Raven Protocol

9.09 %
Change 24h
Current Currency Market: #Raven Protocol(#RAVEN) price: $0.001136, +9.09% up
#链情: #Raven Protocol(#RAVEN) 价格: $0.001136, 上涨9.09%


Raven Protocol(RAVEN) current price is $0.001136 with a market cap of $ 4,948,070. Its price is +9.09% up in last 24 hours.
Raven Protocol(RAVEN)当前价格为$0.001136, 市值$ 4,948,070 其价格在过去24小时内上涨+9.09%。


tags: Current Currency Market, Mars Soon, Satoshi Go, Market Cap, Trend, Raven Protocol, RAVEN
区块链, 数字货币, 行情, 聪购, 链情, Current Currency Market, Mars Soon, Satoshi Go, , Raven Protocol, RAVEN
Market Cap
$ 4,948,070
Volume 24h
$ 20,491
Circulating Supply
Total Supply
Raven Protocol's specific use case is to perform AI training where speed is the key. We're taking a 1M image dataset that takes 2-3 weeks to train on AWS down to 2-3 hours on Raven. AI companies will be able to train models better and faster. Raven Protocol is creating a self-sustaining and dynamic ecosystem for: Customers who want to train their AI engines; and/or Contributors who would like to share their compute resources in the form of Computers, Smartphones, or even a server rack. Raven Tokens (RAVEN) will work as the common ground to facilitate a secure transaction that will take place inside our ecosystem. Enterprise clients who want to rent compute power will do so with RAVEN and contributors of the compute power will be rewarded in RAVEN. Raven is creating a network of compute nodes that utilize idle compute power for the purposes of AI training where speed is the key. A native token is the key to bootstrapping a nascent network. We want to incentivize and reward people all over the world to contribute their compute power to our network. Additionally, we will reward token holders for running masternodes which will be responsible for orchestrating the training of various deep neural networks. Our consensus mechanism is something we call Proof-of-Calculation. Proof-of-Calculation will be the primary guideline for the regulation and distribution of incentives to the compute nodes in the network. Following are the two prime deciders for the incentive distribution: Speed: Depending upon how fast a node can perform gradient calculations (in a neural network) and return it back to the Gradient Collector. Redundancy: The 3 fastest redundant calculation will only qualify for receiving the incentive. This will make sure that the gradients that are getting returned are genuine and of the highest quality.
We Use Cookies
We use cookies to ensure that we give you the best experience on our website. If you continue to use this site we will assume that you are happy with it.