Tiancheng Xie, co-founder of Polyhedra, emphasizes zkML's role in addressing AI accountability, as highlighted in a TechRadar article on April 25, 2025.

zkML uses zero-knowledge proofs to verify AI outputs without revealing sensitive data, ensuring privacy and integrity in AI processes.

The article notes a growing skepticism toward AI reliability, with surveys showing increased user concern, underscoring the need for verifiability.

Polyhedra's EXPchain Layer 1 platform, launched by December 2024, supports zkML to tackle AI safety and data privacy challenges.

A 2025 TechRadar report on AI trends highlights the increasing autonomy of AI systems, aligning with the need for trust mechanisms like zkML.

An arXiv paper from February 2024 discusses zkML's potential to enhance fairness in generative AI, especially in fields like medicine and law.

Tiancheng Xie, co-founder of Polyhedra, emphasizes zkML's role in addressing AI accountability, as highlighted in a TechRadar article on April 25, 2025.

zkML uses zero-knowledge proofs to verify AI outputs without revealing sensitive data, ensuring privacy and integrity in AI processes.

The article notes a growing skepticism toward AI reliability, with surveys showing increased user concern, underscoring the need for verifiability.

Polyhedra's EXPchain Layer 1 platform, launched by December 2024, supports zkML to tackle AI safety and data privacy challenges.

A 2025 TechRadar report on AI trends highlights the increasing autonomy of AI systems, aligning with the need for trust mechanisms like zkML.

An arXiv paper from February 2024 discusses zkML's potential to enhance fairness in generative AI, especially in fields like medicine and law.

https://www.techradar.com/pro/why-ai-needs-zkml-the-missing-puzzle-piece-to-ai-accountability