Today on AI:AM — “AI Security and Real-Time Content Safety.”
We open on Trump’s AI executive order — the polite 30-day model-review ask, classified benchmarks, and the state-vs-federal scramble where JB Pritzker has become the leading anti-AI candidate. Plus why the frontier labs seem calmer about regulation, and why the EO might actually trigger a security-review slowdown.
Tal Hoffman & Yanir Tsarimi (EnclaveAI) on finding the bugs that actually matter — how they reproduced an Anthropic Mythos-class finding with a model ~100x smaller, why proven exploitability is the real bottleneck, how AI-generated bug reports broke the bounty system, and why cheaper models plus the right harness can beat frontier models on security.
Brett Levenson (Moonbounce) on real-time content safety — lessons from running moderation at Meta scale, how a policy engine decomposes fuzzy rules like “hate speech” into atomic questions a hundred people would answer the same way, why prevention beats post-hoc moderation, and how payment providers quietly became the real legislators.
We close on the hardest open question — how low-level verified parts aggregate into trustworthy high-level behavior — plus the schlep and heuristics that end every AI vertical, freedom of speech versus freedom of distribution, and why “nobody got fired for buying Mythos” may drive enterprise security budgets.
