Google Quantum

ZKBoost Protocol Unveiled for Private, Verifiable XGBoost AI Model Training Researchers have introduced ZKBoost, a groundbreaking cryptographic protocol designed to verify XGBoost machine learning model training on sensitive datasets without revealing the underlying data or model parameters. ZKBoost is the first zero-knowledge proof of training (zkPoT) protocol specifically developed for XGBoost, a widely-used algorithm for tabular data. This innovation addresses the critical need for cryptographic guarantees of model integrity in high-stakes applications. The system employs a fixed-point implementation of XGBoost compatible with arithmetic circuits, enabling efficient zero-knowledge proofs. Research indicates this implementation maintains accuracy within 1% of the standard XGBoost, making practical verification on real-world data a reality. ...

Qualcomm Challenges Nvidia with New AI Chips for Data Centers Qualcomm is entering the data center market with its next-generation AI inference accelerators, the AI200 and AI250, directly challenging Nvidia’s dominance. These chips are engineered for high-performance generative AI inference, promising a lower total cost of ownership and superior power efficiency. The AI250, set for a 2027 release after the AI200 in 2026, will feature an innovative near-memory computing architecture to dramatically increase memory bandwidth. Designed for compatibility with major machine learning frameworks, this strategic expansion marks Qualcomm’s significant move from mobile technology into enterprise AI hardware. ...