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Home»NFT»AI filters possibly made NFT collections obsolete
NFT

AI filters possibly made NFT collections obsolete

NBTCBy NBTC27/03/2025No Comments4 Mins Read
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Breakthroughs in AI rendering may have contributed to making NFT collections obsolete. AI’s ability to impose any art style on images means collections are no longer a scarce commodity.

NFTs were already fighting for survival before they were dealt another blow after AI grew its capabilities of image rendering into multiple styles. Previously, collections relied on the scarcity of their style and a complex system of traits and characteristics to justify their high valuations.

NFT collections must now adapt to the new wave of image creation to have any chance at relevance.

AI filters can now render and extend collections to infinite custom images, which can even be re-minted as new NFTs if needed. The appeal of NFT-style avatars as belonging to a community may even be under threat.

Influencers are already noticing AI’s abilities in producing new avatars. The ability to copy the style of NFT collections can either kill them or give them a new path to recovering their popularity.

#NFTs are done!

Dropped my pic into some of the top NFTs, and honestly, the results say more about the space than any chart could! 🧵👇

— Ali (@ali_charts) March 27, 2025

In the past years, NFT collections have used some forms of automated generation or AI art. This time, the new filters and styles also enjoy social media popularity.

The launch of AI filters rendering multiple styles has already given a boost to meme tokens. A new wave of launches for remastered old memes created a wave of Pump.fun tokens. For the NFT space, the ability to create limitless images and extend collections may bring down value even further.

NFTs have one possible saving grace – the presence of true believer communities, as well as preferential access and airdrops. NFT artists and creators, however, may see themselves displaced by AI. Previously, NFT artists were tasked with creating the images for all trait variations in the same style for a fixed number of items.

NFT collections remaster their art

The addition of Studio Ghibli style to ChatGPT led to an explosion of images remastered in that style.

Collections are now relaunching in that style, as in the case of Ghiblady Maker, generated off the Milady Maker collection. The collection had an asking price of over $10K for its top NFT on OpenSea.

Milady Maker retained a floor price of 3.24 ETH, and has not benefitted from the growing attention. The Milady collection got a recent boost after the Ethereum community used the NFT as their avatars. Despite this, the floor price has fallen by 60% recently, as the community lost its attraction.

The Milady Maker collection retains a relatively high floor price, becoming one of the collections to be remastered in the Studio Ghibli style. | Source: NFT Price Floor

Other collections like Mad Lads are having even more fun with their avatars, by producing a Studio Ghibli version. Mad Lads remains one of the top 10 NFT collections still commanding a high floor price.

Even Bored Apes got the Studio Ghibli treatment, though just as a test. The new trend has not created many new collections, as demand for NFT remains more limited due to the relatively high floor prices.

NFTs have slowed down in the past year, with a total valuation of $1.6B. This is lower than some of the leading meme tokens, as the NFT market remains much slower. Despite this, individual NFTs are selling at prices as high as 135 ETH, with one Punk selling for 420 ETH in the past week. Collections also retain their leading positions, with liquidity still seeking out Pudgy Penguins and Crypto Punks.

There is no mass interest in NFTs as most of the activity comes from insider communities, with additional sales, mini-collections and airdrops. Older collections are often revived with accompanying floor price rallies. The NFT space remains split between low-cost items used for fun, and the remaining blue-chip collections, which strive to retain value.

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