A curated list of Blockchain projects for Artificial Intelligence and Machine Learning.
This list explores awesome projects that exploit the properties of blockchain technologies (decentralization, immutability, smart contracts, etc.) to build the next generation of AI systems.
- Recommended reading
- Foundations
- Blockchains for AI algorithms
- Blockchains for data
- Blockchains for computation
- Blockchains for AI in finance
- Blockchains for AI in medicine
- Blockchains for AI in supply chains
- Academic Research
- Blockchain: "A blockchain is a growing list of records, called blocks, which are linked using cryptography."
- Artificial Intelligence: "In the field of computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals."
- Machine Learning: "Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead."
- Decentralizing AI: Dreamers vs. Pragmatists. - Jesus Rodriguez, May 23, 2019.
- How the Blockchain Could Break Big Tech’s Hold on A.I. - New York Times, October 20, 2018.
- How to Actually Combine AI and Blockchain in One Platform - Hacker Noon, June 7, 2018.
- Blockchain-based Machine Learning Marketplaces - Fred Ehrsam, March 13, 2018.
- The convergence of AI and Blockchain: what’s the deal? - Francesco Corea, December 1, 2017.
- Decentralized AI Alliance (DAIA). DAIA is an alliance of serious participants in the AI & blockchain related ecosystem, coming together to collectively solve common challenges and create an amazing future.
- SingularityNET - SingularityNET is a distributed AI platform on the Ethereum blockchain, with each blockchain node backing up an AI algorithm.
- Intuition Fabric - The goal of Intuition Fabric is to democratize access to AI through a network of deep learning models that are stored on the interplanetary file system and accessed through the Ethereum blockchain.
- OpenMined - OpenMined is a community focused on building open-source technology for the decentralized ownership of data and intelligence. With OpenMined, AI can be trained on data that it never has access to.
- Raven Protocol - Raven Protocol is a decentralized and distributed deep-learning training protocol.
- Thought Network - Thought's blockchain-enabled Fabric fundamentally changes applications by embedding artificial intelligence into every bit of data making it agile, actionable and inherently secure.
- MATRIX AI - The Matrix AI Network is a public chain that combines AI technology with blockchain technology to solve the major challenges currently stifling the development and adoption of blockchain technology. Matrix is poised to revolutionize and democratize the field of Artificial Intelligence using a blockchain-powered decentralized computing platform.
- Cortex Labs - Cortex Labs is a decentralized AI platform with a virtual machine that allows you to execute AI programs on-chain.
- Fetch.ai - Fetch.ai is a decentralized machine learning platform based on a distributed ledger, that enables secure sharing, connection and transactions based on any data globally.
- Danku - A blockchain-based protocol for evaluating and purchasing ML models on a public blockchain such as Ethereum. Blog post.
- Decentralized & Collaborative AI on Blockchain - 0xDeCA10B is a framework to host and train publicly available machine learning models in smart contracts with incentive mechanisms to encourage good quality training data while keeping the models free to use for prediction. Blog post.
- Ocean Protocol - Ocean Protocol is a decentralized data exchange protocol that lets people share and monetize data while guaranteeing control, auditability, transparency and compliance to all actors involved. Its network handles storing of the metadata (i.e. who owns what), links to the data itself, and more.
- Neuromation - Synthetic datasets generation and algorithm training platform.
- BOTTOS AI - A decentralized AI data sharing network that uses a consensus-based application platform to allow AI projects to gather training data.
- Synapse AI - A decentralized global data marketplace built on the Ethereum blockchain.
- Neuromation. - Distributed synthetic data platform for Deep Learning Applications.
- Cyber - A decentralized search engine, able to learn from knowledge graphs and provide predictive models.
- Neureal - Open source, peer-to-peer AI supercomputing powered by blockchain.
- TrueBit - TrueBit gives Ethereum smart contracts a computational boost.
- DeepBrain Chain - A decentralized AI computing platform that supplies processing power to companies looking to develop A.I. technologies.
- AI Crypto - AI Crypto is a blockchain-based ecosystem where AI resources such as GPU, models, and data are distributed in order to lower the cost of AI development.
- Numerai - Numerai is a hedge fund powered by a network of anonymous data scientists that build machine learning models to operate on encrypted data and stake cryptocurrency to express confidence in their models.
- Napoleon X - Napoleon X is an open online computer driven asset management platform selecting quantitative strategies (trading bots) from world class traders, where each crypto-fund dedicated to a specific Asset Class.
- Cindicator - Cindicator is a crowd-sourced prediction engine for financial and crypto indicators.
- Erasure - Erasure is a decentralized protocol and data marketplace for financial predictions.
