Fetch is a next-generation protocol built with a ready-to-go Useful Proof of Work system invented by world-leading AI minds.
Returns Since ICO
- ICO Price in USD: $0.0341. ROIx in USD: 5.88x USD
Problems & Solutions
Fetch AI is incorporated in the UK with an aim to create a digital economy where autonomous agents can interact with one another without human intervention. The environment will create a decentralised digital world to perform useful economic work where information trades effortlessly. There is a plethora of applications that can be adopted, but the overall bottom line is to bring data to life.
Here are several issues that Fetch AI seeks to resolve:
- Creating economic efficiencies by providing market intelligence to prevent issues such as shipping empty containers and energy waste by power grids
- The “disconnect” between centralised systems as they cannot effectively communicate with one another
- Scalability of distributed ledger technology
Features & Highlights
- Digital infrastructure for deployment of Multi Agent Systems
- Unique scalable ledger to support high transaction rates
- Synergetic computing: Intelligent smart contracts for autonomous systems
- Economic framework for governing dynamic marketplaces
- Semantic, geographic and decision based navigation for autonomous agents to deliver seamless problem solving
Token Sale & Economics
- Project website: https://fetch.ai/
- Project whitepaper: https://fetch.ai/technical-introduction
- Token sale start time: TBA
- Ticker: FET
- Token type: ERC20
- Total hard cap: $21,000,000
- Total supply: 1,152,997,575 FET
- Public sale token price: 1 FET = $0.0867
- Private sale vesting period: Vesting monthly over 3 months thereafter
- Seed sale vesting period: Vesting monthly over 3 months thereafter
Token Utility & Use Cases
Fetch.AI tokens can be used for many purposes, the largest six of which are:
- Ability to connect agents and nodes to the network: FET is an access deposit token that acts as a form of stake to demonstrate desire to behave appropriately. It modulates the ability for bad actors to flood the network with undesirable nodes or agents due to the escalating cost of doing so. Fetch.AI are performing modelling and simulations on their testnets (both public and private) during the first half of 2019 to determine what this stake should be.
- Value exchange between agents: The Fetch.AI token is required in order to allow for two agents, regardless of where they are, to perform a value exchange. The Fetch.AI token is infinitely divisible, thereby supporting transactions that have very low monetary value, but in aggregate provide new and profound level of insight and opportunity.
- Access to search and discovery, and advertisement services: Fetch.AI tokens are needed to access, view and interact with the Fetch.AI search engine. This is a space optimized for autonomous digital entities, providing dynamic and autonomous price setting and negotiation.
- Access to Fetch’s multi-dimensional digital world: Fetch.AI tokens allow agents to view and explore its digital space geographically, semantically or economically. Some of these detailed views involve considerable computing time and communications between many nodes. These more resource intensive operations will require more tokens. Fetch’s AI and ML constantly restructure this world to optimize each agent’s individual view.
- Ability to access and develop ledger-based AI/ML algorithms: The Fetch.AI token enables development of and access to a broad range of machine learning and artificial intelligence tasks that are available on the ledger. These may be Fetch-developed primary services such as trust and prediction models, or they may be large-scale independently developed services for network users.
- For exchange into Fetch’s operational fuel: Operation costs in Fetch.AI are decoupled from the Fetch.AI token in a similar way to that of "gas" on the Ethereum network, but with additional functionality designed to increase the stability of such a fuel and look at addressing issues associated with high and low-velocity economies. Fetch’s operational fuel allows access to processor time for contract execution and services for agents.
Sample Target Use Cases:
- Transport: Fetch.AI is working on reducing laborious travel planning tasks by using expert autonomous economic agents to organize complex trips, predict potential misconnections and dynamically reroute journeys, rearrange travel plans and rebooking reservations without intervention. The goal is to improve users’ and transport providers’ efficiency, service levels and satisfaction.
- Energy: Fetch.AI is working on creating a fluid energy model to deliver the most effective energy solution to households without the friction of switching suppliers. Consumers could potentially change providers down to the minute or even by each appliance’s unique energy demands. Fetch.AI is working with Warwick University on creating and deploying a live energy balancing simulation.
- Supply Chain: Fetch.AI is enabling the trillion dollar steel sector to autonomously and collaboratively self-manage. It is now able to optimize its supply chain from the raw materials to the finished product, giving it the opportunity to massively reduce costs and improve efficiency.
Fetch.AI is also working on building collective prediction models to improve efficiency in cargo rail route in collaboration with a German team.
