[Incorporating AI into NFT] Humans.AI: Making Artificial Intelligence “Digital Immortal” in the Web3 Gene Bank

IntermediateDec 17, 2023
This report introduces the HEART project in detail. It analyzes various aspects, from principles and incentive mechanisms to tokens, explores how digital AI has become a reality, involves digital AI's memory and cognitive replication technology, and discusses possible ways and means to store the human AI gene pool.
[Incorporating AI into NFT] Humans.AI: Making Artificial Intelligence “Digital Immortal” in the Web3 Gene Bank

humans.ai is committed to creating an integrated platform for creation and governance based on artificial intelligence. On May 19, humans.ai announced the news that the product will soon be launched on the main website, and has formulated a series of publicity and promotion activities around this. The initial focus of the project was to generate or modify multimedia content such as images, audio, and video using artificial intelligence technology. However, with the passage of time, the ambition of Humans.AI has gradually developed. Its core vision is for AI-type NFTs to eventually become a digital extension of humans, or even replace humans, to achieve digital immortality.

In 2007, the Svalbachin Bank, known as the “granary of doom,” was placed on a small island about 1,000 kilometers from the North Pole. In this heavy gene bank, about 100 million crop seeds from around the world were stored in an underground warehouse at minus 18 degrees Celsius. Illuminated by the Arctic icebergs, the pursuit of immortality and the sense of crisis of the end of life collided in a unique romance in this gene pool.

To a greater or lesser extent, we all believe that accurately reproducing all of our thoughts and memories through digital AI is a potential method of “digital immortality.” However, if it is further implemented into reality, in addition to the memory and cognitive reproduction technology of digital AI, how to store our AI gene pool is also an issue that must be considered — in what way, and through what channels?

What if we use Web3 to build this artificial intelligence gene bank?

Introduction to the Humans.ai project

Since John McCarthy first proposed the concept of “artificial intelligence” in 1956, AI has been ingrained in people's minds, although at the time it was more of an ideal idea. After decades, the application possibilities of AI have been proven time and again, and now it has become one of the most popular technologies. Whether it's AI cloud computing in the past few years or recent AIGC applications such as ChatGPT and Midjourney, the value of AI has been demonstrated.

However, in the new round of AI competition, in addition to tech giants, many participants used small AI models and their databases as core competitiveness, further strengthening the concept of data sovereignty. But we should think: Where should real security place AI models and data? As a result, Humans.ai was born.

Humans.ai is a blockchain-based content platform that focuses on large-scale creation of on-chain AI applications, forming a multi-stakeholder ecosystem. It incorporates a library of AI tools into the creative studio suite, giving users more options when implementing their ideas. Users have the right to create and own their own digital portraits, which can be used by themselves and others to create countless digital assets. Synthetic media, AI applications, and other digital assets can all use blockchain technology to generate NFTs (non-homogenized tokens) that cannot be falsified.

Humans.ai provides users with an AI algorithm model library and training and deployment environment (can be traded). Developers can share their algorithm models on it, and other developers can also make improvements after purchasing. Furthermore, every developer will have a “digital gene” authentication function, and model users need to obtain permission from the author through the “digital gene”.

If we describe it in simpler and easier to understand language, we can understand that humans.ai is an AI model blockchain content platform that can make AI models into NFTs for on-chain storage. Its core feature is the NFT of “genetic” credentials of human identity, such as digital image and sound, to ensure that every request forwarded to the AI NFT is verified as a real person, so that the scope of AI use complies with Humans.ai's ethical standards and a set of rules embedded in AI NFTs by its creators/owners.

How does artificial intelligence NFT work?

Imagine a researcher developing an algorithm that can accept voice input and build a program that converts written text into audio similar to initial voice input — this is the underlying application logic of Humans.AI.

