About Decentralized Machine Learning
Our goal is to create a blockchain-based decentralized machine learning protocol and ecosystem through:
- utilizing untapped private data for machine learning while protecting data privacy,
- connecting and leveraging idle processing power of individual devices for machine learning,
- 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,
- improving and correcting existing machine learning algorithms and models through crowdsourced fine-tuning model trainers,
- 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.
Missing whitepaper? Let us know.
Rated on Aug 3, 2018
Team is cool +
Roadmap is good to have some of the project developed already +
Having a prototype is a bonus +
Product idea is neutral in my opinion +/-
Having a small community is a drawback -
Allocating only 50% of the token sale to public is bad -
Rated on Feb 6, 2019
Modified on Apr 9, 2019
I’m very fond of DML’s core idea of utilizing untapped private data and processing power from the 2.3 billion smartphones and 2 billion PCs of our world a private way to foster a better ML community. As everyone knows, the AI market is growing exponentially fast. This is the recipe for something huge. Maybe a unicorn.
However, I do need to tame these words. DML is facing numerous complex challenges.
Adoption being the most critical one in my opinion. How will they onboard enough users in their ecosystem when they currently have nearly no activity on their social media? It seems hard to go from radio silence (besides monthly updates on their Medium) and a dormant community to being a leader in their field. Unless they somehow are able to create a buzz and massive fomo…
Their team has decent experience but they only list 4 core members VS a shitton of advisors. This seems unbalanced.
Their recent announcement of collaborating with 3 companies (Molecular Hub, HKSTP and ASTRI) is looking very promising and will certainly help them from a technical standpoint and more importantly with market analysis, getting partners on board to use their platform and general awareness.
Overall, I would say buying now is quite a risky play considering the market situation. With that said, I do think the DML team is one of the few ICO team that seems to be honest, hard working and has the experience and skills to pull it off despite the rough market.
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TeamApply as an advisor
Project Lead Director
Blockchain and Software Developer
Machine Learning Engineer
System Security Engineer
Google published the research paper on federated learning
AlphaGo beat Lee Sedol in Go
Idea generation of decentralization in machine learning
Google published research blog in federated learning
Development of proof of concept
Idea generation of decentralization in algorithms
Whitepaper published and DecentralizedML.com online
Release of DML Protocol Gen 0 (DML Algo Marketplace) Prototype
Token Generation Event and Launch of DML Protocol Gen 0 (DML Algo Marketplace) Beta
DML Algo Marketplace online
Release of DML Protocol Gen 1 alpha (decentralized machine learning on-device private data)
Research of state channels for increasing DML scalability
First DML Algo competition to grow and support developers’ community
Release of DML Protocol Gen 1 beta
DML Protocol Gen 1 online
Release of customized state channels for increasing DML scalability
Release of DML Protocol Gen 2 beta (decentralized machine learning on-device private data with third-party service and data access)
Research of multi-chain support and interoperability
DML Protocol Gen 2 online
Release of DML Protocol Gen 3 beta (decentralized machine learning on-device private data with third-party service and data access and mobile sensors/ IoT connection capability)
DML Protocol Gen 3 online
Research of general purpose API start for expanding usage of DML marketplace from machine learning to general applications
Research of new blockchain supporting mass adaption of general purpose decentralized applications and data privacy
Release of DML Protocol Gen 4 beta (Support deployment of general applications)
DML Protocol Gen 4 online