Niraj Pant, one of the co-founders of Ritual, recently sat down for an exclusive interview with Cryptonews to discuss the future of crypto and AI, decentralized AI, and the application of machine learning (ML) to decentralized finance (DeFi).
Pant believes that the collaboration between blockchain and AI has been delayed due to several challenges. However, he believes that blockchain technology is now reaching a point where it can effectively support AI applications. He highlights the recent advancements in machine learning architecture, such as the development of the transformer architecture and the creation of ChatGPT and GPT-3, as a catalyst for the growth of AI within the crypto space.
According to Pant, the relationship between crypto and AI is mutually beneficial. While AI is highly centralized, the crypto world values decentralization and transparency. Pant sees the potential for a decentralized alternative to AI that offers privacy, computational integrity, and governance rights to its users. On the other hand, AI can also benefit from crypto by enabling various use cases, such as NFT generation, customized games, and personalized movies.
Pant emphasizes the lack of AI-enabled decentralized applications (dapps) in the crypto space. He sees this as a massive opportunity for growth and explains that Ritual aims to enable developers to easily integrate AI into their smart contracts. The team has built Ritual in two phases: the first phase is Infernet, a decentralized oracle network that allows smart contract developers to request off-chain computation, and the second phase is Ritual Chain, a Layer-1 chain that supports AI-native operations.
The interview also touches on the GPU conundrum in AI development. Pant acknowledges that GPUs are essential for AI tasks but can be prohibitively expensive and time-consuming to acquire. He believes that the crypto market can revolutionize the GPU-as-a-service industry by expanding the range of hardware suppliers and providing a more efficient marketplace for buyers and sellers.
Furthermore, Pant discusses the application of ML to make DeFi more efficient. He highlights the challenges of governance in decentralized organizations and suggests that AI and ML can play a role in managing certain aspects of DeFi protocols. For example, ML models can help determine interest rates, liquidation factors, and collateral factors based on data from different protocols and price feeds.
In conclusion, Pant expresses his excitement about the future of crypto and AI. He believes that combining the infinite abundance of AI with the ownership and self-sovereignty properties of crypto will lead to a new era of innovation. He also mentions upcoming developments from Ritual, including Infernet ML, a toolkit that provides pre-built ML workflows for various use cases in the crypto space.
