Red Genesis Price ($r3d/CAD)

Red Genesis
Currency
Red Genesis
Red Genesis
$R3D
Red Genesis Price ($R3D/CAD)
$0.000013
Price Change 24h
$0.00
24h Low / 24h High
$0.00 / $0.00
Market Cap
$13,030.97
Fully Diluted Market Cap
13,210.53
Market Rank
#11445
Bitcoin
Bitcoin
BTC
Bitcoin Price (BTC/CAD)
$127,731.84
Price Change 24h
$2,025.38
1.61%
24h Low / 24h High
$125,103.00 / $128,275.00
Market Cap
$2,551,706,280,337.00
1.63%
Fully Diluted Market Cap
2,551,706,280,337
Market Rank
#1
Ethereum
Ethereum
ETH
Ethereum Price (ETH/CAD)
$4,347.60
Price Change 24h
$24.05
0.56%
24h Low / 24h High
$4,262.75 / $4,357.53
Market Cap
$524,711,546,106.00
0.68%
Fully Diluted Market Cap
524,711,546,106
Market Rank
#2
Tether
Tether
USDT
Tether Price (USDT/CAD)
$1.39
Price Change 24h
$0.001
0.07%
24h Low / 24h High
$1.39 / $1.39
Market Cap
$259,226,185,549.00
0.05%
Fully Diluted Market Cap
266,807,354,019
Market Rank
#3
BNB
BNB
BNB
BNB Price (BNB/CAD)
$1,260.82
Price Change 24h
$10.91
0.87%
24h Low / 24h High
$1,241.62 / $1,267.69
Market Cap
$173,660,739,711.00
0.88%
Fully Diluted Market Cap
173,660,739,711
Market Rank
#5
XRP
XRP
XRP
XRP Price (XRP/CAD)
$2.86
Price Change 24h
$0.02
0.72%
24h Low / 24h High
$2.84 / $2.91
Market Cap
$173,599,574,820.00
0.7%
Fully Diluted Market Cap
285,955,349,218
Market Rank
#4
Official Site
GitHub
White Paper
Official Site
GitHub
White Paper

Red Genesis market data

Trading Volume
24h
Circulating Supply
985,397,708.014344
98.641%
Volume / Market Cap
$0.00 / 0
Market Dominance
0%
Total Supply
998,975,428.247672
BID
N/A
ASK
N/A
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What Is Red Genesis ($R3D)?

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.

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