Understanding Ritual: A Decentralized AI Computing Platform with Ultra-Luxury Financing Background, Co-Invested by Balaji

Strong Financing Lineup and Team Background

Notably, Ritual has a strong financing lineup. The participating firm Robot Ventures has a high success rate, with several star projects from each bull market, such as Optimism, Compound, Lido, Eigenlayer, and more. Hypersphere Ventures is also an investor in Worldcoin and Sei Network. Public information also reveals the involvement of notable angel investors, including former Coinbase CTO Balaji Srinivasan.

Ritual's advisory team is also "star-studded," including Illia Polosukhin, co-founder of NEAR Protocol and Transformers ("Attention is All You Need"), and Sreeram Kannan, founder and partner of EigenLayer. On January 10, BitMEX co-founder Arthur Hayes announced that he has joined Ritual as an advisor.

The Ritual team has years of experience in the crypto field. The founders are Niraj Pant and Akilesh Potti. Niraj Pant holds a Bachelor's degree in Computer Science from the University of Illinois at Urbana-Champaign. Before founding Ritual, Niraj was a general partner at Polychain Capital and served as a board member of CoinDCX, a Sequoia Capital ambassador, and co-founder and CTO of Source Networks. Akilesh Potti graduated from Cornell University and was also a partner at Polychain.

Additionally, Anish Agnihotr, a founding member of Ritual and an independent MEV researcher, previously worked as a researcher at Paradigm.

Ritual has not yet issued a token and will open-source its AI workflows and infrastructure in the coming weeks.

What is Ritual?

Ritual

Ritual brings together a network of distributed nodes that can access computing and model creators, enabling all creators to host their models on these nodes. Users can then access any model on the network (whether LLM or classic ML model) using a universal API, and the network has additional cryptographic infrastructure to ensure computational integrity and privacy.

The components of Ritual are as follows:

Ritual Superchain: A set of sovereign modular execution layers, each containing specialized state precompiles (SPC) suitable for various categories of arbitrary computation, primarily focused on AI models. The GMP layer facilitates interoperability between existing blockchains and the Ritual Superchain, which acts as an AI coprocessor for all blockchains. Ritual's AI VM includes not only SPCs but also foundational infrastructure to facilitate optimized execution, including inference engine binaries and vector databases.
Node Set: The Ritual Superchain consists of categories of nodes, each with different functionalities and resource requirements. Ritual nodes include standard full nodes and validator nodes, as well as Ritual-specific nodes (including proof nodes, model cache nodes, and privacy nodes). Ritual proof and privacy nodes can utilize various mechanisms based on the guarantees required by users and the complexity of the AI models, ranging from ZK for proofs to Optimism, and FHE to MPC for privacy.
About State Precompiles (SPCs): State precompiles are precompiles with state access. Ritual requires highly optimized operations capable of efficiently computing specific functions of various AI models. Some SPCs can be implemented as combinations of other SPCs (i.e., fine-tuning and inference). Some SPCs can fully leverage various types of parallelism (i.e., embeddings), while others are constructed sequentially.
General Message Passing (GMP): Ritual allows applications on any chain to leverage the execution capabilities of the superchain through compact bidirectional general message passing.
Portals: Portals are a unique feature of Ritual that allows for urgent data evaluation of the source chain via native smart contracts before leveraging the Ritual superchain. Portals are optimized for static analysis of AI model inputs, localizing computation to the source chain and minimizing data sent over the network.

Infernet

Infernet is the first building block of the protocol and utility suite that Ritual will release. Infernet Node v0.1.0 is a lightweight off-chain client for Infernet service computing workloads.

Infernet allows anyone to seamlessly build on top of Ritual and access Ritual's model and computing provider network without permission. Infernet brings AI into today's on-chain applications by providing a powerful interface for smart contracts to access AI models for inference.

Ritual aims to develop Infernet into a modular execution layer suite that interoperates with other foundational infrastructures in the ecosystem, becoming a key point for AI in the web3 space, allowing every protocol and application on any chain to utilize the Ritual AI coprocessor. Using a given model and functionality, smart contracts can request Infernet to compute some outputs and proofs.

Infernet's workflow can be understood through Frenrug, an interactive experimental instance launched by the Ritual Infernet SDK.

Frenrug is a bot in the friend.tech chat room, where any holder of a Frenrug Key can send messages to the Frenrug chat room. In the message, users can attempt to persuade Frenrug to purchase other users' Keys. The Frenrug agent relays user messages through multiple LLMs running on different Infernet nodes. Initially, all Infernet nodes are run by Ritual, and later, individuals from the community will participate in running the nodes.

Each node will respond on-chain to LLM-generated votes, deciding whether Frenrug should take action. Since LLMs are non-deterministic, each LLM may produce different responses, even if it is the exact same model.

When enough nodes respond, the aggregation request will be fully initiated on-chain. The off-chain Infernet nodes receive this request and aggregate various LLM votes into a single operation through a supervised classifier, forwarding the corresponding validity proof on-chain. Subsequently, the Frenrug agent contract executes this operation (buying keys, selling keys, or no operation), and Frenrug key holders see replies in the Frenrug chat room, which include votes from each LLM agent and the final output.

The "Bidirectional Rush" of AI and Crypto

By integrating the best principles and technologies of cryptography and artificial intelligence, Ritual aims to create a system that allows for the open and permissionless creation, distribution, and improvement of AI models. Ritual seamlessly integrates AI into applications or protocols on any chain, enabling users to fine-tune, monetize, and infer models using cryptographic schemes. Niraj Pant outlined five key focus areas for Ritual: creating an incentive network; connecting distributed computing devices to support hosting, sharing, inference, and fine-tuning; adjusting the API layer for accessing AI models; ensuring a proof layer for computational integrity; and resisting censorship while protecting privacy.

Niraj Pant stated that the current AI tools' chips, computing power, and models are controlled by a few companies, posing a threat to the future development of technology. Several core issues are:

Lack of Strong SLAs: Existing platforms do not provide any guarantees regarding computational integrity (i.e., whether the model is running correctly), privacy (inputs and outputs of the model), and resistance to censorship (limitations on models, applications, and geographical locations);
Licensing and Centralized APIs: Existing infrastructures are hosted by a few centralized companies, limiting developers and users from building native integrations;
High Computing Costs and Limited Hardware Access: It is becoming increasingly difficult for developers to procure AI hardware, with hardware providers charging high commissions;
Oligopoly and Structural Imbalance: Organizations are either incentivized to keep their models closed-source, stifling innovation and concentrating power, or open-source their models because they recognize the lack of appropriate infrastructure to reward their contributions. Additionally, users have little say in the governance and ownership of today's AI.

Innovations in cryptography, game theory, and mechanism design can address these issues. Ritual's goal is to break the dependency on these companies, open access to critical infrastructure, and ensure better AI construction.

Moreover, AI technology can bring new momentum to the crypto space. From foundational infrastructure to applications, AI models can encapsulate complex logic and enable new applications that were previously only possible through smart contracts. For instance, we envision a world where users can generate transactions and interact with contracts using natural language, or agents automatically manage the risk parameters of loan agreements based on real-time market conditions. There are numerous fascinating use cases, but the infrastructure needed to bridge the gap between accessing models and leveraging them on-chain is currently lacking.

Ritual stands at the forefront of this intersection, building a unified solution for the aforementioned issues.

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