To ensure the security of artificial intelligence networks, Humans.ai uses blockchain and a set of other technologies, such as cryptography and containers. An AI network is encapsulated in a container, a virtual machine-like structure that acts as a way to package an application so that it can run with isolated dependencies and its libraries and algorithms, so the application runs quickly and reliably from one computing environment to another. When the container receives compatible input, it generates an AI model.

AI NFTs center on the user's digital DNA, and biometric data can be anything from sound, face, way of being, gestures, etc. This information is encapsulated in AI NFTs and can be used as a foundation for future AI product development such as synthetic media. For example, we can use multiple AI NFTs to create a talking avatar, a digital avatar that combines sound and face to create a digital character that can be trained to speak in multiple languages.

In addition to the biometric data it stores, the AI NFT also embeds a set of rules governing how to use the information encapsulated in it. In this way, we can prevent users from generating AI products that spread harmful content, such as hate speech, politically incorrect information, or offensive content.

The process of creating AI NFTs within the Humans.ai ecosystem is called minting. Once minted, the AI NFT will have two components:

▪️ A descriptive component — biometric data and a set of governance rules outlined by the creator/owner of the AI NFT, and other data confirming the existence of an NFT in the blockchain

▪️ Computational component — A container structure that encapsulates an AI network. By adopting a new type of zero-knowledge cryptography called Zero-Knowledge Concise Non-Interactive Knowledge Arguments (zk-SNARKS), we are able to ensure that no entity can execute AI components from containers without the AI NFT owner's digital signature.

In order to facilitate users to operate, Humans.ai has also built rich infrastructure around trading markets, application stores, etc. Humans.ai plans to build an “AI Library” — deploying and training algorithms in a ready-made sales environment where users can share their creations and collaborate to improve their models.

Once the model has been published, it will be automatically uploaded to the Motivation Studio. The data and algorithm models are encapsulated as AI entities and service products for commodity trading, and are used by different users after passing the “human credential” verification license. This model means a form of intelligent expression of humans—abstract elements such as language communication ability, speech style, personality traits, etc. can be traded and encapsulated into a single expressive entity.

Human Proof Consensus Mechanism (PoH): The Heart of the AI Ecosystem

When artificial intelligence involves the application layer, the regulation of artificial intelligence systems becomes a problem we all have to face. Although “I, the Robot” and “The Matrix” depict the harm caused by artificial intelligence slightly exaggerated, if AI is allowed to develop freely, it will inevitably become a huge technological crisis.

Precisely based on this underlying logic with ethics as the main reference, Humans.ai introduced the Human Proof Consensus Mechanism (PoH), which places greater emphasis on the ethical supervision of artificial intelligence on the basis of maintaining the fairness of the ecosystem. PoH is a complex and versatile mechanism that ensures the three key functions associated with AI NFTs: governance, consensus, and verification.

People can directly interact with the Humans.ai blockchain and PoH mechanism through various smart interactive devices (smartphones, smartwatches, etc.) through specialized applications. To ensure that the governance of AI NFTs is in line with human ethics, Humans.ai uses human proof to confirm that behind every request made to the AI model, there are digital signatures of multiple real users, such as private keys and biometric data (fingerprints, heartbeats, retinal scans, facial recognition, etc.).

For example, let's say a person named Jungle encapsulates his voice in an AI NFT. To prevent third parties from misusing his voice (which could be a media company or any individual or entity looking to generate content from AI NFTs), Jungle could engrave a set of rules in his AI NFT outlining how to use her biometric data.

For instance, Jungle could stipulate that his AI NFTs cannot be used to produce obscene content, hate speech, or any politically incorrect content. The rules written internally by AI NFTs can always be modified by their owners in case they wish to correct them or want to include additional rules.

Rules embedded in AI NFTs can also specify that only validators with a certain staking token threshold can act as validators for the corresponding AI NFT, or how many validators are required to approve/reject requests. Validators are rewarded with tokens for their work, but if they always approve requests that deviate from the rules set in AI NFTs, they will be sanctioned and lose validator privileges.