- doc.ai - doc.ai aims to decentralize precision medicine on the blockchain by using AI.
- BurstIQ - Healthcare data marketplace with granular ownership and granular consent of data. By using on-chain storage on a custom blockchain, BurstIQ can comply with HIPAA, GDPR, and other regulations.
- Vytalyx - Vytalyx is a health technology company that plans to use AI and blockchain to store and analyse medical data.
- Coin.AI - Baldominos, A., & Saez, Y. (2019). Coin.AI: A proof-of-useful-work scheme for blockchain-based distributed deep learning. Entropy, 21(8), 723.
- WekaCoin - Bravo-Marquez, F., Reeves, S., & Ugarte, M. (2019, April). Proof-of-learning: a blockchain consensus mechanism based on machine learning competitions. In 2019 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPCON) (pp. 119-124). IEEE.
- Deep Learning-Based Consensus - Li, B., Chenli, C., Xu, X., Shi, Y., & Jung, T. (2019). DLBC: A Deep Learning-Based Consensus in Blockchains for Deep Learning Services. arXiv preprint arXiv:1904.07349.
- Proof of Deep Learning - Chenli, C., Li, B., Shi, Y., & Jung, T. (2019, May). Energy-recycling blockchain with proof-of-deep-learning. In 2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC) (pp. 19-23). IEEE.
- BlockML - Merlina, A. (2019, December). BlockML: a useful proof of work system based on machine learning tasks. In Proceedings of the 20th International Middleware Conference Doctoral Symposium (pp. 6-8).
- Convergence of AI and DLT - Pandl, K. D., Thiebes, S., Schmidt-Kraepelin, M., & Sunyaev, A. (2020). On the convergence of artificial intelligence and distributed ledger technology: A scoping review and future research agenda. IEEE Access, 8, 57075-57095.
- Proof of Learning - Lan, Y., Liu, Y., & Li, B. (2020). Proof of Learning (PoLe): Empowering Machine Learning with Consensus Building on Blockchains. arXiv preprint arXiv:2007.15145.
- Decentralized and Collaborative AI on Blockchain - Harris, J. D., & Waggoner, B. (2019, July). Decentralized and collaborative AI on blockchain. In 2019 IEEE International Conference on Blockchain (Blockchain) (pp. 368-375). IEEE.
- Decentralized and Collaborative AI on Blockchain - Harris, J. D. (2020, September). Analysis of Models for Decentralized and Collaborative AI on Blockchain. In International Conference on Blockchain (pp. 142-153). Springer, Cham.
- Hyperparameter Optimization - Mittal, A., & Aggarwal, S. (2020). Hyperparameter optimization using sustainable proof of work in blockchain. Frontiers in Blockchain, 3, 23.
- Proof of Federated Learning - Qu, X., Wang, S., Hu, Q., & Cheng, X. (2021). Proof of federated learning: A novel energy-recycling consensus algorithm. IEEE Transactions on Parallel and Distributed Systems, 32(8), 2074-2085.
- Proof of neural architecture - Li, B., Lu, Q., Jiang, W., Jung, T., & Shi, Y. (2021, May). A mining pool solution for novel proof-of-neural-architecture consensus. In 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC) (pp. 1-3). IEEE.
- Explore Blockchain - Discover & find a curated list of popular & new Blockchain libraries, top authors, trending project kits, discussions, tutorials & learning resources on kandi
These projects are not active anymore.
- Dopamine - Decentralized AI workforce and services marketplace.
- Trane AI - A decentralized economy for tagging, storing and modeling data for AI-training.
- starmine AI - Starmine is a robust and highly scalable platform for constructing, trading and exchanging advanced algorithmically generated on-demand datasets for machine learning and artificial intelligence efforts.
- Cerebrum - Cerebrum is a decentralized platform for crowdsourced machine learning. Cerebrum enables anyone to encrypt their data and host machine learning competitions to utilize crowd-sourced machine learning models.
- Fitchain - Fitchain is a blockchain-based machine learning factory that allows data scientists to train models, tracing them from inception and throughout their lifetime.
- Namahe - Namahe is platform that aims to bring efficiency to supply chain industries by incorporating an A.I. layer.
- Pandora Boxchain - A marketplace for AI kernels, computations and big data powered by Proof of Cognitive Work (PoCW).
- Decentralized Machine Learning - DML aims to create a blockchain-based decentralized machine learning protocol and ecosystem.
- Computable - A decentralized data marketplace for artificial intelligence applications.
To the extent possible under law, Steven Van Vaerenbergh has waived all copyright and related or neighboring rights to this work.