machine Learning
• Huge Market Potential in Existing Data
• Unlock Massive Market Potential of Untapped Private Data
• Utilize Decentralized and Idle Processing Power
• Unleash Creativity to Build ML Algorithms and Models with Practical Utility
Solutions
• Apply Decentralized Algorithm & Data for ML Prediction
• Deploy Machine Learning Algorithm for Practical Prediction
• Customers Acquire Algorithms from Marketplace
• Use of Smart Contracts to ensure Governance among Users
• Decentralized Architecture via Decentralized Node Deployment
• Distribute Algorithm to Eligible Devices
• Distributing Node to Identify Devices for Algorithm Distributions
• Auction Mechanism to Prioritize Machine Learning Sequence
• Run Algorithms on Eligible Data Owners’ Devices
• Run Algorithms directly on Devices without Data Extraction
• Deploy Algorithms on Individuals’ Authorized Dataset
• Share Encrypted Prediction Results without Data Extraction
• Federated Nodes to Aggregate Prediction Results
• Average Prediction Results by Federated Learning
• Validate Prediction Result Quality against Requirement
• Report Node to Produce Final Report & Store in IPFS
• Prediction Report Retrieval and Smart Contract Execution
• Improve Existing ML Algorithm via Crowd Informed Fine-tuning
• Distribute to Voluntary Trainers for Algorithms Improvement
• Adaptive Test Approach: Common data as Control Group
• Federated Node to Aggregate Weighted Fine-tuning Update
• Algorithm Refining Node to form Fine-Tuned Algorithm
To facilitate the DML ecosystem, smart contracts are utilized free of middlemen as a trustless tool. It is in perspective of the following people
• Customers:
Customers, who request for machine learning service, to pay DML tokens to run machine learning algorithm on data owners’ authorized dataset in their individual devices. The decentralized nodes will facilitate by distributing algorithms and collecting, aggregating and averaging the local prediction results to produce the final prediction report.
• Machine Learning Developers:
Machine learning developers, who sell their algorithm on the DML Marketplace, to get paid by customers in DML tokens.
• Model Trainers
Model trainers, who correct and improve the machine learning model, to be rewarded, by the customers or machine learning developers, who solely want to improve their algorithm for further use.
Blockchain Based Smart Contract
• Smart Contract for Machine Learning on Untapped Data
• Smart Contracts for DML Marketplace Activities
• Acquire ML Algorithms for Self or Business Predictions
• Crowd Fine-tuning to Improve Existing ML Algorithms
Benefits
Unleash Creativity via Innovation from Periphery
DML Algorithm Marketplace creates a developer’s community where developers have the capacity to work as a freelancer to build and market their machine learning algorithms in return for incentives. Innovation and creativity to build machine learning algorithms are unleashed as no approval by tech giants or any other parties with vested interest is needed. Better algorithms can be developed and evolved due to open competition in a free market ecosystem.
Open Market to Sell Machine Learning Algorithms
DML algorithm Marketplace provides developers an alternative mean to market their algorithms to potential algorithm buyers in an open market that are free from middleman control and costs. The transaction will be executed in smart contract with clear written terms and free from default risk.
External Source to Fine-tune Machine Learning Algorithms
Through DML Marketplace, developers have additional means to connect with numerous individual devices owners who can support the manual exercises to fine-tune the algorithms and trained the dataset without the need to hire in-house limited resources. This is another breakthrough and improvement in machine learning by connecting and engaging model trainers in the crowd.
Unlock Economic Value of Private Data with Privacy Protection
Through DML Protocol, the economic value of the private data is unlocked. Data owners are incentivized to allow machine learning algorithms to run on their private data in return of DML tokens without leakage of their private data to any third parties. Data privacy is protected as only the prediction results will be collected and aggregated through the decentralized nodes while the original source of private data will be kept within their individual devices. Therefore, data owners can participate in the machine learning development with economic incentives while data privacy concerns are addressed.
Make Use of Idle Processing Power
DML sees exponential improvement in processing power in smart devices with dedicated chips for on-device artificial intelligence and machine learning. While we usually do not actively use our devices 24/7, the underutilized processing power can now be used to run machine learning algorithms and be rewarded along with the private dataset usage.
Certain Data and Device Owner also acting as Model Trainer
While DML protocol design aims to run and make prediction in a hassle-free and automatic way to encourage mass participation, some data and device owners may be interested to walk an extra mile by acting as model trainers through correcting the labels of the machine algorithm in their spare time. The effort contributes to the machine learning development and earn extra DML token.
Reducing the Bar for Applying Machine Learning Algorithm
DML Algorithm Marketplace creates an open market that is available for anyone to acquire machine learning algorithms at a market-driven cost that are free from middleman control and costs. As a result, even small and medium enterprises, research institutions or even individuals may also be able to afford accessing talented resources from all over the world and acquiring the algorithms for business predictions or other usages at a market-driven cost. Furthermore, customers can request tailor-made machine learning algorithms for specific predictions without going through a middleman, if the algorithm required is not in the current list or does not match the exact required criteria. As such, the marketplace could always meet the latest demand in the market.
Better Prediction Results with the Use of Untapped Data
The DML Protocol and Algorithm Marketplace can help the customers to acquire machine learning algorithms for their business predictions. They can also generate more accurate predictions by applying the algorithms to untapped data stored in individual electronic devices, which is inaccessible before, at a market-driven cost and free from middleman by adopting smart contract. Comparing to traditional market research such as conducting survey and focus group, prediction from the DML protocol could be much faster and timely, unbiased, cost-effective, more accurate and relevant. DML protocol provides a powerful tool to identify market trends and sentiments are learnt.
