KGeN Reveals KAI Details…Taking on AI Training Issues

Global verification distribution protocol company KGeN said on the 31st that it disclosed details of the infrastructure layer KAI it is developing.

KAI is a project to solve the shortage of 'human-verified data' for advanced AI models such as frontier models and enterprise AI. KGeN said, "KAI is designed to address challenges repeatedly raised in the AI development process such as data bias (Bias), traceability (Traceability), and scalability (Scalability)."

KAI's distinction lies in its learning method. First, KAI collects data based on KGeN's global network that has completed on-chain identity verification. Therefore, it can collect data spanning broad communities and specialized domains. The company says this minimizes the data bias problem.

Regarding traceability, KAI applies KGeN's reputation system 'POGE' to the data it trains on to verify the source and credibility of all data contributors. The strategy is to thereby secure transparency across AI training data.

In addition, KAI provides scalability to flexibly respond to large-scale data demand and focuses on reducing the burden on companies and developers through a lower cost structure compared to existing approaches.

Ishank Gupta, KGeN co-founder, said, "The future of AI depends on the quality of data," adding, "Verified human data is especially key." He added, "KAI will grow into a core infrastructure that links the potential of the global community to AI training infrastructure."

Meanwhile, KGeN has formed strategic partnerships with Poseidon, Remix, Navigate AI, Segmind, Morphic, Render, Mira, Sapien, and Sentient to expand the KAI ecosystem.