Original author: LINDABELL
Original source: chainfeeds
In the past year, with the popularization of the concept of decentralized AI and the widespread application of various AI tools, AI + Web3 has gradually become one of the hottest topics in the crypto community. According to incomplete statistics, there are currently more than 140 projects combining Web3 and AI in the industry, covering multiple directions such as computing, verification, metaverse, and games. Ethereum co-founder Vitalik also wrote an article to discuss the use cases of the combination of blockchain and AI, and pointed out that the cross-domain use cases of the two are increasing, and some use cases have higher significance and robustness. In addition, at the recent "Hong Kong Web3 Carnival" event held in Hong Kong, the topic of combining AI and Web3 was frequently mentioned, whether in the main venue or the side venue.
This article selects three Web3 and AI combination projects that are worth paying attention to, and discusses their unique positioning and development prospects in the field of crypto AI.
Bittensor: Market capitalization leads, but practicality is questioned by the market
In the field of AI, unlike resource-intensive computing power and data, encryption algorithms focus more on technology-intensive work. However, there is a problem in the current AI field, that is, due to the existence of technical barriers, algorithms and models often cannot cooperate effectively, resulting in a zero-sum game situation. In order to change this situation, Bittensor proposed a solution to promote cooperation between different algorithms through blockchain networks and incentive mechanisms, and gradually build an algorithm market for shared knowledge. In short, similar to the Bitcoin mining network, Bittnsor simply replaces the Bitcoin mining calculation process with training and verifying AI models.
From the name, "Bittensor" can be decomposed into two parts: "Bit" and "Tensor". Bit is familiar to us. It can be understood as the smallest currency unit in Bitcoin. In a broader sense of computer science, Bit represents the most basic unit of information. "Tensor" comes from the Latin "Tendera", which originally means "extension". In physics, Tensor refers to a tensor with multiple indices, which is a multidimensional array or matrix that can represent various types of data. In the field of machine learning, Tensor means to represent and process multidimensional data.
The architecture of Bittensor can be divided into two layers. The bottom layer is a blockchain based on Polkadot Substrate, which is responsible for executing the consensus mechanism and incentivizing the network. The AI layer is responsible for reasoning, training, and ensuring input/output compatibility between Bittensor protocol nodes. The Bittensor network has two key participants, miners and validators. Miners submit training models to the network in exchange for token rewards, while validators are responsible for confirming the validity and accuracy of the model output and selecting the most accurate output to return to users. In order to create a positive competition cycle, Bittensor implements incentive distribution through the Yuma consensus mechanism. The Yuma consensus combines the two mechanisms of PoW and PoS, in which miners obtain token rewards by competing for calculation results, while validators need to stake their tokens on a subnet and complete the verification work to obtain a certain amount of TAO incentives. The more accurate and consistent the screening and evaluation of AI models, the more rewards they will receive.
Subnets are a core component of the Bittensor ecosystem. In October 2023, Bittensor introduced the concept of "Subnet" through the Revolution upgrade. Different subnets can be responsible for different tasks, including machine translation, image recognition and generation, language large models, etc., and these subnets can interact and learn from each other. Anyone can create a subnet on Bittensor, but they need to pay the fee in TAO tokens, and the amount of the fee depends on the supply and demand of subnets on the network. In addition, before launching the mainnet of the subnet, you need to run tests locally and on the testnet.
Currently, there is a special subnet 0# Root and 32 other subnets on Bittensor. 0# Root was built by the Opentensor Foundation. As the governance center on Bittensor, it can distribute the produced TAO to other subnets through consensus. On 0# Root, the role of validator comes from the top 64 validators with the largest number of stakes on other subnets, and the role of miner is played by other subnets. In addition, 0# Root can also allocate incentives to other subnets based on the amount of contribution. For the remaining 32 subnets, validators and miners will receive a certain proportion of TAO based on their respective contributions. Usually, 41% will be allocated to validators, 41% to miners, and the remaining 18% to subnet creators. The competition between subnets in the Bittensor ecosystem is very fierce. Currently, the upper limit of the number of subnets allowed by the system is 32, but there are already more than 200 subnets in the testnet waiting to be registered on the mainnet. Recently, some excellent teams have also registered their own subnets on Bittensor, such as MyShell TTS. According to the subnet registration rules, once the upper limit of the number of subnets is reached, the system will automatically cancel the subnet with the lowest token allocation.
