The AI safety question just got more pressing. Why stop at asking LLMs to write code? The real challenge is demanding they provide verifiable proofs of correctness alongside it. Without formal verification, we're essentially flying blind with deployed AI systems.

Here's what's worth paying attention to: roughly 80% of major language models—including Claude and others—pull training data from Common Crawl. That's a massive data dependency issue nobody talks about enough.

But there's an emerging solution worth watching. Blockchain-based governance platforms designed specifically for AI/ML model security are starting to take shape. Imagine distributed verification layers that can cryptographically ensure model integrity and decision transparency at scale. That's the kind of infrastructure gap the industry needs filled.

The convergence of formal verification, model transparency, and decentralized oversight could actually reshape how we approach AI deployment risk.