AI 🤝 NFTs? Though already connected through generated art, AI may end up playing a far more significant role in our interactions with NFTs. Here’s how 👇
that hold unique metadata and identifiers that make them uniquely distinguishable from any other digital asset. They’re used to prove ownership and authenticity for both digital and real-world objects. NFTs have revolutionized one industry after another since their meteoric rise to popularity in 2020. Massive leaps forward in the
One design of an AI NFT is a tokenized asset with a Generative Pre-trained Transformer 3 AI model coded into its. A GPT-3 is a language model based on deep learning and is used to produce human-like text. On top of being able to interact with people via user inputs, AI NFTs can come with other properties like animation. This makes them more dynamic compared to more “traditional” NFTs that often take the form of an image or audio file.
AI NFTs, on the other hand, can create new content on their own and produce dynamic experiences thanks to their learning abilities. The more these digital assets are exposed to a specific environment or user, the more data they can pull and generate.AI NFTs can leverage deep learning methods such as computer vision, speech recognition, and natural language processing to make your tokenized asset more dynamic and interactive.
In the generative art space, AI models study a large database of human-created artwork and learn how to produce original art. This is particularly useful for project teams or creators who want to issue large sets of NFT collections but would like to avoid the trouble of creating each piece by hand.
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