Artificial Intelligence for Blockchains
Fetch.ai is building an open access, tokenized, decentralized machine learning network to enable smart infrastructure built around a decentralized digital economy.
What is Fetch.ai
At Fetch.ai we build tools and infrastructure to enable a decentralized digital economy.
Fetch.ai, a Cambridge-based artificial intelligence lab, is building a decentralized machine learning platform based on a distributed ledger, that enables secure sharing, connection and transactions based on any data globally.
Fetch.ai’s network is based around an open-source technology that any user can run to connect to the network, giving access to the power of AI on a world-scale secure dataset, to carry out complex coordination tasks in the modern economy.
On this network a series of software agents represent and act on behalf of their owners. These autonomous agents work to provide an optimised service across a variety of ecosystems, to the benefit of both suppliers and consumers.
This system has wide potential in many areas. Financial services users can optimize trading, public transport networks could be reconfigured, cities could intelligently adapt to usage by their citizens, the gig economy could be restructured, and energy networks can be connected in a smart grid.
Introduction
Fetch.ai is building technology to power the machine-to-machine economy. This includes novel blockchain and a generic framework for building off-chain protocols using techniques from multi-agent systems. This agent framework can be used for oracles, interchain transfers, state channels and many other applications and is tightly integrated with the Fetch ledger.
Our mission
Our mission is to build the infrastructure required for autonomous software agents to organize complex tasks to benefit individuals, businesses and organizations.
And to enable anyone access to the power of AI with our interoperable decentralized network and open‑source software tools.
Technical Focus
Machine Learning
Blockchain can be used to decentralize federated learning algorithms so that the benefits of these collective machine learning models are shared across the multiple owners of data.
Agents
Simple development and deployment of autonomous agent populations that fulfill economic goals through strategy, communication, search and the exchange of value.
Cryptography
Enhance the speed, efficiency and security of the blockchain using next generation multi-party computation (MPC) protocols for random beacons and aggregated signatures.