FET, also known as Fetch. Ai, aims to create a self-learning blockchain network that facilitates economic activity/composition among offline AI agents. Fetch's blockchain network will help AI agents (such as delivery robots) autonomously discover economic partners who recognize the value of their services and data. Fetch tokens are key to value transactions on the Fetch network and can be used to connect agents/nodes to the network, exchange value between agents, access and develop distributed AI/ML algorithms, and drive website operations.

It aims to build an economic Internet. Digital agents of the moving parts of the economy (such as data, hardware, services, people, and infrastructure) can do their jobs efficiently with practical guidance and predictions. Fetch is committed to bringing autonomous systems to all markets. At present, the process of market autonomy needs a lot of manpower and material resources. Automated economic transactions help markets function efficiently and smoothly. According to Fetch's vision, each person will have multiple economic agents on Fetch.AI platform. Agents running in parallel or in series to develop solutions to complex problems of today and tomorrow will be more elegant and superior than human versions.

With the geometric growth of IOT devices, data collected by various devices presents a phenomenon of decentralization and fragmentation. However, the amount of valuable data mined by existing systems is not high. The efficiency of the data realization market lies in how to mine more data value and quickly match the data supplier and the demand side.

Fetch.AI project aims to popularize autonomous systems in all markets. Autonomous economic transactions help markets operate efficiently and smoothly. According to the project design, each person will have multiple economic agents on the Fetch.AI platform, which will operate in parallel or series to develop solutions for complex problems. In addition, by combining the collective intelligence of machine and human intelligence, the information island problem of ARTIFICIAL intelligence is solved and the decision-making process is improved.

AEAs access OEF performs artificial intelligence data processing operations through data resource sharing in Fetch.AI ecosystem, and provides solutions for users to solve complex problems. In the digital economy world envisaged by the project owner, AEAs can be applied to almost all life application scenarios, such as hotels, transportation, energy and supply chains, and can be driven by artificial intelligence without human intervention.

FET utility tokens are the key to unlocking the Fetch ecosystem. It requires finding, creating, deploying and training autonomous economic agents, and is critical to providing the smart contracts, prognosticators and transactions needed for the new digital economy. 1. Train and deploy your agents on the Fetch. Ai network: By paying the right amount of FET tokens, developers can access machine learning-based utilities to train autonomous agents and deploy collective intelligence on the network. 2. Build the broker and connect it to the network: With the FET token, you can build and deploy your broker on the network. This process is a bit like staking, giving the agent the right to work on the network. 3. Build the broker and connect it to the network: Participate in the mortgage to verify the network service. The validation node is enabled by pledging the FET token. This contributes to network validation and reputation.

Fetch.AI will use a combination of proof of work (PoS) and proof of work (PoW) to reach a consensus, which they call Useful Proof of Work (UPoW) consensus, which aims to save useless work, while valid proof of work (UPoW) brings more advantages. Most current blockchain ecological consensus requires nodes to download all block data and add it to the main chain in block order. The project operator of Fetch.AI believes that this method is time-consuming and energy consuming. Based on the DAG system, a transaction only needs to be confirmed by two other nodes to reach the final result. In uPoW's consensus algorithm, some of the computing resources are used to train the AI, rather than all of them to compute useless problems.

1. The whole economic model of Fetch is finely designed and tightly operated. In terms of technology, 2. The Fetch project combines ledger technology of blockchain with artificial intelligence and deep learning technology, 3. UPOW mechanism is adopted to improve transaction efficiency and enrich technology application scenarios.

Autonomous Economic Agents -- AEAs is a software entity that pairs with devices such as cars, sensors, cameras, mobile devices, PCS, etc. By integrating the clients in these devices, AEAs connects to OEF and performs artificial intelligence data processing operations through data resource sharing within the Fetch.AI ecosystem, providing solutions to users to solve complex problems. For example, mobile phone operators can obtain a large amount of data to predict weather changes and traffic conditions to remind users, and users can provide the location of gas stations and the optimal route in real time through AEAs in the car. In the digital economy world envisaged by the project owner, AEAs can be applied to almost all life application scenarios, such as hotels, transportation, energy and supply chains, and can be driven by artificial intelligence without human intervention. 2. Open Economic Framework - OEF AEAs can connect to OEF systems through APIS. OEF provides an adaptive support environment for AEAs based on the data and information provided by AEAs. OEF will use machine learning and artificial intelligence to enable real-time coordination between AEAs for communication and interaction. Nodes that provide data and transmit data will be rewarded with tokens. Simply put, all AEAs will be hosted and run in the OEF, which will become an evolving ecosystem that allows AEAs to search, interact, and share with each other. With the gradual increase of information data, the whole system will become more reliable and effective. Fetch.AI's smart ledger combines blockchain and DAG technology. The Fetch system will collect transaction information and use "sharding" technology to record the ledger for expansion. Unlike traditional sharding, the system may assign a transaction to several different branches to record simultaneously, which spontaneously causes a hard fork in the chain. At the same time, the emergence of multiple parallel chains may increase the amount of transaction information in the whole network, and the "double flower problem" may occur.

Unique Proof-of-work (UPOW) consensus algorithm: Based on DAG system, a transaction only needs to be confirmed by two other nodes to reach the final. In uPoW's consensus algorithm, some of the computing resources are used to train the AI, rather than all of them to compute useless problems.

1. Team: Lack of experience in blockchain industry. Although most of the members are professionals in the technical field of ARTIFICIAL intelligence, the combination of artificial intelligence and blockchain is a completely different field with many technical difficulties. On the other hand, the project's technical assumption is that every connected client (vehicle system, mobile devices, etc.) can access API to provide services for AEAs. However, such a huge idea requires a strong business development ability of the team and the integration of client programs for many brand devices, which is extremely difficult. Therefore, the Fetch.AI project was a big challenge for the team. 2. Project: Grand structure, great difficulty and long implementation cycle, which has been overdue to some extent. Currently, according to the public information disclosed by the Fetch.AI project party, TokenGazer's evaluation of the project technology is not optimistic, and Fetch.AI has great obstacles in the implementation of technology and the final implementation of the project. 3. Community: The recent community popularity is mainly driven by an asset issuing platform, which is difficult to maintain for a long time.

Fetch.AI, if it can be realized, will be a strong combination of AI and blockchain, but it will be a costly project due to constraints such as long development cycle, long investment return cycle and difficult technology implementation. Although the attention of the project is still low, most of the attention recently comes from the driving effect of Binance Launchpad, so it is still unknown when Fetch.AI will be online and how it will perform after it is online.

Fetch. Ai is running an incentive test net for three topics, taking us to mainnet version 2. Each test net will run for approximately 6 weeks and will be arranged by incentive grouping. As each excitation test net is completed, it is reset and a new test net is created. This will reset the state, and testing and work will focus on adding new features. With each step in the process, we are getting closer to a fully functional Fetch V2 mainnet. When the snazzy incentive test network is complete, main network V2 will be started. The three phases are: Phase 1: Incentives with agency themes and some governance Phase 2: incentives related to DRBS, node operations and governance Phase 3: incentives designed to provide prognosticators and connect the world with trusted information