What is Fetch.ai (FET)?
Fetch.ai (FET) is an innovative project that can change the world. It is an innovative platform that connects IoT (Internet of Things) devices and algorithms to enable collective learning. Built on a high-throughput sharded ledger, the Fetch.ai architecture offers a unique smart contract capability to deploy ML (Machine Learning)/AI (Artificial Intelligence) solutions for decentralized problem solving.
Open source tools allow users to create various eco-structures (ecosystem infrastructures) and deploy new trading models.
The Fetch.ai team is a dynamic, fast-growing international team of engineers and forward-thinking technology researchers working on the convergence of Blockchain, AI and multi-agent systems. They aim to build technology for both today and tomorrow; Fetch.ai (FET) is described as a collective super intelligence on top of the decentralized economic internet built with highly scalable next-generation distributed ledger technology. Combined with machine learning, this provides predictions and infrastructure that will power the economy of the future.
The Fetch.ai (FET) team believes its technology will improve the way we communicate, giving people, organizations and the “Internet of Things (IoT)” a voice and new opportunities, effectively democratizing the space and improving the lives of citizens.
Who are the Founders of Fetch.ai (FET)?
Fetch.ai (FET) was founded by Toby Simpson, Humayun Sheikh and Thomas Hain. Humayun Sheikh is the current CEO of Fetch.ai. He is also the CEO and founder of Mettalex, as well as the founder of uVue and itzMe. Toby Simpson is the COO of Fetch.ai. He was also CTO at Ososim Limited and head of software design at DeepMind. Thomas Hain is the Chief Science Officer at Fetch.ai. Before that, he was co-founder and executive of Koemei.
Fetch.ai's CTO is Toby Simpson, who has over a decade of experience in CTO roles at other technology companies. He was also involved with DeepMind, where he served as Head of Software Design.
Third Fetch.ai co-founder and Chief Science Officer, Thomas Hain, holds a PhD from the University of Cambridge and specializes in Machine Learning. In addition to his role at Fetch.ai, he is also a professor at the University of Sheffield.
In addition to the co-founders, the leadership team includes Jonathan Ward (Head of Research), Troels F. Rønnow (Head of Software Engineering), Maria Minaricova (Head of Business Development) and Arthur Meadows (Head of Investor Relations). The rest of the Fetch.ai team consists of 10 developers, 11 researchers and 5 administrative staff.
What Makes Fetch.ai (FET) Unique?
Fetch.ai's utility token, FET, is designed to find, create, distribute and train autonomous economic agents and is a key part of smart contracts and oracles on the platform.
Thanks to the use of FET, users can create and deploy their own agents on the network. By paying with FET tokens, developers can access machine learning-based utilities to train autonomous agents and deploy collective intelligence across the network.
Validation nodes are also activated by acquiring FET tokens, which ultimately facilitates network verification and reputation.
Fetch.ai Blockchain:
It combines multiparty cryptography and game theory to provide secure, censorship-resistant consensus along with fast chain synchronization to support broker applications.
When it comes to the core components of the platform, there is a “learner” part where each participant becomes a learner in the experiment, representing a unique proprietary dataset and machine learning system. There is also the global market, which is the result of the collective learning experiment, where the machine learning model is mass trained by the learners themselves. Then there is the Fetch.ai Blockchain, which supports smart contracts that allow for coordination and governance in a secure and auditable manner. Finally, there is the decentralized data layer based on IPFS, which enables the sharing of machine learning weights among all relevant learners.
Machine Learning (ML) and Artificial Intelligence (AI)
Fetch.ai (FET) includes machine learning and artificial intelligence at all three layers of its protocol. They are used to provide trust information at four different layers:
Confidence in how normal any transaction is.
Trust in information received from other nodes in the network.
Trust in the parties involved based on their history.
Emerging market and data intelligence.
Finally
Fetch.ai is one of the more ambitious blockchain projects as it also tries to integrate artificial intelligence. There is great hope for success as the team appears to have the skills, knowledge and industry experience to create something that can solve countless real-world problems across a variety of industries, from supply chain to energy and much more.
