Arbius is a decentralized network for machine learning and a token with limited inflation. It allows users to interact with AI models permissionlessly and democratizes AI by being controlled by its users.

What are the core features of Arbius?

The core features of Arbius include decentralized machine learning, customizable AI models, on-chain protocol upgrades, economic optimization, secure task completion, and integration with downstream applications.

How can I earn income with Arbius?

Users can earn income with Arbius by creating and holding AI models, participating in governance, staking LP tokens, validating the network, and promoting free and open AI.

What is the Arbius token supply and emission process?

Arbius has a max supply of 1 million tokens and follows a continuous halving process for minting. Task rewards and fees contribute to the token emission, which is governed by the smart contract.

How does Arbius ensure task accuracy and security?

As long as a majority of the solvers are honest, tasks are completed accurately within seconds. Additionally, Arbius is fully open-source, allowing for transparency and community auditing.

What is the role of the Arbius DAO?

The Arbius DAO, controlled by holders of Arbius tokens, operates entirely on-chain and 10% of all newly created Arbius is sent to the DAO. It plays a crucial role in the decentralized governance of the network.

Arbius: Decentralized Machine Learning for customizable AI models and economic optimization.

Name: Arbius
Rating: 5 (82 reviews)
Author: toolify

Sponsored by floatz AI - Supercharge Your Research, with AI.

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Introduction:

Decentralized Machine Learning for customizable AI models and economic optimization.

Added on:

Jan 22 2024

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Arbius Product Information

What is Arbius?

Decentralized Machine Learning

How to use Arbius?

Arbius is a decentralized network for machine learning and a token with limited inflation. Users can participate in the network by generating Staking Models, exploring the network, accessing governance documents, connecting with peer-to-peer machine learning, and reading the whitepaper.