Zenqira concludes its first private sale of ZENQ tokens and announces a new sale slot, aiming to democratize access to AI training resources.
Points
- Zenqira’s first private sale of ZENQ tokens concludes successfully.
- New private sale slot to start on August 14, 2024.
- Zenqira aims to democratize AI training resources through decentralized computing.
- ZENQ token drives the ecosystem, offering incentives and premium access.
Zenqira, a decentralized computing platform dedicated to democratizing access to AI training resources, has announced the successful conclusion of its first private sale of ZENQ tokens. Due to high demand, a new private sale slot is scheduled to commence on August 14, 2024.
Zenqira leverages cutting-edge decentralized computing technology to provide unparalleled access to AI training resources. By connecting global computing providers with AI developers, Zenqira is reshaping the AI landscape through collaboration, innovation, and advanced technology.
The ZENQ token is central to the Zenqira platform, rewarding participants who share their computational power and thus expanding the network and enhancing AI capabilities. Key utilizations of the ZENQ token include:
- Incentives: Encouraging resource sharing and collaboration within the ecosystem.
- Access: Unlocking premium features on the Zenqira platform.
- Discounts: Offering significant savings on computing services.
- Community Building: Strengthening connections within the tech ecosystem.
Zenqira employs a deflationary model to ensure the stability and value of the ZENQ token. Fifteen percent of net revenues from platform service fees, computing resource transactions, and data analytics services are allocated for ZENQ liquidity, with excess tokens strategically burned to manage supply.
The initial private sale of ZENQ tokens has seen tremendous success, and the upcoming private sale slot provides another opportunity for interested participants to join the Zenqira revolution. Zenqira invites AI innovators, developers, and computing resource providers to connect with expert advisors and collaborators and be part of the future of decentralized AI computing.
解説
- Decentralized computing: A distributed computing environment where computing resources and data are decentralized across multiple locations.
- Deflationary model: A system where the supply of tokens decreases over time, typically through token burns, to increase value.
- AI training resources: Computational resources and data sets required to train artificial intelligence models.