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yeyell
@debgab
Parallel EVM is expected to become a hot narrative in 2024. @monad is worth keeping an eye on. 1/ What is Parallel EVM? The Ethereum Virtual Machine (EVM) follows a Last-In-First-Out (LIFO) operation principle, meaning transactions need to be executed one by one in sequence. Parallel EVM, on the other hand, allows multiple operations to be executed simultaneously. The advantages of Parallel EVM are clear: faster transaction speeds, greater processing capacity, and lower transaction costs. 2/ Project Introduction: @monad Monad is an EVM Layer 1 solution. Officially, it claims a processing speed of 10,000 transactions per second and a block time of 1 second, thanks to its MonadBFT consensus mechanism and EVM compatibility. For more technical details on its consensus mechanism, refer to the official documentation: MonadBFT Technical Discussion Hardware requirements for running Monad full nodes: CPU: 16-core CPU Memory: 32 GB RAM Storage: 2 TB NVMe SSD Bandwidth: 100 Mb/s
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yeyell
@debgab
For ordinary users, the experience will be very similar to Ethereum. You just need to add the network in MetaMask and can view it on the Etherscan explorer. This is a crucial advantage. According to its official Twitter, the testnet is 97% complete and should be released soon, though it won’t be open to regular users immediately. Apart from the technical narrative, the ecosystem and community progress are also very strong. For example, the AI project being built on the Monad chain, @monaidev, aims to address censorship issues in training large language models. Its token, $MONAI, has an FDV of $80 million. Here are some other projects that may be built on or collaborate with Monad: @PikeFinance - Cross-chain lending protocol @Monadiansio - Popular Monad NFT series @axelarnetwork - Cross-chain interoperability platform @pear_protocol - DeFi @wormholecrypto - Airdrops sent to some Monad users, indicating close ties.
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yeyell
@debgab
3/ Team Background The core team members come from top global universities. Both the founder and co-founder graduated from MIT. The founder previously worked at Jump Trading in quantitative trading.
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jAjaoqo
@ajsjsk
nice
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