Fetch.AI Fundamental Analysis

Introduction

Similar to SingularityNET, Fetch.AI looks to combine the worlds of blockchain and AI in an extremely ambitious way. The project is very complex and is difficult to understand from a technical perspective but I will do my best to dumb it down in the following sections. The scope of this project is extremely wide but if successful, will be a gamechanger for the world. Lets get started.

 

Fetch.AI looks to combine the worlds of machine learning and Artificial intelligence with blockchain technology and multi agent systems. The goal of this ambitious crossover is to create a much more efficient world where manual work becomes obsolete and therefore the world is run at a frictionless digital speed. 

Inefficiencies exist all over the world from cars that sit idle for 90% of their lives, overcrowded highways, vacant hotel rooms, shipments that aren’t max capacity etc. All of these are inefficiencies that cut into the margins of private businesses and the global economy as a whole. The systems used in each of these are through centralized command centers that are used to manage inventory, guide traffic and operate. The systems therefore are very one dimensional and are prime candidates for disruption after decades of little innovation. AI, and in the case of Fetch, decentralized AI through blockchain technology has the ability to connect the above systems and allow the world to operate more efficiently and effectively.

How Fetch Works

Without getting too technical into how Fetch works, there are three main parts to the project:

 

  1. Autonomous Economic Agents

This is the most important aspect of Fetch and is the bread and butter of the project. AEAs are essentially agents that represent an individual, organization or object that acts independently from its owner and executes actions based on its given goal. One example would be UPS using an AEA to predict how much fuel a specific shipment will use based on given data such as the weather, traffic, construction etc. The agents work within the system that they are given, they analyze and identify key pieces of information and then use “deep learning algorithms” to create the best solution for the identified problem.

  1. Open Economic Framework

As defined on the Fetch website; “The Open Economic Framework provides search and discovery functions to enable agents to find each other along with peer-to-peer networking tools for routing messages between agents.” 

What this entails is that AEAs connect to OEFs in order to collect information and interact with other agents to complete their given tasks. The capabilities of the OEF are fulfilled through these three components: 

  1. Permissionless, public agent to agent communication network called the Agent Communication network
  2. A set of agent interaction protocols 
  3. Centralized search and discovery system(to be decentralized over time)

3 . Fetch Smart Ledgers

The Fetch ledger looks to combine direct acyclic graph technology(DAG) with transaction chains. DAG is an alternative to blockchain technology which is common in projects like Hedera Hashgraph, IOTA and Byteball. 

To understand the technicals of Fetch I highly recommend giving their technology page a read here.

FET Token

The FET token is used by the agents of the ecosystem to fund specific functions and is a tool to incentivize good behavior(prevention of malicious agents). The following information is gathered from Fetch’s Medium blog:

 

5 Examples of use:

 

  1. Connecting agents to the network

Once an agent has been built and developed, it can be deployed on the network by depositing FET tokens. The deposition of FET tokens is a little like staking, it gives the specific agent permission to operate on the network. Due to the escalating costs associated with tokens, this makes it infeasible for bad actors to deploy several malicious agents into the ecosystem. 

  1. Exchanging Value between agents

After agents have communicated and shared valuable information to one another, there needs to be a transaction between the two to pay for the data or services that was offered from one agent to the other. In this instance, the FET token acts as a medium of exchange for the agents to exchange between one another to acquire services and data. An important point that Fetch makes is that the token supports micro-payments meaning the autonomous machines can transact small data inquiries or small services from one another at a low cost. The example they give is a car retrieving a small amount of data from a senor, you wouldn’t want your AEA to spend a large sum on a small data request. 

  1. Accessing ledger-based AI/ML algorithms 

A unique characteristic of the Fetch ledger is that it has artificial intelligence and machine learning functionalities built into the ledger itself. This is why the ledger is referred to as a “Smart Ledger”. In order to access these built in functionalities, agents are required to spend a moderate amount of tokens.

  1. Accessing the Fetch.AI digital world

The Fetch.Ai ecosystem expands beyond the ledger. Fetch makes the claim that “the digital world is a vast space that represents the real world, but in a way machines can work with and interpret”. Within this digital world, AEA can seek out ways in which they can value to other AEAs and receive value in return. The FET token is used as a means for agents to gain access to one another. 

  1. For Exchange into Fetch.AI’s operational fuel

Similar to the Ethereum network, the FET token is used as a form of “gas” for operation costs. With that being said, FET has additional functionality in order to maintain the stability of the fuel and address various issues that come with high and low-velocity economies. 

Fetch Team

An innovative entrepreneur, founding investor in Deep Mind with a record in revolutionizing trading in the steel sector and now focused on changing the way we transact and travel.

Producer of the Creatures series of games and an early developer at Deep Mind. He has 30 years of experience in software and ten as a CTO. Toby is now focused on crypto-economics.

Professor at Sheffield and established scientist in advanced machine learning AI who bridges the real world and academia and is inspired by the opportunities AI brings to modern society.

Conclusion

Like I stated in the introduction, the depth and complexity of this project is unmatched similar to projects like SingulairtyNET. Both projects look to utilize AI to revolutionize the world we live in but in different ways. I’ll be writing a blog post comparing and contrasting the two projects in the following weeks. 

 

Despite my handicap of not being able to understand all of the technicalities of the project(as of writing), it is clear to me that the project warrants more research and is a solid investment. Given its scope, solid team with a background in Deep Mind and the multiple uses of the FET token, small investments at this stage can easily reap massive rewards in the long term and short term. With Mainnet V.2. to be launched at the end of this month alongside consistent partnership announcements throughout this year, short term holding of FET looks to be very profitable as well as long term holding. 

Although not financial advice, my conclusion on FET is to buy if you can stomach holding onto a high risk/high reward altcoin that can easily 100x if it lives up to its ambitions.

9.5/10

Enjoy the analysis? Check out my analysis of SingularityNET here and LUKSO here. All constructive criticism is welcomed.