Depending on their role, human validators can be divided into two categories:

▪️ Staff: Agents that analyze requests sent to AI NFTs to see if there are any differences from the rules embedded in AI NFTs. Based on their analysis, workers can choose whether the request should be accepted or rejected by a vote.

▪️ Block Producer: After workers vote on the request and agree, the block producer is responsible for actually verifying the request. They are called block producers because after they give final confirmation, they sign requests grouped in blocks, which are added to the blockchain to promote transparency and traceability.

By combining artificial intelligence with blockchain technology, Human.ai empowers people to build and control their own artificial intelligence while ensuring that the development and use of artificial intelligence products created in our ecosystem meets our ethical standards.

$HEART: The core of the humans.ai currency ecosystem

Based on the ecosystem model, the flow of the token system is also required for the entire system to actually work. In Huam.ai, the system uses $HEART as the core currency.

As described in the Humans.ai white paper, the current ecosystem mainly includes three token economy systems:

1. $HEART TOKENS: For governance and payments within the ecosystem 2. NON-FUNGIBLE TOKENS (NFTS): Ownership for algorithms, genomes, data, artificial intelligence, and applications 3. ERC20 TOKENS: represents the governance and revenue rights of each NFT. As the native token of Humans.AI, $HEART tokens enable anyone to participate in the platform's governance process and facilitate the flow of key value within the platform. All fees charged by Human.ai will be paid in $heart, even if the payment originates from fiat currency or other accepted cryptocurrencies.

One of the main functions of $HEART is to facilitate staking. Staking $HEART requires performing key functions in the human ecosystem:

▪️ Minting NFTs

▪️ Account verification and transaction payment

▪️ Create an app

▪️ Adding AI to artificial operating systems

All four types of actors who participate in the platform's contributions are automatically rewarded based on a benefit-sharing algorithm. This idealized profit distribution method aims to secure the rights of data providers. It is a breakthrough in the Web 2.0 data and algorithm monopoly model, and returns data rights and developers' rights to the contributors themselves.

Governance is critical in ecosystems because communities put humans at the forefront of the AI revolution, with the sole goal of aligning AI goals with ours. Governance stems from everything we do, and it will play a central role in our ecosystem.

At this stage, Human.AI has 2 different levels of governance — protocol level and AI NFT level. Protocol-level governance is well-documented and will respect current governance standards and collaboration with communities and large-scale projects such as Terra, Cosmos, Osmosis, etc.

Considering that AI NFTs will generate economic value directly proportional to the utility of NFTs, owners of AI NFT DAO tokens will have a say in the $HEART pool that AI NFTs collect from accepted requests. For example, voice data providers can set limits on what kind of voice-casting requests they can accept (for example, commercial video only), and a human verifier will check every request to comply with these restrictions. However, if data providers choose the DAO style for product governance, the entire community will present a different picture under the rules of decentralization.

Summary

So, as a Web3+AI project with an advanced concept, has Humans.AI succeeded?

At least for now, it seems like they're still moving forward. Although the Humans.AI project is not that perfect, the PoH mechanism is too ideal for quantitative ratings of human ethics, and packaging AI in the form of NFT still hampers technical operation, and even driven by AI itself. According to the current stage of development, it is not enough to achieve the effect of a “digital twin” according to the current stage of development.

But none of this matters. Humans.ai's biggest significance is not the project itself, but in telling us about this group of explorers:

When humans want to achieve digital immortality, Web3 will be the key to perpetuating the mindset.

It's enough.

Statement:

  1. This article was reprinted from [ Go2Mars Research], and the copyright belongs to the original author [Go2Mars Research ]. If you have any objections to the reprint, please contact the Gate Learn team, and the team will deal with it as soon as possible according to the relevant procedures.
  2. Disclaimer: The views and opinions expressed in this article only represent the author's personal opinions and do not constitute any investment advice.
  3. Articles in other languages are translated by the Gate Learn team, and translated articles may not be copied, distributed, or copied without mentioning Gate.io.
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