BlockBeats News, January 6 — According to official sources, Pundi AI announced a partnership with GAEA, the world’s first verifiable emotional AI network, to jointly explore the integration of decentralized AI data infrastructure and emotional intelligence, promoting the development of AI systems that align more closely with human values. GAEA captures real human emotional signals through its decentralized training network and has launched GAEA Certification™, providing a measurable standard for AI’s emotional capabilities. This vision aligns closely with Pundi AI’s mission to build an open and verifiable AI data ecosystem. The collaboration aims to advance AI agents with emotional perception capabilities and establish new standards for evaluating AI emotional intelligence. Pundi AI and GAEA will jointly explore how to securely label and verify emotional data and apply it to train more empathetic and responsible AI models. By combining verifiable data infrastructure with an emotional AI certification framework, this partnership marks an important step toward developing powerful, humanized, and auditable AI systems.
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Pundi AI teams up with GAEA: Exploring Verifiable Emotional Intelligence AI
BlockBeats News, January 6 — According to official sources, Pundi AI announced a partnership with GAEA, the world’s first verifiable emotional AI network, to jointly explore the integration of decentralized AI data infrastructure and emotional intelligence, promoting the development of AI systems that align more closely with human values. GAEA captures real human emotional signals through its decentralized training network and has launched GAEA Certification™, providing a measurable standard for AI’s emotional capabilities. This vision aligns closely with Pundi AI’s mission to build an open and verifiable AI data ecosystem. The collaboration aims to advance AI agents with emotional perception capabilities and establish new standards for evaluating AI emotional intelligence. Pundi AI and GAEA will jointly explore how to securely label and verify emotional data and apply it to train more empathetic and responsible AI models. By combining verifiable data infrastructure with an emotional AI certification framework, this partnership marks an important step toward developing powerful, humanized, and auditable AI systems.