Fetch.AI (FET): An AI Solution to Data Inefficiency

What Is Fetch.ai?

Founded in 2017 and launched via IEO on Binance in March 2019, Fetch.AI is an artificial intelligence (AI) lab building an open, permissionless, decentralized machine learning network with a crypto economy. Fetch.ai democratizes access to AI technology with a permissionless network upon which anyone can connect and access secure datasets by using autonomous AI to execute tasks that leverage its global network of data. The Fetch.AI model is rooted in use cases like optimizing DeFi trading services, transportation networks (parking, micromobility), smart energy grids, and travel — essentially any complex digital system that relies on large-scale datasets. 

Fetch.ai Protocol Structure

The Fetch.ai blockchain is an interchain protocol based on the Cosmos-SDK, and uses a high-performance WASM-based smart contract language called Cosmwasm to allow advanced cryptography and machine learning logic to be implemented on-chain. This layer is responsible for securing the network through consensus. It also provides staking, governance, and identity services that support digital twin applications. The Fetch.ai blockchain relies on a modified version of the Cosmos protocol’s Tendermint Proof-of-Stake (PoS) consensus mechanism to secure the network. And since the Fetch.ai blockchain is Cosmos-based, it can be interoperable with other blockchains in the Cosmos ecosystem via the inter-blockchain communication (IBC) protocol. 

ERC-20 and Native FET token

Fetch.ai leverages its own native cryptocurrency FET as a utility token and the primary medium of exchange on the platform. FET is used to pay for network transaction fees, deploy AI, and pay for services. Users can also choose to stake FET to participate in securing the network via its Proof-of-Stake consensus mechanism and earn rewards in return for contributing to validator nodes. 

There is a maximum supply of approximately one billion FET, which exists both in its native form as an ERC-20 token that can be used throughout the Ethereum ecosystem, and as a BEP-20 Token that can be used throughout the Binance Smart Chain Network. FET can be easily exchanged through a token bridge at a 1:1 ratio for either the Fetch.ai blockchain mainnet or ERC-20 version as needed. Staking on the Fetch.ai mainnet can earn users high rewards with significantly lower transaction fees for users. 

Fetch.ai Ecosystem

Fetch.ai is providing technology using multi-agent systems that decentralize access to data-systems. This utility is applicable to a spectrum of use cases and sectors. While a number of projects and use cases are built by the Fetch.ai organization, there also exists a rapidly growing spectrum of independent projects built using Fetch.ai tech. The Fetch.ai ecosystem features tools, projects, and platforms have spun up in industries like DeFi, mobility, and healthcare: 

Mettalex: A decentralized crypto and commodities derivatives trading platform, Mettalex is addressing pain points in commodities markets like front running, poor liquidity, price manipulation and loss of value in the form of margin calls.

Mobix: A decentralized micro-mobility marketplace that incentivizes sustainable urban mobility. 

Catena-X: Fetch.ai is part of the Catena-X Automotive Network, which aims to create an open ecosystem for efficient and secure exchange of information throughout the automotive value chain. The cloud-based network is to open to all companies in the European vehicle industry, along with their global partners, users and equipment suppliers. 

Collective Learning: The Fetch.AI collective learning module is a tool that enables distributed parties to work together to train machine learning models without sharing underlying data with any of the individual participants. Utilizing blockchain technology and AI learning capabilities, it supports and trains its network to learn from private data without having access to it. 

1. COVID-19 detection: Multiple participants from the healthcare sector trained a machine learning algorithm using Fetch.ai’s Collective Learning to detect COVID-19 in chest x-rays. During these trials, the trained AI model correctly identified COVID-19 cases from a training set of over 1,434 chest X-ray images with 90% accuracy.

2. Cancer cell detection: In partnership with Poznan Supercomputing Networking Center (PSNC) on Collective Learning, Fetch.ai and PSNC will train algorithms for hospitals and research centers worldwide to identify and detect circulating cancer cells in patients’ blood or tissue biopsies in the future. 

3. Bosch and Fetch.ai - Predictive Maintenance: Predictive maintenance is a process that identifies potential failures of machinery before they happen. To identify potential failures of manufacturing machinery, Bosch is utilizing Fetch.ai’s Collective Learning to predict potential failures in Bosch’s machinery while maintaining data privacy.

4. Colearn pAInt: This is an art creation platform that allows groups of creators to automatically generate NFTs using Machine Learning. Each piece is one of a kind and sold via auction on OpenSea.

Fetch.ai’s own use cases include dApps like Botswap.fi, which allows users to manage and protect their crypto assets across multiple chains using Fetch.ai tech to automate the process of managing liquidity pools and other key elements. Fetch.ai is also developing a Decentralized Delivery Network, which allows users to engage with delivery services more affordably and privately than many centralized parcel services can offer. 

It’s clear that there are a range of use cases that Fetch.ai’s multi-agent systems can tap into to create a decentralized digital economy. From service sectors like travel or the gig economy to sectors relying on automation and machine learning like mobility or supply chain management, multi-agent systems can decentralize access to data and disrupt existing data monopolies.