Artificial Superintelligence Alliance released ASI:Work, an AI desktop application that processes files and requires user approval for each step. It supports business workflows and coding tasks, including reading local repositories, proposing changes and running tests.
Refer to the official tweet by FET:
🚨 https://t.co/CwbPmOiA4m just launched ASI:Work. An AI desktop app that does the work on your files.
Point it at a folder. Describe the job. Approve every step. Come back to finished work.
2 ways to use it:
→ Work: content, marketing, data, sales prep, ops
→ Coding: reads… pic.twitter.com/EOUtVwyhmR— Fetch.ai (@Fetch_ai) October 28, 2026
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.
