Mapping the Major Bitcoin Forks
The emergence of Bitcoin took the world by storm through its simplicity and innovation. Yet, plenty of confusion remains around the term itself.
The Bitcoin blockchain—not to be confused with the bitcoin cryptocurrency—involves a vast global network of computers operating on the same distributed database to process massive volumes of data every second.
These transactions tell the network how to alter this distributed database in real-time, which makes it crucial for everyone to agree on how these changes should be applied. When the community can’t come to a mutual agreement on what changes, or when such rule changes should take effect, it results in a blockchain fork.
Today’s unique subway-style map by Bitcoin Magazine shows the dramatic and major forks that have occurred for Bitcoin. But what exactly is a Blockchain fork?
Types of Blockchain Forks
Forks are common practice in the software industry and happen for one of two reasons:
- Split consensus within the community
These forks are generally disregarded by the community because they are temporary, except in extreme cases. The longer of the two chains is used to continue building the blockchain.
- Changes to the underlying rules of the blockchain
A permanent fork which requires an upgrade to the current software in order to continue participating in the network.
There are four major types of forks that can occur:
1. Soft Forks
Soft forks are like gradual software upgrades—bug fixes, security checks, and new features—for those that upgrade right away.
These forks are “backwards compatible” with the older software; users who haven’t upgraded still have access to the network but may not be able to use all functionality in the current version.
2. Hard Forks
Hard forks are like a new OS release—upgrading is mandatory to continue using the software. Because of this, hard forks aren’t compatible with older versions of the network.
Hard forks are a permanent division of the blockchain. As long as enough people support both chains, however, they will both continue to exist.
The three types of hard forks are:
Scheduled upgrades to the network, giving users a chance to prepare. These forks typically involve abandoning the old chain.
Caused by disagreements in the community, forming a new chain. This usually involves major changes to the code.
- Spin-off Coins
Changes to Bitcoin’s code that create new coins. Litecoin is an example of this—key changes included reducing mining time from 10 minutes to 2.5 minutes, and increasing the coin supply from 21 million to 84 million.
3. Codebase Forks
Codebase forks copy the Bitcoin code, allowing developers to make minor tweaks without having to develop the entire blockchain code from scratch. Codebase forks can create a new cryptocurrency or cause unintentional blockchain forks.
4. Blockchain Forks
Blockchain forks involve branching or splitting a blockchain’s whole transaction history. Outcomes range from “orphan” blocks to new cryptocurrencies.
Splitting off the Bitcoin network to form a new currency is much like a religious schism—while most of the characteristics and history are preserved, a fork causes the new network to develop a distinct identity.
Summarizing Major Bitcoin Forks
Descriptions of major forks that have occurred in the Bitcoin blockchain:
- Bitcoin / Bitcoin Core
The first iteration of Bitcoin was launched by Satoshi Nakamoto in 2009. Future generations of Bitcoin (aka Bitcoin 0.1.0) were renamed Bitcoin Core, or Bitcore, as other blockchains and codebases formed.
A codebase fork of Bitcoin. Developers released a hard fork protocol called Segwit2x, with the intention of having all Bitcoin users eventually migrate to the Segwit2x protocol. However, it failed to gain traction and is now considered defunct.
- Bitcoin ABC
Also a codebase fork of Bitcoin, Bitcoin ABC was intentionally designed to be incompatible with all Bitcoin iterations at some point. ABC branched off to form Bitcoin Cash in 2017.
- Bitcoin Gold, Bitcoin Diamond, Other Fork Coins
After the successful yet contentious launch of Bitcoin Cash, other fork coins began to emerge. Unlike the disagreement surrounding Bitcoin Cash, most were simply regarded as a way to create new coins.
Some of the above forks were largely driven by ideology (BTC1), some because of mixed consensus on which direction to take a hard fork (Bitcoin ABC), while others were mainly profit-driven (Bitcoin Clashic)—or a mix of all three.
Where’s the Next Fork in the Road?
Forks are considered an inevitability in the blockchain community. Many believe that forks help ensure that everyone involved—developers, miners, and investors—all have a say when disagreements occur.
Bitcoin has seen its fair share of ups and downs. Crypto investors should be aware that Bitcoin, as both a protocol and a currency, is complex and always evolving. Even among experts, there is disagreement on what constitutes a soft or hard fork, and how certain geopolitical events have played a role in Bitcoin’s evolution.
Infographic: Generative AI Explained by AI
What exactly is generative AI and how does it work? This infographic, created using generative AI tools such as Midjourney and ChatGPT, explains it all.
Generative AI Explained by AI
After years of research, it appears that artificial intelligence (AI) is reaching a sort of tipping point, capturing the imaginations of everyone from students saving time on their essay writing to leaders at the world’s largest tech companies. Excitement is building around the possibilities that AI tools unlock, but what exactly these tools are capable of and how they work is still not widely understood.
We could write about this in detail, but given how advanced tools like ChatGPT have become, it only seems right to see what generative AI has to say about itself.
Everything in the infographic above – from illustrations and icons to the text descriptions—was created using generative AI tools such as Midjourney. Everything that follows in this article was generated using ChatGPT based on specific prompts.
Without further ado, generative AI as explained by generative AI.
Generative AI: An Introduction
Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI creates new content in the form of images, text, audio, and more.
Generative AI uses a type of deep learning called generative adversarial networks (GANs) to create new content. A GAN consists of two neural networks: a generator that creates new data and a discriminator that evaluates the data. The generator and discriminator work together, with the generator improving its outputs based on the feedback it receives from the discriminator until it generates content that is indistinguishable from real data.
Generative AI has a wide range of applications, including:
- Images: Generative AI can create new images based on existing ones, such as creating a new portrait based on a person’s face or a new landscape based on existing scenery
- Text: Generative AI can be used to write news articles, poetry, and even scripts. It can also be used to translate text from one language to another
- Audio: Generative AI can generate new music tracks, sound effects, and even voice acting
People have concerns that generative AI and automation will lead to job displacement and unemployment, as machines become capable of performing tasks that were previously done by humans. They worry that the increasing use of AI will lead to a shrinking job market, particularly in industries such as manufacturing, customer service, and data entry.
Generative AI has the potential to disrupt several industries, including:
- Advertising: Generative AI can create new advertisements based on existing ones, making it easier for companies to reach new audiences
- Art and Design: Generative AI can help artists and designers create new works by generating new ideas and concepts
- Entertainment: Generative AI can create new video games, movies, and TV shows, making it easier for content creators to reach new audiences
Overall, while there are valid concerns about the impact of AI on the job market, there are also many potential benefits that could positively impact workers and the economy.
In the short term, generative AI tools can have positive impacts on the job market as well. For example, AI can automate repetitive and time-consuming tasks, and help humans make faster and more informed decisions by processing and analyzing large amounts of data. AI tools can free up time for humans to focus on more creative and value-adding work.
How This Article Was Created
This article was created using a language model AI trained by OpenAI. The AI was trained on a large dataset of text and was able to generate a new article based on the prompt given. In simple terms, the AI was fed information about what to write about and then generated the article based on that information.
In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future.
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