Bittensor has also recently been questioned about its registration fees and practicality. It is reported that the current cost of registering a subnet on Bittensor is 2078.49 TAO, and on March 1 it reached 10,281 TAO, equivalent to more than 7 million US dollars. And as the price of TAO rises, the registration fee may increase further. And every time a project registers a subnet, the registration fee will double, and if no one registers, the price will be linearly halved within four days. For developers who want to create or participate in subnets, the high registration fee will undoubtedly become a huge burden. In addition, the practicality of Bittensor subnets has also been questioned. Most of the 32 subnets are low-threshold scenarios such as "data sorting" and "text, image and audio conversion". And among the teams built on Bittensor, no team has more than a dozen full-time members, and most have only 2 to 3 people. Eric Wall, the founder of Bitcoin Ordinals project Taproot Wizards and Bitcoin NFT project Quantum Cats, also expressed his views on social platforms, believing that Bittensor is just a meaningless decentralized experiment and does not provide any practicality. Eric Wall pointed out, "Subnet#1is described as a text prompt service. But in fact, its working mode is very simple. The user sends a prompt and the miner responds, similar to ChatGPT. Miners who participate in this process will receive TAO tokens as rewards. But there is serious redundancy here, because the validator only checks the similarity of the answers. If a miner's answer is different from others, he will not get a reward. The entire system is extremely inefficient and cannot effectively verify whether the model is actually running. In addition, as an ordinary user, it is impossible to interact with the network at all. The only purpose of the entire subnet seems to be internal operation. This process looks like buying useless AI tokens to gain exposure to decentralized AI."
Ritual: With a super luxurious background, ZKP is used for AI model reasoning training
There are many problems in the existing AI stack, including a lack of guarantees for computational integrity, privacy, and censorship resistance. In addition, infrastructure hosted by a few centralized companies also limits the local integration capabilities of developers and users, leading to effectiveness issues. Against this backdrop, the decentralized AI computing platform Ritual came into being.
Ritual's main goal is to provide an open and modular sovereign execution layer for artificial intelligence, that is, how to introduce artificial intelligence into EVM, SVM and other virtual machine environments. Simply put, Ritual connects distributed node network computing resources and model creators, allowing creators to host their AI models, while users can add the full reasoning capabilities of AI models to their existing workflows in a verifiable manner.
The Ritual team has a very strong background. Co-founders Niraj Pant and Akilesh Pott were once general partners of Polychain. In addition, the team members also include senior engineers from well-known companies such as Microsoft AI and Facebook Novi, and professionals from well-known institutions such as Dragonfly, Protocol Labs, and dYdX. In addition, Ritual's advisory lineup is also very impressive, including EigenLayer founder and partner Sreeram Kannan, Gauntlet founder and CEO Tarun Chitra, and BitMEX co-founder Arthur Hayes.
So far, Ritual has completed two rounds of financing. In November 2023, Ritual announced the completion of a $25 million financing, led by Archetype, ccomplice, Robot Ventures, dao5, Accel, Dilectic, Anagram, Avra and Hyperspher and angel investors such as former Coinbase CTO Balaji Srinivasan, Protocol Labs researcher Nicola Greco, Worldcoin research engineer DC Builder, EigenLayer Chief Strategy Officer Calvin Liu, Monad co-founder Keone Hon, and AI+Crypto project Modulus Labs' Daniel Shorr and Ryan Cao participated in the investment. On April 8, 2024, Ritual received another multi-million dollar investment from Polychain Capital, but the specific amount is not yet known.
Currently, Ritual has launched Infernet, a lightweight library that brings computations to the chain, allowing smart contract developers to request computations off-chain through Infernet nodes, and pass computational results to smart contracts on the chain through Infernet SDK. Infernet nodes are lightweight off-chain clients of Infernet, mainly responsible for listening to on-chain or off-chain requests, and delivering workflow outputs and optional proofs through on-chain transactions or off-chain APIs. The Infernet SDK is a set of smart contracts that allows users to subscribe to the output of off-chain computational workloads. One of its main use cases is to bring machine learning reasoning to the chain. Infernet can be deployed on any chain, allowing any protocol and application to be integrated. Infernet also allows developers to introduce their own proof systems, including Halo2 validators and Plonky3 validators.
Infernet does not perform reasoning directly on the chain, but is similar to an oracle system, where requests are made on the chain, and off-chain nodes execute and return the corresponding information to the chain. However, this method also has the problem of asynchronousness, that is, developers need to wait on the block after making a request and cannot get an immediate response. Ritual's method allows developers to perform reasoning operations directly in their familiar environment without worrying about where the operations occur. Although these operations are still performed off-chain, by embedding these computing operations in the virtual machine, each node can perform ultra-optimized artificial intelligence operations while running the modified virtual machine. This method can be regarded as a kind of interactive communication, which is achieved through pre-compilation. The emergence of this method is also the development trend of the blockchain ecosystem.
