[Short general description]: Decentralized Machine Learning unleashes untapped private data, idle processing power and crowdsourced algorithms development by on-device machine learning, blockchain and federated learning technologies.
[Main problems tackled]:
1) Inaccessibility of Private Data - Nowadays, machine learning is mainly conducted through a centralized computer, which its processing power is usually limited or confined to the processors of a single machine.
2) Centralization of Processing Power - Only large corporations can afford investing huge initial capital and resources to build in-house machine learning models and algorithms, or acquire tailor-made ones from consultancy firms to apply machine learning in their own business.
3) DML advances machine learning development by returning power to all ecosystem contributors - DML has created an open source infrastructure and network which data, processing power and models/algorithms development will all be decentralized.
4) Processing Power - DML Procotol will utilize the idle processing power of the devices to perform on-device machine learning.
5) Data - All private data will be kept within the devices and only the local prediction results will be transferred. Usage of untapped private data is unleashed as a result.
6) Algorithms - The supply of algorithms will be crowdsourced in our developer community. Customer such as corporates, research institutes, governments or NGOs can simply search or request suitable machine learning algorithms in DML Algorithms Marketplace.
[Main contribution proposal]: To create a blockchain-based decentralized machine learning protocol and ecosystem through:
1) Utilizing untapped private data for machine learning while protecting data privacy,
2) Connecting and leveraging idle processing power of individual devices for machine learning,
3) 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,
4) Improving and correcting existing machine learning algorithms and models through crowdsourced fine-tuning model trainers,
5) Creating a new DML utility token and leveraging on blockchain smart contract technology to provide a trustless and middle-man free platform that connects potential contributors in machine learning from all aspects.
1) Apply Decentralized Algorithm & Data for ML Prediction
2) Improve Existing ML Algorithm via Crowd Informed Fine-tuning
3) Smart Contract for Machine Learning on Untapped Data
4) Smart Contracts for DML Marketplace Activities
5) Benefits for Different Participants - 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.