Fetch.AI combines machine learning (ML) and artificial intelligence (AI), multi-agent systems, and decentralized ledger technology to build the Internet of Economics. Digital agents for economic activity components—such as data, hardware, services, people, and infrastructure—can work more efficiently with practical guidance and predictions. Fetch is committed to bringing autonomous systems to all markets. Currently, market autonomy requires significant human resources; automating economic transactions can help markets operate more efficiently and smoothly. According to Fetchs vision, everyone will have multiple economic agents on the Fetch.AI platform. These agents, running in parallel or series, can solve todays—and tomorrows—complex problems more elegantly and effectively than their human counterparts.
The Fetch token is a divisible token used within the Fetch.AI network as digital currency required for any transaction or secure communication on the network. Additionally, nodes and agents must stake a certain amount of tokens to gain specific operational privileges (a security mechanism against malicious behavior).

What is Fetch.ai

Fetch.ai is a decentralized digital world that builds the future digital economy by deploying machine learning, advanced cryptography, and autonomous agents onto blockchain.

We focus heavily on building real-world solutions, putting us at the forefront of blockchain and AI technologies. We are exploring several key areas, including:
1. Sharing knowledge between disparate data silos using machine learning, economics, and advanced cryptographic techniques, with potential applications in finance, insurance, and healthcare.
2. Autonomous agents for optimizing complex systems alongside multiple stakeholders in transportation, smart cities, energy, and supply chain sectors.
3. Developing advanced blockchain technologies to overcome existing implementations security and scalability challenges.

Fetch.ai will leverage recent advancements in cloud, IoT, edge computing, and 5G networks, making complex task automation easier across various consumer and business applications.

Technical Focus

Machine Learning
Blockchain can be used to decentralize federated learning algorithms, enabling the collective benefits of these machine learning models to be shared among multiple data owners.

Agents
Simplified development and deployment of populations of autonomous agents that achieve economic goals through strategy, communication, search, and value exchange.

Cryptography
Enhancing blockchain speed, efficiency, and security using next-generation multiparty computation (MPC) protocols for random beacons and aggregate signatures.