Token Usage and Mechanism
Utilize Untapped Data and idle processing power for Machine Learning
DML token is paid to the data owner to contribute their private data and idle processing power for running machine learning algorithm in the DML protocol.
Acquire Machine Learning Algorithms in Marketplace
Apart from building in-house machine learning algorithm, customers could acquire machine learning algorithm from the developers in our DML marketplace using DML tokens. Therefore, talented developers are incentivized to join the DML developers’ community to develop machine learning algorithms for real life applications.
Reward to Decentralized Nodes in the protocol
DML tokens are used to motivate the decentralized nodes with different functions such as distributing algorithms, aggregating and averaging local machine learning result by federated learning or producing aggregated machine learning report. Those functions are essential and serve as part of the decentralized processing power network in machine learning.
Reward to Algorithm Trainer for Fine-tuning Algorithms
Developers who wish to seek resources to train and fine-tune their models can pay DML tokens to the model trainers. DML tokens are used to motivate model trainers to contribute their effort and time to fine-tune the algorithms by correcting the label of the algorithm.
User Growth Pool to Incentivize Users
A user growth pool of 9% of DML tokens will be created to incentivize DML users to early participate in the DML protocol and ecosystem. Data owners to allow machine learning algorithms to be run on their untapped private data. Decentralized nodes which provide various essential functions in supporting different parts of decentralized machine learning.
Extra Reward to Contributors
In addition to DML tokens directly paid by customers, data owners may earn extra DML tokens randomly from the user growth pool as long as they are connected to the DML protocol. The data owners, therefore, will earn DML tokens from up to two sources i.e. customers and user growth pool.
User Growth Pool Generation Mechanism
A limited amount of the DML token will be generated according to the pre-defined decreasing-supply algorithm based on the preset mechanism across time. The mechanism is designed to encourage early participation to contribute to machine learning development. Therefore, the reward block is designed with a pre-defined algorithm that will decrease with time.
The DML Token Utility System
Data owners will be rewarded from up to two sources, which is driven by the market demand of using untapped private data for machine learning and from the user growth pool. To encourage simplicity and mass adoption of token and cryptocurrency, a ERC20-supported wallet will be built in DML App to keep the DML token or other supported tokens.
Future Upgrades with DML
Flexibility to Upgrade and Multi- Blockchain Compatibility
DML treasures the knowledge, expertise and innovation of every individual as they believe in collective wisdom and intelligence, their core value that motivates to unleash untapped data and link them together to create a co-intelligence system. Therefore, DML protocol is designed to encourage developers to participate in system upgrade or future technology compatibility advancement too.
Compatibility with existing and forthcoming blockchain and cryptographic technology together with the flexibility for protocol upgrades are the key for on-going development and sustainability. Therefore, DML protocol is designed with flexibility to be upgraded and compatible with new blockchain technology, of which it will not be confined to any single or existing ones.
Promote DML Protocol Upgrade
DML encourages any developers, who have ideas to improve the protocol by proposing enhancement to the existing one, through our protocol. They’ll reserve financial resources to motivate any developers to improve their protocol. This does not only incentivize developers across the globe to continuously contribute to the maintenance of the decentralized network, but also the forthcoming enhancement of the protocol.
Scalability and Off-chain Transactions
DML protocol is designed with scalability feature to cope with increasingly mass usage and heavy transactions load. For instance, DML may adopt off-chain method, such as state channels, by offloading non-core and generalized processes off-chain to increase its efficiency and reduce transaction costs.
Cross-chain Compatibility and Interoperability
DMLs decentralized and open-source blockchain technology allows individual data and intelligence to be joined together to create a collective beneficial ecosystem. They believe such decentralization approach should not be confined to one single blockchain platform. Therefore, their technology welcomes and encourages all sorts of blockchain technology to be adopted in their protocol and various system languages to be used to run their machine learning algorithms on their network.
We encourage both adoption of existing blockchain technology such as Ethereum and any other future blockchain platform. Their protocol aims to allow integration of new blockchain technology to the currently adopted ones without replacing or overriding them. A co-exist ecosystem that links and aggregates different blockchain-based technologies will be created.
Likewise, for the protocol upgrade mechanism, developers are also encouraged to integrate any new blockchain technology on top of the existing blockchain platform as used in DML protocol. The same incentive mechanism will be deployed to encourage a variety of blockchain technologies to be adopted.
The potential of DML protocol is far more than facilitating algorithms or programs to be run directly on these connected electronic devices through its decentralized network. Ultimately, we aim to leverage the decentralized network that connects potentially billions of devices all over the globe to be able to communicate with each other.
Decentralized Machine Learning Protocol provides the technological, social and business structures for utilizing blockchain or any other associated technology to continually develop and evolve within the foreseeable future. Accordingly, the plans, strategies and implementation will likely evolve as well.
DML Tokens are being sold in accordance to the Terms and Conditions of the token sale are available at https://decentralizedml.com
• For complete details, please refer to the terms and conditions of the token sale.
• DML Tokens are utility tokens and are not securities, investments or currency, and are not sold or marketed as such.
• Participation in the token sale involves significant technological and systematic risks.
• The sale is not open to individuals who reside in or are citizens of the United States, Singapore, China and Hong Kong.
• The sale period, duration, pricing, and other provisions may change as stated in the token sale terms.
• The DML token sale involves known and unknown risks, uncertainties, and other factors that may cause the actual functionality, utility, or levels of use of DML Tokens to be materially different from any projected future results, use, functionality or utility expressed or implied in the terms and conditions of token sale.