A Visual Guide to Profile Picture NFTs
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A Visual Guide to Profile Picture NFTs

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Profile picture NFTs

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A Visual Guide to Profile Picture NFTs

How do you represent yourself on social media? For most people it’s a selfie, a photo with their friends, or a picture of their pet—but what about a digitally-created character?

Profile picture NFTs are pieces of digital artwork that people use to express themselves online. Each item is a depiction of a character’s face, and has a unique mix of attributes that gives it a sense of collectability.

Like other NFTs, they’re secured on a blockchain and can be bought and sold for cryptocurrency. And while there’s nothing to stop you from screenshotting an NFT and using it for your own profile, the market for these items continues to grow.

To learn more, this infographic explains how three well-known profile picture NFT collections were created.

CryptoPunks

CryptoPunks are commonly regarded as one of the first examples of NFTs. The collection consists of 10,000 unique “punks” and was released in 2017 by Larva Labs.

One interesting fact is that these NFTs were originally given out for free—today, they are worth thousands or millions of dollars each. According to OpenSea, one of the largest NFT marketplaces, CryptoPunk #3100 was sold for 4,200 Ethereum (roughly $7.6 million) in March 2021.

A large component of #3100’s perceived value is its blue alien skin, which only eight other punks have. In other words, it’s incredibly rare. The following table shows the species distribution of the CryptoPunks collection.

Species% Rarity
Human98.7%
Zombie0.88%
Ape0.24%
Alien0.09%

In addition to species, each punk features a unique mix of facial accessories or “attributes”. Examples include a big beard (found in only 146 punks), and a VR headset (found in 332 punks).

Bored Ape Yacht Club

Next is the Bored Ape Yacht Club (BAYC), another collection of 10,000 unique profile picture NFTs. Unlike CryptoPunks, BAYC NFTs show both the head and torso of a character (in this case, an ape).

This opens up many combinations of clothing items, facial features, and accessories. Altogether, there are seven categories of attributes: Background color, Clothes, Earring, Eyes, Fur, Hat, and Mouth.

The following table lists some examples of BAYC attributes, and their % rarity. To explore further, visit the BAYC gallery.

Attribute CategoryAttribute Name% Rarity
FurSolid Gold0.05%
FurWhite3.9%
HatKing's Crown0.02%
HatStuntman Helmet1.6%

BAYC NFTs also grant access to members-only benefits. This includes access to a collaborative graffiti board, as well as other NFTs from spin-off collections like the Bored Ape Kennel Club (BAKC). As its name suggests, the BAKC is a collection of dogs, rather than apes.

Cool Cats NFT

The last collection is Cool Cats NFT, which again amounts to 10,000 images. Cool Cats were minted at a cost of 0.06 Ethereum each, or roughly $200. The act of “minting” an NFT is similar to when metal coins are entered into circulation.

Each Cool Cat NFT is a depiction of a cartoon cat with a varying number of facial features, hats, and shirts. Altogether, there are over 300,000 possible options that could be included.

This collection also features nine “hidden” cats which boast one-off features. #500 is an upside down cat floating in a blue sky background, while #2288 is simply a skeleton.

Building Your Identity in the Metaverse

A criticism of today’s social media is that there’s little room to express yourself.

Think back, for a moment, to the days of MySpace. Users could spend hours customizing their profile page, adding music, art, and whatever else they felt was an expression of themselves. As the platform’s name implied, it was a space that belonged to you.

The metaverse offers something similar. To take part in a virtual universe, you need an avatar—a digital manifestation of yourself. Avatars will be highly customizable and far less constrained by the limitations of the real world.

If you’re having trouble imagining this, check out VR Chat, a virtual reality game where players socialize as aliens, monsters, and other “interesting” beings.

This may help to explain the recent craze around profile picture NFTs. When the metaverse arrives, these NFTs could become a user’s avatar. After all, who wouldn’t want to have blue alien skin?

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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.

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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

Disrupting Industries

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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