The idea that you can store money in crypto, privately, without volatility, is a new concept. $XHV $xUSD 2/
The brilliance of the one and only private algorithmic stable coin in crypto..... A thread. 1/ $XHV $xUSD
The idea that you can store money in crypto, privately, without volatility, is a new concept. $XHV $xUSD 2/
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Back with another #FreeLoveFriday. Last time, we covered how Mastercoin/@Omni_Layer pioneered digital asset issuance on blockchains. Today, let’s discuss @Chainlink and the vital role it plays in connecting blockchains to the real world.
I have said repeatedly that digital asset issuance is the killer application for blockchains. The next frontier is bringing real world assets to networks like @AvalancheAVAX, but we often face a significant problem:
Namely, how do you get data from the real world onto blockchains and into applications running on them? More critically, how do you achieve that securely and transparently in real-time? Smart contracts are tamper-proof, but they're only as reliable as their input data.
Enter ChainLink in September 2017, with a whitepaper outlining a vision for a decentralized network of “oracles,” entities that inject facts from the external world into blockchains in a suitable format for smart contracts.
Until ChainLink, oracles were trusted and centralized. This is a huge problem for high-value assets and smart contracts. High value projects, such as @CelsiusNetwork, @synthetix_io, @Aaveaave and others depend critically on oracle data.
Back with another #FreeLoveFriday. My first thread focused on what I love about Bitcoin, and features we borrowed for @AvalancheAVAX. Today, let's focus on @Omni_Layer, or as OGs knew it, Mastercoin https://t.co/fXFgmaeUEz
— Emin G\xfcn Sirer (@el33th4xor) January 15, 2021
I have said repeatedly that digital asset issuance is the killer application for blockchains. The next frontier is bringing real world assets to networks like @AvalancheAVAX, but we often face a significant problem:
Namely, how do you get data from the real world onto blockchains and into applications running on them? More critically, how do you achieve that securely and transparently in real-time? Smart contracts are tamper-proof, but they're only as reliable as their input data.
Enter ChainLink in September 2017, with a whitepaper outlining a vision for a decentralized network of “oracles,” entities that inject facts from the external world into blockchains in a suitable format for smart contracts.
Until ChainLink, oracles were trusted and centralized. This is a huge problem for high-value assets and smart contracts. High value projects, such as @CelsiusNetwork, @synthetix_io, @Aaveaave and others depend critically on oracle data.
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1/OK, data mystery time.
This New York Times feature shows China with a Gini Index of less than 30, which would make it more equal than Canada, France, or the Netherlands. https://t.co/g3Sv6DZTDE
That's weird. Income inequality in China is legendary.
Let's check this number.
2/The New York Times cites the World Bank's recent report, "Fair Progress? Economic Mobility across Generations Around the World".
The report is available here:
3/The World Bank report has a graph in which it appears to show the same value for China's Gini - under 0.3.
The graph cites the World Development Indicators as its source for the income inequality data.
4/The World Development Indicators are available at the World Bank's website.
Here's the Gini index: https://t.co/MvylQzpX6A
It looks as if the latest estimate for China's Gini is 42.2.
That estimate is from 2012.
5/A Gini of 42.2 would put China in the same neighborhood as the U.S., whose Gini was estimated at 41 in 2013.
I can't find the <30 number anywhere. The only other estimate in the tables for China is from 2008, when it was estimated at 42.8.
This New York Times feature shows China with a Gini Index of less than 30, which would make it more equal than Canada, France, or the Netherlands. https://t.co/g3Sv6DZTDE
That's weird. Income inequality in China is legendary.
Let's check this number.
2/The New York Times cites the World Bank's recent report, "Fair Progress? Economic Mobility across Generations Around the World".
The report is available here:
3/The World Bank report has a graph in which it appears to show the same value for China's Gini - under 0.3.
The graph cites the World Development Indicators as its source for the income inequality data.
4/The World Development Indicators are available at the World Bank's website.
Here's the Gini index: https://t.co/MvylQzpX6A
It looks as if the latest estimate for China's Gini is 42.2.
That estimate is from 2012.
5/A Gini of 42.2 would put China in the same neighborhood as the U.S., whose Gini was estimated at 41 in 2013.
I can't find the <30 number anywhere. The only other estimate in the tables for China is from 2008, when it was estimated at 42.8.