Josh ✓

[image] Ritual sits at the intersection of artificial intelligence and blockchain infrastructure, exploring how machine learning systems might interact with decentralized networks in a more native way. Most AI models today run inside centralized cloud environments. Access to them is

[image] Smart contracts today follow fixed rules. They execute exactly what was written, nothing more. When a task gets heavier running a model, analyzing data, generating output it usually happens outside the chain. A separate service handles it, then sends back a result. That

[image] One of the most interesting aspects of Ritual is how it rethinks where AI models live and how they’re shared. Instead of being confined to private servers, developers could make models available on an open network, where they can be discovered, integrated, and reused across

[image] Blockchains are powerful, but they have always depended on something external to move. A contract waits for a transaction. A protocol waits for input. Nothing truly begins on its own. Ritual’s autonomous research focuses on changing that structure. The goal is to design systems

[image] Infernet is one of the core pieces of the Ritual world. It’s a decentralized oracle network built to connect blockchain applications with meaningful compute tasks especially AI work in a way that doesn’t depend on a single company or centralized service. Unlike simple oracles

[image] Most applications today rely on external systems to handle heavy computation. The blockchain records the transaction, but the actual work happens somewhere else, and the result is returned separately. This creates trust gaps. With Ritual, a contract or application can request

[image] Game economies in Web3 often rely on fixed rules for rewards, item supply, or marketplace pricing. While this approach keeps systems transparent and predictable, it can also make economies slow to respond when player behavior or market demand changes. As games grow more

[image] Ethereum gave developers the ability to build decentralized applications through transparent and trustless smart contracts. However, its deterministic design limits direct access to advanced computation, AI models, or external data without relying on off-chain systems. Ritual

[image] One aspect of Ritual that stands out is its use of cryptographic proofs to support verifiable AI computation. In traditional AI systems, outputs are generated by models running on centralized infrastructure. Applications receive results but usually have no way to independently