2/ #Ethereum bot ecosystems often unintentionally evolve to single-bot-wins situations, where it is pointless & costly to run a bot that consistently comes in "2nd place"
3/ Bot 1 consistently wins liquidation auctions. It becomes unprofitable for others to play the game, resulting in a single player game. If the player (Bot 1) leaves or malfunctions, no other bots step up and take its place, due to incentives & deteriorated ecosystem.
4/ Some commonly used #Ethereum#DeFi systems suffer from bot monoculture, and heavy reliance on some centralized piece of trustless infrastructure, and are more fragile than they appear on the surface.
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1/ Yesterday: My L1 chain has better, faster tech than #Bitcoin or #Ethereum. It is not compatible with existing software or tooling, but will nevertheless overcome network effect and momentum to become the next Ethereum. Invest in my Ethereum killer.
2/ Today: My L2 rollup chain has better, faster tech than #Bitcoin or #Ethereum. It is not compatible with existing software or tooling, but will nevertheless overcome network effect and momentum to become... Invest in my...
3/ Investors routinely underestimate the value of iterative evolution - trial-and-error over time - sunk into software, tooling, auditing software libraries & the 1,000 other elements of a software ecosystem.
Smart competitors build on top of that, rather than starting from zero
Finally spent some time studying #Ethereum Merkle Patricia Tree github.com/ethereum/wiki/… 1. It is an elegant data structure for Eth, creating a cryptographically stable merkle root, no matter the data insertion order. 2. Oh boy, it really punishes your hard drive storage.
In my past life at Red Hat, I wrote the ATA (aka IDE) drivers for Linux, so I know a bit about data storage and hard drives.
Here is why Eth is so punishing on data storage, and why SSDs/NVMe are a field requirement for Eth:
Like Bitcoin, Eth has poor cache locality:
* Huge db, which means each Next Page is less likely to be in page/disk cache.
* Keys are hashes, which means each Next Query Key is uniformly random, and therefore equally unlikely to be “close” to any recent past query.