The post XRP Ledger Becomes Testing Ground for Next-Gen AI Integration appeared on BitcoinEthereumNews.com. AltcoinsBlockchain Ripple’s University Blockchain Research Initiative (UBRI) is reshaping how artificial intelligence interacts with blockchain. In collaboration with Nanyang Technological University (NTU), the project is developing an AI framework that runs directly on the XRP Ledger (XRPL), making it a foundation for autonomous and verifiable machine agents. From Research to On-Chain Reality Led by Professor Yang Liu, NTU’s team began with cybersecurity experiments aimed at detecting code flaws using large language models. When those models failed to recognize subtle vulnerabilities, the researchers turned to agentic AI – systems designed to think like human analysts. The breakthrough came when they connected these AI agents to XRPL’s infrastructure, allowing them to execute tasks and settle results transparently on-chain. Ripple’s UBRI host Lauren Weymouth said the integration represents “academic innovation turned production-grade,” emphasizing how AI can now exist as part of the ledger rather than a separate off-chain service. Transparency and Utility Running AI directly on XRPL brings a unique benefit: traceability. Every decision, payment, or analysis performed by these agents is logged on-chain, offering complete accountability. “The XRP Ledger gives AI a built-in trust layer,” Liu explained, noting that it also allows agents to access payment systems seamlessly. Ripple’s vision is broader than security audits. The same framework could power smart financial tools, IoT coordination, or liquidity management – all handled by self-operating agents that use XRP for settlement. Managing AI Risks Liu also warned that autonomous systems can behave unpredictably when tied to real-world value. His team is designing guardrails to prevent agents from taking unintended actions, combining security measures to block hacks with safety protocols to keep behavior aligned with human intent. The next research phase focuses on giving agents “memory” and reasoning skills, enabling them to learn from past transactions and adapt to changing conditions. Liu said these features… The post XRP Ledger Becomes Testing Ground for Next-Gen AI Integration appeared on BitcoinEthereumNews.com. AltcoinsBlockchain Ripple’s University Blockchain Research Initiative (UBRI) is reshaping how artificial intelligence interacts with blockchain. In collaboration with Nanyang Technological University (NTU), the project is developing an AI framework that runs directly on the XRP Ledger (XRPL), making it a foundation for autonomous and verifiable machine agents. From Research to On-Chain Reality Led by Professor Yang Liu, NTU’s team began with cybersecurity experiments aimed at detecting code flaws using large language models. When those models failed to recognize subtle vulnerabilities, the researchers turned to agentic AI – systems designed to think like human analysts. The breakthrough came when they connected these AI agents to XRPL’s infrastructure, allowing them to execute tasks and settle results transparently on-chain. Ripple’s UBRI host Lauren Weymouth said the integration represents “academic innovation turned production-grade,” emphasizing how AI can now exist as part of the ledger rather than a separate off-chain service. Transparency and Utility Running AI directly on XRPL brings a unique benefit: traceability. Every decision, payment, or analysis performed by these agents is logged on-chain, offering complete accountability. “The XRP Ledger gives AI a built-in trust layer,” Liu explained, noting that it also allows agents to access payment systems seamlessly. Ripple’s vision is broader than security audits. The same framework could power smart financial tools, IoT coordination, or liquidity management – all handled by self-operating agents that use XRP for settlement. Managing AI Risks Liu also warned that autonomous systems can behave unpredictably when tied to real-world value. His team is designing guardrails to prevent agents from taking unintended actions, combining security measures to block hacks with safety protocols to keep behavior aligned with human intent. The next research phase focuses on giving agents “memory” and reasoning skills, enabling them to learn from past transactions and adapt to changing conditions. Liu said these features…