5.1%
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 Read more
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.
DeBot.Science is a decentralized platform focused on training and optimizing robotics models for com Read more
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.
The community is experiencing rapid growth.
The follower growth appears organic and healthy.
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🔔 Get Anomaly AlertsMarket Cap
Fully Diluted Valuation
Volume 24h
All Time High Jan 07 2025
ATH Circulating Supply
Total Supply
Max Supply
All Time Low Feb 18 2025
Red Genesis's community is presently earning an 'A' grade due to an impressive level of interactions relative to the number of followers. It has a small follower base and experiencing booming growth. The community is less active than most along with a predominantly neutral sentiment among its members.
| Development | 24 h | 7 d | 14 d | 30 d |
|---|---|---|---|---|
| Price | 5.1% | 0.4% | 13.03% | 95.64% |
| Follower | 0.27% | 0.54% | 6.26% | 78.27% |
Daily relevant Posts from Twitter, Telegram and Reddit ranked by our Smart Relevance Score.
Unfortunately, we do not have access to postings within this community at this time. If you have noticed that we do not connect all channels of the community, please let us know via the contact form.
Thank you for your support!
5.1%
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 Read more
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.
DeBot.Science is a decentralized platform focused on training and optimizing robotics models for com Read more
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.
| Development | 24 h | 7 d | 14 d | 30 d |
|---|---|---|---|---|
| Price | 5.1% | 0.4% | 13.03% | 95.64% |
| Follower | 0.27% | 0.54% | 6.26% | 78.27% |
Market Cap
Fully Diluted Valuation
Volume 24h
All Time High Jan 07 2025
ATH Circulating Supply
Total Supply
Max Supply
All Time Low Feb 18 2025
The community is experiencing rapid growth.
The follower growth appears organic and healthy.
Be the first to know about suspicious activities around your watchlist's coins.
🔔 Get Anomaly Alerts
Daily relevant Posts from Twitter, Telegram and Reddit ranked by our Smart Relevance Score.
Unfortunately, we do not have access to postings within this community at this time.
If you have noticed that we do not connect all channels of the community, please let
us know via the contact form.
Thank you for your support!
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