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Home Code Reviews

Fetch.ai Code Review

by The Token Metrics Team
2023/03/06
in Code Reviews
Reading Time: 7 mins read
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Review Date: 26/02/2023

Fetch.ai is an interchain protocol that operates as a Layer 1 blockchain, utilizing Cosmos SDK and Multi-Agent System principles. Its goal is to establish a decentralized infrastructure for P2P applications that are capable of automation and AI functionalities.

The network functions through a group of independent agents that interact via the blockchain to complete their tasks. To provide developers with tools for building and running these agents, the Fetch.ai team created the Autonomous Economic Agent (AEA) framework.

In addition to the AEA framework, the team has launched two groundbreaking platforms. CoLearn, a marketplace for data and AI models, allows users to monetize their data and AI models. DabbaFlow, a decentralized data-sharing protocol, allows users to securely share their data across multiple parties without a middleman.

The FET token serves as the native token for the Fetch.ai ecosystem. The team boasts an impressive research team, continually developing innovative solutions for the platform’s advancement.

Overall, Fetch.ai is an exciting project at the forefront of decentralized P2P applications with AI capabilities. Their achievements to date demonstrate their commitment to creating a more innovative and interconnected digital world.

Notes to Take

  • Fetch.ai is an interchain protocol, built using the Cosmos SDK
  • Built using principles of the Multi-Agent system, branch of AI
  • Mission is to build infrastructure for decentralized P2P applications
  • Fetch Wallet
    • Forked from Kepler wallet
    • Store and stake FET
    • Mobile and PC version
  • FET token is the native token for the Fetch.ai ecosystem
    • Network fees
    • Staking
  • Autonomous machine-to-machine ecosystem
    • Network agents work as independent parties and interact via the blockchain network
    • To perform their tasks, agents connect and negotiate with each other
    • Agreements made between the agents are recorded on the blockchain network
    • Rewards to stakeholders who contribute to the federated learning models
    • CoLearn Marketplace
    • DabbaFlow
      • Decentralized data-sharing protocol
    • Mainnet launched
  • Autonomous Economic Agent (AEA) framework is a development suite that equips you with an efficient and accessible set of tools for building and running AEAs. It is modular and composable
    • ACN helps agents interact over the internet
  • CoLearn
    • A library that enables privacy-preserving decentralized ML tasks
    • A marketplace for data and AI models
    • A Blockchain mediated collective learning system
  • DabbaFlow
    • Provides privacy to Colearn
    • Data sharing platform
  • Jenesis
    • CL tool for rapid contract and service development
  • Axim
    • Helps you make informed decisions and reach your goal
    • Optimizes business functions
  • Agents Based Modelling (ABM)
    • An agent is a piece of software that represents an entity (individual, organization, or object) and acts continuously and autonomously (with limited or no interference) on its behalf.
      • Key characteristics
        • Representation
        • Autonomy
        • Self-interest
        • Proactive
        • Reactive
    • ABM consists of a system of agents and connections between them
  • Multi-Agents Systems (MAS)
    • Group of agents that interact with each other and the environment  to achieve specific goals
    • Key characteristics
      • Decentralization
      • Heterogeneity
      • Scalability
      • Robustness
      • Adaptability
    • Highly complex and difficult to predict
    • Building since 4 years
Initial Screening
Keep researching
Does this project need to use blockchain technology?Yes
Can this project be realized?Yes
Is there a viable use case for this project?Yes
Is the project protected from commonly known attacks?Yes
Are there no careless errors in the whitepaper?Yes

Project Technology Score
DescriptionScorecard
Innovation (Out Of 11)7
How have similar projects performed?Good2
Are there too many innovations?Regular2
Percentage of crypto users that will use the project?1-5%1
Is the project unique?Yes2
Architecture (Out of 12)11
Overall feeling after reading whitepaper?Good2
Resistance to possible attacks?Good2
Complexity of the architecture?Not too complex2
Time taken to understand the architecture?20-50 minute1
Overall feeling about the architecture after deeper research?Good4
Code Quality (out of 15)12
Is the project open source?Yes2
Does the project use good code like C,C++, Rust, Erlang, Ruby, etc?Yes2
Could the project use better programming languages?No0
Github number of lines?More than 10K1
Github commits per month?More than 102
What is the quality of the code?Good2
How well is the code commented?Bad0
Overall quality of the test coverage?Outstanding2
Overall quality of the maintainability index?Good1
When Mainnet (out of 5)5
When does the mainnet come out?Live5
Usability for Infrastructure Projects (out of 5)5
Is it easy to use for the end customer?Yes5
Team (out of 7)6
Number of active developers?5+2
Developers average Git Background?Senior2
Developers coding style?Solid2
Total Score (out of 55)46
Percentage Score
Innovation12.73%
Architecture20.00%
Code Quality21.82%
Mainnet9.09%
Usability9.09%
Team10.91%
Total83.64%
Tags: Code ReviewsPremium
The Token Metrics Team

The Token Metrics Team

Token Metrics is an AI-driven cryptocurrency research and analytics platform.

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