Safe & secure Red Genesis wallet
Take control of your Red Genesis assets with complete confidence in the Trezor ecosystem.
- Secured by your hardware wallet
- Use with compatible hot wallets
- Trusted by over 2 million customers
Send & receive your Red Genesis with the Trezor Suite app
Send & receive
Trezor hardware wallets that support Red Genesis
Sync your Trezor with wallet apps
Manage your Red Genesis with your Trezor hardware wallet synced with several wallet apps.
Trezor Suite
Backpack
NuFi
Supported Red Genesis Network
- Solana
Why a hardware wallet?
Go offline with Trezor
- You own 100% of your coins
- Your wallet is 100% safe offline
- Your data is 100% anonymous
- Your coins aren’t tied to any company
Online exchanges
- If an exchange fails, you lose your coins
- Exchanges are targets for hackers
- Your personal data may be exposed
- You don’t truly own your coins
How to $R3D on Trezor
Connect your Trezor
Open a third-party wallet app
Manage your assets
Make the most of your $R3D
Trezor keeps your $R3D secure
Protected by Secure ElementThe best defense against both online and offline threats
Your tokens, your controlAbsolute control of every transaction with on-device confirmation
Security starts with open-sourceTransparent wallet design makes your Trezor better and safer
Clear & simple wallet backupRecover access to your digital assets with a new backup standard
Confidence from day onePackaging & device security seals protect your Trezor’s integrity
DeBot.Science is a decentralized platform focused on training and optimizing robotics models for complex environments. Using large-scale reinforcement learning and distributed compute resources, the project aims to develop adaptable, autonomous robots capable of navigating and interacting with challenging terrains, such as simulated Martian surfaces.
The project operates under a community-driven model, with $R3D as its native token. $R3D is utilized to support research, incentivize participation, and scale the training processes, aligning contributors with the long-term vision of advancing robotics and artificial intelligence. DeBot.Science leverages innovative methodologies like cross-stage policy transfer, domain randomization, and hybrid learning frameworks to ensure high adaptability and efficiency in robot training.
By combining decentralized technologies with cutting-edge robotics research, DeBot.Science seeks to bridge the gap between theoretical AI advancements and practical, real-world applications.