Our research spans two fundamental areas that are critical to a future where AI proliferates and permeates every aspect of our lives.
The study of models as complex information systems. We investigate how AI models encode, process, and transform information, developing frameworks to understand their internal representations, behaviors, and capabilities. This includes analyzing model architectures, training dynamics, and emergent properties to create comprehensive profiles of AI systems.
The development of techniques to programmatically verify execution of complex systems. We create cryptographic and algorithmic methods that enable automated verification of AI model behaviors, capabilities, and integrity without requiring access to internal parameters or training data.
Our research in Model Informatics and Verifiable Computation has led to the development of breakthrough technologies that enable trustworthy and verifiable AI deployments. These technologies form the foundation of our products and services, providing practical solutions for real-world AI verification challenges.
Learn more about our core technologies, including Behavioral Fingerprinting for AI model identification and ZkTorch for zero-knowledge verification of large language models.
Exploring methods and frameworks for identifying AI systems developed by foreign adversaries and implementing appropriate policy responses.
White PaperIntroducing ZKTorch, the first universal zero-knowledge machine learning compiler designed for real-world AI applications.
White Paper | code
A comprehensive white paper exploring the critical importance of AI model verification, behavioral fingerprinting, and establishing trust in AI systems for enterprise deployment.
White PaperExploring the relationship between AI agents, computational requirements, and task complexity in modern AI systems.
SubstackAnalyzing the computational requirements and challenges of stochastic systems in AI applications.
SubstackDrawing parallels between AI adoption and sugar consumption to understand societal impacts and dependencies.
SubstackExamining the critical differences between transparency and interpretability in AI systems and their implications.
SubstackAddressing the challenge of model identification and verification in an era of proliferating AI systems.
SubstackStay updated with the latest research, insights, and thought leadership on AI and model informatics.
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