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Applied AI·September 19, 2026·1 min read

Weeks ago Jensen Huang said labs should pace themselves if they felt out of control. Now he puts the risk at 0%.

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When the leading GPU supplier says there is a 0% chance AI ends the world by 2030 and urges the industry to go "as fast as it can," he is giving political cover for maximal deployment and capex. If you’re an operator, assume less regulatory drag than the doomer narrative implies and plan for faster model iteration, but do your own risk thresholds instead of outsourcing them to suppliers.

Applied AI

A look at AI safety groups METR, Redwood Research, and Apollo Research, as AI misalignment incidents at OpenAI and Anthropic thrust them into the spotlight

Independent groups like METR, Redwood, and Apollo moving from the margins into the spotlight after misalignment incidents means third-party evals are becoming part of the de facto governance stack. If you’re deploying frontier models, expect board and regulators to ask which external evaluators you use—not just what your internal red-teaming looks like.

Applied AI

Three researchers used Claude to reach OpenAI’s internal code. OpenAI paid $6,500 and closed the hole in 14 hours.

Researchers chaining two weaknesses and using Claude to reach OpenAI employee accounts and internal code in under 72 hours—then getting $6,500—shows AI-augmented offense is cheap while the potential blast radius is huge. If you run bug bounties or internal red teams, assume attackers have LLM copilots and raise both rewards and response readiness accordingly.