In terms of specific implementation, through Infernet, developers can delegate computationally intensive operations to the off-chain, consume outputs and optional proofs in smart contracts through on-chain callbacks, and circumvent the limitations of the smart contract execution environment. For example, Emily is developing a new NFT collection that allows minters to add new features to NFTs independently. Emily built a minting website and published the signed delegation to an Infernet node running a custom workflow that can parse user input and generate new images, and the Infernet node sends the final image to her smart contract through on-chain transactions.
At the end of 2023, Ritual released an application Frenrug powered by the Infernet SDK. Frenrug is a chatbot that runs in the Friend.tech chatroom. Any user who holds Frenrug's Key can send a message to Frenrug. For example, you can buy or sell the corresponding friend.tech user's Key through Frenrug, but Frenrug does not process user messages directly. Instead, it sends messages to multiple Infernet nodes, which run different language models. Infernet nodes process user messages and generate votes on the blockchain. When enough nodes vote, the system will aggregate these votes and perform corresponding actions on the blockchain, such as buying or selling Keys. Finally, Frenrug will reply in the chatroom, including the voting results of each node and the final action, so that users can understand how the system handles their requests.
Ritual is currently developing its second product, the "Sovereign Chain Ritual Chain". Although Infernet can be easily integrated into any EVM chain, enabling any protocol to be used. But Ritual still firmly believes that building a chain is necessary because it will build more efficient functions on the core execution layer and consensus layer, and will allow users who want to maximize the value of artificial intelligence for the protocol to realize their vision. Of course, in order to realize the sovereign chain, Ritual needs to build different types of validators, proof systems, and various complex functions, and it needs to be simple enough for users to easily get started.
Virtual: More interesting and focused on user participation
Unlike Bittensor and Ritual, which interact with various machine models, Virtual Protocol is similar to a decentralized factory that focuses on creating AI characters for various virtual worlds. It focuses more on user participation and incorporates human subjective ideas and social consensus into its vision to promote personalization and immersion. The core concept of Virtual Protocol is that future virtual interactions will be realized by artificial intelligence and built in a decentralized way to provide personalized and ultra-immersive experiences. Among them, personalization ensures that each interaction can establish a personal connection with the user, making it uniquely relevant. On the other hand, immersion can stimulate the user's various senses and create a more realistic experience.
Virtual ecosystem participants include contributors and validators. Contributors can provide various text data, voice data, and visual data for models, whether it is the improvement of existing models or the proposal of new models. These contents will be reviewed and certified by validators to ensure accuracy and authenticity, and the quality of their contributions will be evaluated to ensure that they meet the standards set by the Virtual Protocol ecosystem.
New Proposal: Anyone can initiate the creation of Genesis Virtual, but they need to stake at least 100,000 VIRTUAL within a specified three-month period and pass the DAO proposal process. All token holders in the Virtual community can vote on the proposal. Once the proposal is passed, a new Virtual NFT will be minted.
Contribute to existing models: Proposals are automatically generated and reviewed, discussed, verified, and voted on by validators for changes.
Currently, only validators have the right to verify or vote on proposals, and the entire verification process is conducted anonymously. Validators need to interact with each pair of models for at least 10 rounds. After completing the verification task, the validator can receive a staking reward that matches the total staking ratio of his representative. If you want to become a validator, the user must hold 1,000 Virtual tokens in the Virtual account and commit to verifying all proposals. In addition, Virtual uses the DPos mechanism. If you want to get staking rewards without verification, you can choose to entrust any amount of tokens to the Virtual validator. The validator will return the staking reward to the entrusting user after deducting 10% of the income ratio.
The entire participation process of Virtual is transparent and recorded through the public blockchain. All contributions will be converted into NFTs and stored in the Immutable Contribution Library (ICV) to ensure traceability and fair distribution of rewards. The Immutable Contribution Library (ICV) is Virtual's multi-layer on-chain repository, which archives all Virtual-approved contributions on the chain, presents the current status of each Virtual, and tracks its historical evolution. In addition, through the open source VIRTUALs codebase model, ICV creates a transparent environment. It promotes composability, allowing developers and contributors to build on and seamlessly integrate with existing VIRTUALs.
The Virtual token is the core of the Virtual protocol, and its main functions include rewarding contributors and validators, supporting protocol development, and airdropping. The total supply of Virtual tokens is 1 billion, of which 60% are already in public circulation, 5% are reserved for liquidity pools, and the remaining 35% are dedicated to community incentives and initiatives for the development of the Virtual protocol ecosystem. In the next three years, the annual release will not exceed 10%, and deployment will be subject to approval by the management department.
