New York, NY – 03/28/2024 – (SeaPRwire) – In an innovative move that is set to change the way that liquid staking works on the Bittensor network, Gradient Protocol has introduced a novel approach to validation across the network’s many subnets. This recent strategy serves as a testament to Gradient Protocol’s mission to enhance its network performance, increase the overall yield on staked assets, and enhance security across its liquid staking operations.
The strategy consists of utilizing the very many subnets available on the Bittensors network architecture. By opening a number of different validators across a range of subnets, the Gradient Protocol can ensure that their validation is taking advantage of the subnet’s varying ROI, as well as making the most of the TAO tokens that are being staked.
Validating Across a Range of Subnets – A More Scalable Liquid Staking Solution
Gradient Protocol has been at the forefront of liquid staking innovation for the TAO network. With their initial validator running on subnet 18 ( Coretex.t ) without any problems, the team has announced that they’re working towards improving internal hardware as well as purchasing additional server space so more validators can go live on more subnets.
It serves as an important note that Bittensor validation comes with a couple of key differences when compared to more traditional networks such as Ethereum. Different subnets on Bittensor serve different purposes, and validating across a number of them enhances the network’s overall performance, security, and scalability.
About Gradient
Gradient Protocol developed from an innovative vision to set the stage for the liquid staking landscape within the Bittensor network. By leveraging the power of decentralized staking methods, Gradient aspires to offer a sustainable, high-yielding, and truly decentralized platform. The protocol’s growth is marked by significant milestones in network validation diversity and highlights its potential to further substantiate the growth of the TAO network as a whole.
Social Links
X: https://twitter.com/Gradient_GDT
Documentation: https://docs.gradientprotocol.io/
Telegram: https://t.me/Gradient_Entry
Media Contacts
Brand: Gradient Protocol
Contact: David F. (BD)
Website: https://gradientprotocol.io/
SOURCE: Gradient Protocol
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