Fetch.ai to Hold Hackathon
Fetch.ai will participate in the Web Weaver Hackathon at Pune Institute of Computer Technology (PICT). The event, organized by IEEE, is set to take place from April 19th to 21st.
During the hackathon, participants will be tasked with utilizing Fetch.ai’s Agents to develop a unique AI Agent solution. This solution is expected to include an external integration.
Refer to the official tweet by FET:
Fetch.ai@Fetch_aiAbr 18, 2024We're proud to announce that we are the Title Sponsor for the Web Weaver #hackathon at @PunePict organized by @IEEEorg! 🙌
Participants are challenged to use our Agents to create a unique #AIAgent solution, including an external integration! 🔌
🗓ï¸ April 19th-21st 2024 pic.twitter.com/XcrSvmAZ6z
FET Info
Fetch.ai's FET, a utility token, is the bedrock for discovering, creating, deploying, and training digital twins, playing an essential role in smart contracts and oracles on the platform. With FET, users can build and deploy their digital twins on the network. The token also allows developers to access machine-learning utilities for training autonomous digital twins and deploying collective intelligence on the network. Additionally, validation nodes can stake FET tokens to facilitate network validation, enhancing their reputation in the process.
The technological architecture of Fetch.ai consists of four distinctive elements. The Digital Twin Framework offers modular components to help teams construct marketplaces, skills, and intelligence for digital twins. The Open Economic Framework provides search and discovery capabilities for digital twins. The Digital Twin Metropolis is a collection of smart contracts that maintain an immutable record of agreements between digital twins on a WebAssembly (WASM) virtual machine. Lastly, the Fetch.ai Blockchain employs multi-party cryptography and game theory to ensure secure, censorship-resistant consensus and rapid chain-syncing to support digital twin applications.
Among the platform's key components is the learner, wherein each participant represents a unique private dataset and machine learning system. The global market emerges as a product of a collective learning experiment, with a machine learning model trained by the learners collectively. The Fetch.ai Blockchain supports smart contracts, allowing secure and auditable coordination and governance. Finally, the platform includes a decentralized data layer based on IPFS, facilitating the sharing of machine learning weights among all learners involved.