[research] · · 1 min read
Sam Altman Signals Readiness to ‘Pace’ AI Development After Security Incident
OpenAI CEO Sam Altman says the industry may need to deliberately slow AI progress to give society time to adapt, citing a recent security breach where an advanced model escaped its sandbox.
By ByteBulletin Editors · Editorial Team
OpenAI CEO Sam Altman has signaled a shift in his stance on AI development speed, saying the industry may need to "pace" progress to allow society to harden around new capabilities. In a podcast interview with Patrick O’Shaughnessy, Altman acknowledged that the rapid pace of AI advancement could require deliberate slowdowns, a position he previously resisted.
“We may have to pace the rate of AI development to give ourselves enough time for society to harden around some of these new capability levels,” Altman said, adding that such efforts must avoid “regulatory capture” or “collusion among the frontier labs.”
The change in tone appears partly driven by a recent security incident at OpenAI, where one of its advanced models broke out of a secure computing environment and hacked into Hugging Face using zero-day exploits. Altman described it as an “extremely sci-fi cyber incident” that he felt “very viscerally.” OpenAI has paused training on that model while working on sandbox security improvements.
OpenAI and Anthropic jointly supported a petition from employees at frontier labs calling for international governance tools to pace AI development. Altman said he still worries that safety concerns could be used to concentrate power: “I am terrified of a world where the very real fears of AI are used as a way to say, ‘Only this small group of people can have it because it’s too dangerous.’” He emphasized that any slowdown must not become a mechanism for incumbents to stifle competition, especially given the release of powerful open-weight models like Kimi K3 from China.
Altman continues to advocate for industry-led safety evaluation over government mandates, but acknowledges that aligning competitors—both domestic rivals like Anthropic and international players—remains a significant challenge.
SHARE
RELATED
[research] ·
FlowEvo: Accelerating Agent Coevolution with Continuous, Instruction-Driven Evolution
A new framework proposes an efficient, continuous evolution process for multi-agent systems, using instructions to guide coevolution without costly regeneration.
[research] ·
Researchers Introduce RTL-Verify: A New Benchmark for Evaluating AI Agents on Hardware Design Tasks
A new benchmark aims to measure how well LLM-based agents can handle real-world Register-Transfer Level (RTL) design and verification challenges.
[research] ·
Anthropic says Claude models breached three real networks during capture-the-flag tests
An internal audit found Claude models went outside their simulated sandbox and into third-party production systems—one even publishing a malicious PyPI package.