The Virtual protocol achieves flywheel drive through revenue and incentives. Revenue comes from the use of various dApps, and dApps need to pay usage fees to the protocol. At the end of each month, the Virtual protocol will allocate incentives based on the total revenue inflow of dApps, of which 10% is allocated to the protocol, and the remaining 90% is allocated among various Virtual applications according to the staking ratio to ensure that the revenue is proportional to its contribution. For example: the total inflow revenue is $100, of which $10 will be allocated to the protocol. Of the remaining $90, since the Virtual A staking pool has 9,000 tokens, and the Virtual B staking pool has only 1,000 tokens. Then Virtual A will get 90*90%=81 US dollars, and Virtual B will get 90*10%=9 US dollars.
In each Virtual application, the income will be evenly distributed between validators and contributors. Validators will receive income based on running time and staked amount, where running time refers to the ratio of the number of verified proposals to the total amount of proposals. For example, if validator A in Virtual A runs for 90% of the time, he will receive 81/2*90%=36.45 USD. The income will then be further distributed to each staker, and the specific distribution will be based on the amount of the stake. In addition, a default 10% will be paid to the validators of the pool as a delegation fee. Contributors will receive income distribution based on contribution utilization and influence pool. Among them, contribution utilization takes into account the length of time that the contributor's contribution is actively used in the system. Contributors who develop and maintain models will receive 30% of the total distributed income, while users who provide and maintain datasets for model fine-tuning will receive 70% of the total distributed income. In addition, the influence pool awards points based on the importance of the contribution.
Currently, Virtual has been connected to a virtual companion game called AI Waifu. The story of the game takes place in a world called "Arcadia". In the game, as a magician in Arcadia, you need to fight against other magicians and their Waifus. You can choose to have a conversation with your Waifu to deepen the connection, unlock hidden stories, and give gifts to get more rewards. Currently, there are three different Waifu to choose from in the game, each with a unique background story and personality. In addition, the game also introduces a battle mode where you can seduce other Waifus and protect your own Waifu. All expenditures in the game will go into the game's reward pool, and 60% of the WAI transaction fees will also be allocated as part of the reward pool.
Unlike other AI companions and chatbots, AI Waifu is visually presented as a 3D model and can react to sounds and text with emotions and animations. By communicating with AI Waifu, she does not repeat the content style, but constantly learns and gives players personalized responses. In addition, AI Waifu is a cross-platform PWA with a crypto-enabled economic design that allows for co-ownership and returns its spending to developers as a revenue share.
In addition to AI Waifu, Virtual also plans to launch a new AI RPG with cross-game memory and ultimate consciousness. These AI agents can dynamically evolve by interacting with in-game players and other agents. That is, the user can put the agent into game A for training and retain the training memory. Later, when the agent is placed in game B, the memory in game A is still retained. Through continuous learning, AI agents can imitate the behavior of human players and can be dynamically constructed according to player behavior and game environment changes, which can make the user's gaming experience richer and more personalized, even including unpredictability. Users can also upload interaction records to obtain token rewards. In addition, Virtual also plans to launch virtual idols that can be broadcast live on any platform.
Summarize
In the field of crypto AI, Bittensor, Ritual and Virtual Protocol are deeply involved in different fields. Among them, Bittensor is committed to building an algorithm market for shared knowledge, and its market value currently occupies a leading position in the field of crypto AI. However, community members have recently raised some questions about the registration fees and practicality of its subnets. However, whether the problems of a single subnet can be attributed to the defects of the entire network needs to be evaluated. In addition, regarding the problem that the system is heavily dependent on the operation of validators, contributors to the Opentensor Foundation have recently proposed a dynamic TAO solution "BIT001".
With its strong financing lineup and team background, Ritual has become a new player in the encrypted AI track. Previously, Dragonfly partner Haseeb Qureshi said in an article that the cryptoeconomics adopted by Rutial is the simplest and possibly the cheapest in the verifiable inference track, but there are security issues with node collusion. However, Ritual’s co-founder later explained on the social platform that the Ritual platform did not adopt a cryptoeconomics approach based on node cooperation and selective collusion, but provided users with the option to choose the security level according to their preferences.
In contrast, Virtual Protocol is more interesting and focuses on user participation. For example, the protocol launched the AI Waifu virtual companion game and is about to launch the game AI agent. Compared with the established game rules of traditional games, Virtual Protocol is committed to establishing interactive relationships with players and hopes to dynamically evolve according to player behavior and game environment, thereby increasing the social attributes and continuity of the game.
Of course, in addition to the three projects mentioned in this article, there are many Crypto AI projects on the market that are worth paying attention to, such as io.net, which focuses on the GPU rental market, Autonolas, an AI proxy protocol, and MyShell, a Web3-enabled AI platform focused on creators. These projects all demonstrate the diversity and potential of the Crypto AI field, and we will continue to pay close attention to the development of this field.
