@Polkadot is a platform on which blockchain networks are built and connected into one unified network. These connected chains, called parachains, form a living organism of networks all in sync and secure. This forms the foundation on which Web3 will be built.
Polkadot is complicated as hell! This 24-tweet thread is a beginner's guide to @Polkadot $DOT and @KusamaNetwork $KSM in simple English.
What is Polkadot? Kusama? Parachains? Crowdloan and Parachain slot auction?
Comment with other questions and share if you learn something ⤵️
@Polkadot is a platform on which blockchain networks are built and connected into one unified network. These connected chains, called parachains, form a living organism of networks all in sync and secure. This forms the foundation on which Web3 will be built.
Think of it as drag-and-drop blockchain consensus, or even easier, like Music EQ with dials up & down on certain features.
Dev teams use @Polkadot's Substrate framework to build custom chains for a specific use/vertical, such as @AcalaNetwork for DeFi, @PhalaNetwork for Privacy, @chainlink for Oracles, or @hydra_dx for liquidity.
Legacy networks like #Ethereum are called "layer 1" chains. These are single blockchains, operating in isolation. Parachains are also layer 1 chains. Polkadot is one level below, a "layer zero" multi-chain growing to 100+ networks.
@Polkadot will be bridged to existing networks like @ethereum and #bitcoin via bridges built by teams like @InterlayHQ (BTC), @snowfork_inc (ETH), @ChainSafeth & @centrifuge (ETH), @chainx_org (BTC), and more.
Kusama is essentially the exact same code/archtr as Polkadot, but its on-chain governance moves 4x faster (7 days) and there are lower barriers to entry for teams to get a slot on the network (more on this below).
The model is Testnet->Kusama mainnet->Polkadot mainnet.
This ensures code is as flawless as possible before going to @Polkadot
For the sim/difs between @Polkadot and Kusama, check out this post: https://t.co/3aYG3jWTgo
Teams like Acala are launching @AcalaNetwork on Polkadot and @KaruraNetwork on Kusama. @purestakeco is similarly launching Moonbeam (DOT) & Moonriver (KSM).
@Polkadot has 100+ parachain "slots" (see below) which must be 'leased' for access to Polkadot's security and ability to communicate with other chains.
In fact, no team is "built on Polkadot" until they win an auction!
Candle auction: https://t.co/6ZI6hwNux1
This will enable an meta-infrastructure running myriad blockchains and applications on those chains, all in sync and sharing security.
Just like the databases/protocols powering the apps we use every day, end users and consumers shouldn't even know Polkadot and Kusama are there: Web3 apps that operate as good or better than their Web2 counterpart.
More from Tech
A brief analysis and comparison of the CSS for Twitter's PWA vs Twitter's legacy desktop website. The difference is dramatic and I'll touch on some reasons why.
Legacy site *downloads* ~630 KB CSS per theme and writing direction.
6,769 rules
9,252 selectors
16.7k declarations
3,370 unique declarations
44 media queries
36 unique colors
50 unique background colors
46 unique font sizes
39 unique z-indices
https://t.co/qyl4Bt1i5x
PWA *incrementally generates* ~30 KB CSS that handles all themes and writing directions.
735 rules
740 selectors
757 declarations
730 unique declarations
0 media queries
11 unique colors
32 unique background colors
15 unique font sizes
7 unique z-indices
https://t.co/w7oNG5KUkJ
The legacy site's CSS is what happens when hundreds of people directly write CSS over many years. Specificity wars, redundancy, a house of cards that can't be fixed. The result is extremely inefficient and error-prone styling that punishes users and developers.
The PWA's CSS is generated on-demand by a JS framework that manages styles and outputs "atomic CSS". The framework can enforce strict constraints and perform optimisations, which is why the CSS is so much smaller and safer. Style conflicts and unbounded CSS growth are avoided.
Legacy site *downloads* ~630 KB CSS per theme and writing direction.
6,769 rules
9,252 selectors
16.7k declarations
3,370 unique declarations
44 media queries
36 unique colors
50 unique background colors
46 unique font sizes
39 unique z-indices
https://t.co/qyl4Bt1i5x
PWA *incrementally generates* ~30 KB CSS that handles all themes and writing directions.
735 rules
740 selectors
757 declarations
730 unique declarations
0 media queries
11 unique colors
32 unique background colors
15 unique font sizes
7 unique z-indices
https://t.co/w7oNG5KUkJ
The legacy site's CSS is what happens when hundreds of people directly write CSS over many years. Specificity wars, redundancy, a house of cards that can't be fixed. The result is extremely inefficient and error-prone styling that punishes users and developers.
The PWA's CSS is generated on-demand by a JS framework that manages styles and outputs "atomic CSS". The framework can enforce strict constraints and perform optimisations, which is why the CSS is so much smaller and safer. Style conflicts and unbounded CSS growth are avoided.
Here is a simple example of a machine learning model.
I put it together a long time ago, and it was very helpful! I sliced it apart a thousand times until things started to make sense.
It's TensorFlow and Keras.
If you are starting out, this may be a good puzzle to solve.
The goal of this model is to learn to multiply one-digit
I put it together a long time ago, and it was very helpful! I sliced it apart a thousand times until things started to make sense.
It's TensorFlow and Keras.
If you are starting out, this may be a good puzzle to solve.
The goal of this model is to learn to multiply one-digit
It is a good example of coding, what is the model?
— Freddy Rojas Cama (@freddyrojascama) February 1, 2021
There has been a lot of discussion about negative emissions technologies (NETs) lately. While we need to be skeptical of assumed planetary-scale engineering and wary of moral hazard, we also need much greater RD&D funding to keep our options open. A quick thread: 1/10
Energy system models love NETs, particularly for very rapid mitigation scenarios like 1.5C (where the alternative is zero global emissions by 2040)! More problematically, they also like tons of NETs in 2C scenarios where NETs are less essential. https://t.co/M3ACyD4cv7 2/10
In model world the math is simple: very rapid mitigation is expensive today, particularly once you get outside the power sector, and technological advancement may make later NETs cheaper than near-term mitigation after a point. 3/10
This is, of course, problematic if the aim is to ensure that particular targets (such as well-below 2C) are met; betting that a "backstop" technology that does not exist today at any meaningful scale will save the day is a hell of a moral hazard. 4/10
Many models go completely overboard with CCS, seeing a future resurgence of coal and a large part of global primary energy occurring with carbon capture. For example, here is what the MESSAGE SSP2-1.9 scenario shows: 5/10
Energy system models love NETs, particularly for very rapid mitigation scenarios like 1.5C (where the alternative is zero global emissions by 2040)! More problematically, they also like tons of NETs in 2C scenarios where NETs are less essential. https://t.co/M3ACyD4cv7 2/10
There is a lot of confusion about carbon budgets and how quickly emissions need to fall to zero to meet various warming targets. To cut through some of this morass, we can use some very simple emission pathways to explore what various targets would entail. 1/11 pic.twitter.com/Kriedtf0Ec
— Zeke Hausfather (@hausfath) September 24, 2020
In model world the math is simple: very rapid mitigation is expensive today, particularly once you get outside the power sector, and technological advancement may make later NETs cheaper than near-term mitigation after a point. 3/10
This is, of course, problematic if the aim is to ensure that particular targets (such as well-below 2C) are met; betting that a "backstop" technology that does not exist today at any meaningful scale will save the day is a hell of a moral hazard. 4/10
Many models go completely overboard with CCS, seeing a future resurgence of coal and a large part of global primary energy occurring with carbon capture. For example, here is what the MESSAGE SSP2-1.9 scenario shows: 5/10