Roadmap & Updates
- Phase 1 - By Invite Testnet (Feb 2019) - Development release
- Access to private test network extended by invite for network participation and wallets
- Phase 2 - Public Testnet (Apr 2019) - Full public test network with smart contracts
- Includes enhanced Open Economic Framework ("OEF") search capabilities
- Phase 3 - Smart Market Testnet (Jun 2019) - Consensus, synergetic computing, & auctions
- Full Fetch.AI consensus with multi-party & multi-dependency auctions and computing
- Launch Phase begins (Jul 2019) - Alpha
- Delivers the initial mainnet OEF and ledger functionality in its initial form. All building blocks will be present
- End of Sept 2019 - Beta
- All expected mainnet functionality undergoing tuning, optimisations and tweaks. Beta will extend out to the mainnet release
- End of Dec 2019 - Mainnet
- Initial release of the Fetch.AI main network powered by the native on-chain Fetch.AI token (FET)
Humayun Sheikh, CEO & Co-Founder, An innovation entrepreneur, founding investor in DeepMind with a record in revolutionising trading in steel sector and now changing the way we transact and travel. Linkedin.
Toby Simpson, CTO & Co-Founder, Producer of the successful a-life Creatures series of games and early developer at Deepmind. His thirty years’ experience in software, ten as a CTO, are now focussed on crypto-economics. Linkedin.
Thomas Hain, CSO & Co-Founder, Professor at Sheffield and established scientist in advanced machine learning AI who bridges real world and academia and is inspired by the opportunities AI brings to modern society. Linkedin.
Jonathan Ward, Head of Research, A researcher in machine learning, complex systems and blockchain technology. Excited by the challenge of deploying decentralized multi-agent systems in smart cities, supply chain and healthcare. PhD in Machine Learning from UCL. Linkedin.
Troels Rønnow, Head of Software Engineering, A scientist and innovator, that benchmarked D-Wave Two, co-authored 35 patent applications who has been working more than two years full time building distributed ledgers. Linkedin.
Maria Minaricova, Head of Business Development, Experienced in managing strategic program delivery, business development and the application of state-of-the-art ICTs. Worked at Oracle and at Europe’s e-infrastructure GEANT collaborated with flagship pan-European research groups and e-infrastructures. Linkedin.
Arthur Meadows, Head of Investor Relation, International experience in software start-ups and bringing disruptive, high-growth tech products to commercial success. MBA from Judge Business School, University of Cambridge. Linkedin.
Michael Wooldridge, Advisor, Head of Department and Professor of Computer Science at the University of Oxford. Recipient of the ACM Autonomous Agents Research Award. Former President of the International Joint Conference on Artificial Intelligence (IJCAI). Linkedin.
Kash Iftikhar, Advisor, Kash Iftikhar is Vice President of product, strategy & GTM for Oracle Cloud Infrastructure. He previously worked at PLUMgrid, a software defined networking start-up which was acquired by VMware. He has also held executive management positions at Force10 Networks and Cisco. Linkedin.
Monique Gangloff, Advisor, Principal investigator/senior scientist at the University of Cambridge, Department of Biochemistry. Her research endeavours have resulted in more than 35 international peer-reviewed publications and 1 patent application. Linkedin.
Melvyn Weeks, Advisor, Assistant Professor in Economics at University of Cambridge, researching the application of Machine Learning to market pricing. Senior Economic Advisor to Ofgem, UK’s Energy regulator. Linkedin.
Abe Ulusal, Advisor, Abe Ulusal is an executive director at Mitsui Bussan Commodities Limited and the former chairman of the London Metal Exchange Steel Committee. Linkedin.
Phillip Price, Advisor, Phillip Price is deputy chairman of the London Metal Exchange Steel Trading Committee and is a founding partner of Ferrometrics LLC, a company that specialises in developing liquidity in nascent derivatives markets. Linkedin.
Jonathan Fish, Advisor, Jonathan Fish has spent his career in the commodities sector. He began at EDF Trading, before spending nine years managing risk positions for Goldman Sachs. In 2015 he co-founded the highly successful coal trading house Javelin Commodities Trading.
Jamie Burke, Advisor, Founder and CEO of Outlier Ventures, Jamie has cultivated a powerful ecosystem of corporate partners, investors and government agencies to help companies scale. He also advocates for the professionalisation of the industry through international media. Linkedin.
Steve Grand, Advisor, An inventor of complex autonomous agents for nearly 40 years, creator of the Creatures artificial life games and proud father to a small robot now in the Science Museum, Steve has held research fellowships in artificial life, psychology, biomimetics and creative technologies. He received a D.Univ from the OU and was made an OBE in 2000 for Services to Computing. Linkedin.
Niall Armes, Armes is a world-leading biochemist, molecular biologist and entrepreneur. He received his PhD from the Imperial Cancer Research Fund in London for work on comparative genome structure. He subsequently founded TwistDx, serving as CSO and CEO prior to the company’s acquisition. Linkedin.
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Blocktopian - The company is a multinational consulting and media company for the blockchain. With New York as the central node, Shanghai, Beijing, and Shenzhen as secondary nodes, the company provides consulting, media, promotion and research services for blockchain startups, and is committed to incubating investment-grade high-quality blockchain projects. The company customizes high KPI services for customers by arranging vertical areas of blockchains at home and abroad.
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