Establishing the scientific foundation for safe Compute Intelligence.
A safe transition to a heterogeneous compute future requires the technical ability to learn hardware physics without compromising correctness, continuous constraint enforcement at the kernel level, and system-wide robustness against adversarial workloads.
Here, we summarize our thinking on three priority subproblems we want to help address:
Formal Verification of Kernels
If we are to trust an AI to write the code that runs our most critical infrastructure, we must be certain it is correct. We are developing Formal Verification techniques that mathematically prove the correctness of generated kernels before they ever touch silicon. This ensures that our foundational models never introduce subtle bugs or vulnerabilities into the compute stack.
Runtime Safety (RS1)
Reliability is the bedrock of safety. We have developed the RS1 (Runtime Safety) model, a circuit breaker architecture nested within our Policy Optimization model. RS1 provides continuous constraint enforcement, runtime validation against reference implementations, and automatic escalation on violation, ensuring that our execution policies never exceed safe operational bounds.
Silicon Neutrality & Access
We believe that the concentration of compute power in the hands of a few is a safety risk. By building foundational models that run on Any Chip, we democratize access to high-performance compute. This "Silicon Neutrality" ensures that the future of AI is not dictated by hardware monopolies, but is instead an open, competitive, and resilient ecosystem.
If you have thoughts on our approach, we would be delighted to hear from you at [email protected].