Lean4 powers AI advisers to pair hypotheses with physics‑consistent proofs

Or, an AI scientific adviser that outputs a hypothesis alongside a Lean4 proof of consistency with known physics laws. The pattern is the same - Lean4 acts as a rigorous safety net, filtering out incorrect or unverified results. As one AI researcher from Safe put it, "the gold standard for supporting a claim is to provide a proof," and now AI can attempt exactly that.

Building secure and reliable systems with Lean4 Lean4's value isn't confined to pure reasoning tasks; it's also poised to revolutionize software security and reliability in the age of AI. Bugs and vulnerabilities in software are essentially small logic errors that slip through human testing. What if AI-assisted programming could eliminate those by using Lean4 to verify code correctness?

In formal methods circles, it's well known that provably correct code can "eliminate entire classes of vulnerabilities [and] mitigate critical system failures." Lean4 enables writing programs with proofs of properties like "this code never crashes or exposes data." However, historically, writing such verified code has been labor-intensive and required specialized expertise. Now, with LLMs, there's an opportunity to automate and scale this process. Researchers have begun creating benchmarks like VeriBench to push LLMs to generate Lean4-verified programs from ordinary code.

Early results show today's models are not yet up to the task for arbitrary software - in one evaluation, a state-of-the-art model could fully verify only ~12% of given programming challenges in Lean4.