Comparing Bitcoin, Ethereum, and Other Cryptos
View the high resolution version of today’s graphic by clicking here.
Unless you’ve been hiding under a rock, you’re probably aware that we’re in the middle of a cryptocurrency explosion. In one year, the value of all currencies increased a staggering 1,466% – and newer coins like Ethereum have even joined Bitcoin in gaining some mainstream acceptance.
And while people like Jamie Dimon of J.P. Morgan and famed value investor Howard Marks have been extremely critical of cryptocurrencies as of late, many other investors are continuing to ride the wave. As we’ve noted in the past, the possible effects of the blockchain cannot be understated, and it could even change the backbone of how financial markets work.
However, even with the excitement and action that comes with the space, a major problem still exists for the layman: it’s really challenging to decipher the differences between cryptocurrencies like Bitcoin, Ethereum, Ethereum Classic, Litecoin, Ripple, and Dash.
For this reason, we worked with social trading network eToro to come up with an infographic that breaks down the major differences between these coins all in one place.
A Description of Major Coins
Here are descriptions of the major cryptocurrencies, which make up 84% of the coin universe.
Bitcoin is the original cryptocurrency, and was released as open-source software in 2009. Using a new distributed ledger known as the blockchain, the Bitcoin protocol allows for users to make peer-to-peer transactions using digital currency while avoiding the “double spending” problem.
No central authority or server verifies transactions, and instead the legitimacy of a payment is determined by the decentralized network itself.
Bottom Line: Bitcoin is the original cryptocurrency with the most liquidity and significant network effects. It also has brand name recognition around the world, with an eight-year track record.
Litecoin was launched in 2011 as an early alternative to Bitcoin. Around this time, increasingly specialized and expensive hardware was needed to mine bitcoins, making it hard for regular people to get in on the action. Litecoin’s algorithm was an attempt to even the playing field so that anyone with a regular computer could take part in the network.
Bottom Line: Other altcoins have taken away some of Litecoin’s market share, but it still has an early mover advantage and some strong network effects.
Ripple is considerably different from Bitcoin. That’s because Ripple is essentially a global settlement network for other currencies such as USD, Bitcoin, EUR, GBP, or any other units of value (i.e. frequent flier miles, commodities).
To make any such a settlement, however, a tiny fee must be paid in XRP (Ripple’s native tokens) – and these are what trade on cryptocurrency markets.
Bottom Line: Ripple runs on many of the same principles of Bitcoin, but for a different purpose: to serve as the middleman for all global FX transactions. If it can successfully capture that market, the potential is high.
Ethereum is an open software platform based on blockchain technology that enables developers to build and deploy decentralized applications.
In the Ethereum blockchain, instead of mining for bitcoin, miners work to earn ether, a type of crypto token that fuels the network. Beyond a tradeable cryptocurrency, ether is also used by application developers to pay for transaction fees and services on the Ethereum network.
Bottom Line: Ethereum serves a different purpose than other cryptocurrencies, but it has quickly grown to displace all but Bitcoin in value. Some experts are so bullish on Ethereum that they even see it becoming the world’s top cryptocurrency in just a short span of time – but only time will tell.
In 2016, the Ethereum community faced a difficult decision: The DAO, a venture capital firm built on top of the Ethereum platform, had $50 million in ether stolen from it through a security vulnerability.
The majority of the Ethereum community decided to help The DAO by “hard forking” the currency, and then changing the blockchain to return the stolen proceeds back to The DAO. The minority thought this idea violated the key foundation of immutability that the blockchain was designed around, and kept the original Ethereum blockchain the way it was. Hence, the “Classic” label.
Bottom Line: As time goes on, Ethereum Classic has been carving out a separate identity from its bigger sibling. With similar capabilities and a different set of principles, Ethereum Classic could still have upside.
Dash is an attempt to improve on Bitcoin in two main areas: speed of transactions, and anonymity. To do this, it has a two-tier architecture with miners and also “masternodes” that help the network perform advanced functions such as near-instant transactions and coin-mixing to provide additional privacy.
Bottom Line: The innovations behind Dash are interesting, and could help to make the coin more consumer-friendly than other alternatives.
Bonus: Bitcoin Cash
Although not included in the graphic, we also wanted to add a quick word on Bitcoin Cash. This new currency “hard forked” from Bitcoin about a month ago, as a result of miner disagreements about the future of Bitcoin. Here’s a detailed summary of the announcement.
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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