The coming convergence of NFTs and artificial intelligence
NOTOn-fungible tokens (NFTs) are emerging as one of the most important trends in the crypto ecosystem. The first generation of NFT focused on key properties such as ownership representation, transfer, automation as well as building the basic elements of the NFT market infrastructure.
The hype in the NFT market makes it relatively difficult to distinguish between signal and noise when even the most simplistic form of NFT is able to capture incredible value. But, as the space evolves, the value proposition of NFTs is expected to shift from static images or text to more dynamic and intelligent collectibles. Artificial intelligence (AI) is likely to have an impact in the next wave of NFT.
Jesus Rodriguez is the CEO of IntoTheBlock, a market intelligence platform for crypto assets. He has held executive positions in large technology companies and hedge funds. He is an active investor, lecturer, author and guest lecturer at Columbia University in New York.
We are already seeing manifestations of NFT-AI convergence in the form of generative art. However, the potential is much greater. Injecting AI capabilities into the life cycle of NFTs opens the door to forms of smart property that we have never seen before.
Today, NFTs remain primarily digital manifestations of the word offline in areas such as art or collectibles. Although compelling, this view is quite limited. A more intriguing way to think of NFTs is as digital property primitives. Property representations have much broader applications than collectibles. While in the physical world, property is mostly represented as static records, in the digital chained world, property can be programmable, composable, and of course, intelligent.
With smart digital property, the possibilities are endless. Let’s illustrate this in the context of collectibles which remains one of the most well-known applications of NFTs.
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Imagine digital art NFTs that could converse in natural language by answering questions to explain the inspiration behind their creation and tailor those responses to a specific conversational context. We might also consider NFTs that could adapt to your feelings, mood, and provide a consistently fulfilling experience. What about smart NFT wallets that when interacting with a website could decide what property rights to showcase in order to improve a given user’s experience?
Echoing the famous quote from William Gibson: “The future is already here, it’s just not very evenly distributed”, we should view the intersection of smart digital property as something that is possible with today’s AI and NFT technologies. NFTs are likely to evolve as a digital property primitive and intelligence should definitely be one of them.
IA and NFT
To understand how intelligent NFTs can be enabled with today’s technologies, we need to understand which AI disciplines have points of intersection with the current generation of NFT. The digital representation of NFTs relies on digital formats such as images, video, text or audio. These representations correspond brilliantly to the various sub-disciplines of AI.
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Deep learning is the field of AI that relies on deep neural networks as a way to generalize knowledge from datasets. While the ideas behind deep learning have been around since the 1970s, they have exploded over the past decade with a number of frameworks and platforms that have catalyzed its mainstream adoption. Some key areas of deep learning can be incredibly influential in activating intelligence capabilities in NFTs:
Computer Vision: Today’s NFTs are primarily concerned with images and video and, therefore, are ideally suited to take advantage of advances in computer vision. In recent years, techniques such as convolutional neural networks (CNN), generative antagonist neural networks (GANs) and, more recently, transformers have pushed the boundaries of computer vision. Image generation, object recognition, scene understanding are some of the computer vision techniques that can be applied in the next wave of NFT technologies. Generative art seems to be a clear area for combining computer vision and NFT.
Understanding of natural language: language is a fundamental form for expressing cognition, and this includes forms of property. Understanding natural language (NLU) has been at the center of some of the most important deep learning breakthroughs over the past decade. Techniques such as transformers powering models such as the GPT-3 have reached new milestones in NLU. Areas such as answering questions, summarizing, and analyzing sentiment could be relevant to new forms of TVN. The idea of overlaying language comprehension on existing forms of NFT seems to be a trivial mechanism to enrich interactivity and user experience in NFTs.
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Speech recognition: Speech intelligence can be considered as the third area of deep learning that can have an immediate impact on NFTs. Techniques such as CNNs and Recurrent Neural Networks (RNNs) have advanced the speech intelligence space in recent years. Capabilities like speech recognition or tone analysis could fuel interesting forms of NFT. Unsurprisingly, audio-NFTs seem to be the perfect scenario for voice intelligence methods.
Three key categories at the intersection of AI and NFT
Advances in language, vision and speech intelligence are expanding the horizon of NFTs. The value unlocked at the intersection of AI and NFT will impact not one but several dimensions of the NFT ecosystem. In today’s NFT ecosystem, there are three fundamental categories that can be immediately redesigned by incorporating AI capabilities:
AI-generated NFTs: This seems to be the most obvious dimension of the NFT ecosystem to benefit from recent advancements in AI technologies. Leveraging deep learning methods in areas such as computer vision, language and speech can enrich the experience of the creators of NFT to levels never seen before. Today, we can see manifestations of this trend in fields such as generative art, but they remain relatively constrained both in terms of the AI methods used and the use cases they tackle.
In the near future, we should see the value of AI-generated NFTs to expand beyond generative art into more generic NFT utility categories providing a natural vehicle to take advantage of the latest techniques. deep learning. An example of this value proposition can be seen in digital artists like Refik Anadol who are already experimenting with cutting edge deep learning methods for creating NFT. Anadol’s studio has been a pioneer in the use of techniques such as GANs, and even in quantum computing, has trained models in hundreds of millions of images and audio clips to create stunning visuals. NFTs have been one of the recent delivery mechanisms explored by Anadol.
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Integrated NFTs AI: We can use AI to generate NFTs, but that doesn’t mean they’ll be smart. But what if they could? Native integration of AI capabilities into NFT is another dimension of the market that can be unlocked by the intersection of these two fascinating technology trends. Imagine NFTs that integrate language and speech capabilities to establish a dialogue with users, answer questions about its meaning, or interact with a specific environment. Platforms such as Alethea AI or Fetch.ai are starting to surface here.
AI-Driven NFT Infrastructures: The value of deep learning methods for NFTs will not only be reflected at the individual NFT level, but throughout the ecosystem. Incorporating AI capabilities into building blocks such as NFT marketplaces, oracles, or NFT data platforms can lay the groundwork for enabling intelligence progressively throughout the NFT lifecycle. Imagine NFT data APIs or oracles that provide smart metrics pulled from on-chain datasets or NFT markets that use computer vision methods to make intelligent recommendations to users. Data and intelligence APIs will become an important component of the NFT market.
AI is changing the landscape of all software and NFTs are no exception. By incorporating NFT capabilities, NFTs can evolve from basic property primitives to smart, scalable forms, or a property that enables richer digital experiences and greater utility to NFT creators and consumers. The era of intelligent NFTs does not require any futuristic technical breakthrough. Recent advances in computer vision, natural language understanding or speech analysis, combined with the flexibility of NFT technologies, already offered a formidable landscape of experimentation to bring intelligence to the ecosystem. NFT.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.