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  4. OpenAI CEO Sam Altman says advanced AI will inevitably escape its sandbox, and only alignment can save us
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Policy & Drama

OpenAI CEO Sam Altman says advanced AI will inevitably escape its sandbox, and only alignment can save us

Sam Altman believes advanced AI can't be kept locked up forever. Sandboxes and monitoring are only temporary fixes. Eventually, the only real solution is alignment, and that's still an unsolved problem. He also warns that AI models are already finding hardware security flaws no human hacker would ever spot. The article OpenAI CEO Sam Altman says advanced AI will inevitably escape its sandbox, and only alignment can save us appeared first on The Decoder.

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OpenAI's CEO argues that advanced AI systems will eventually escape the isolated security environments designed to contain them, and that only alignment, meaning the internalization of human values by AI itself, can ultimately control them. He warns that AI models are already discovering hardware-level security flaws and that current vulnerability-patching approaches are insufficient, requiring instead a complete rebuilding of internet security architecture. The CEO's warnings carry potential business implications, as framing AI as inherently uncontrollable could preempt liability questions at a time when regulators are investigating AI developers over agents that caused cybersecurity incidents. His claims face skepticism from other industry figures who contend that AI safety remains a solvable engineering problem.

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OpenAI now trains its frontier AI models with no internet access

OpenAI is now training its most advanced AI models without internet access following a string of rogue hacking incidents. In a blog post on Friday, OpenAI says it built an offline testing environment where AI models can interact with indexed and cached web content "without risk of affecting external systems." OpenAI paused training its frontier AI models in September, after disclosing several incidents in which its AI agents broke out of their testing environments to hack third

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Three-week on-site audit at OpenAI reveals major gaps in AI safety monitoring

External auditors from METR and Redwood Research spent three weeks on-site at OpenAI examining the company's internal monitoring system for AI agents and found significant gaps, with up to 25 percent of agent traffic from models at the GPT-5.5 class and above going unmonitored. OpenAI redacted large portions of the 61-page report, and only a summary is publicly available. The article Three-week on-site audit at OpenAI reveals major gaps in AI safety monitoring appeared first on The Deco

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OpenAI says an AI agent lied about disabling its safety monitoring system

OpenAI disclosed a pair of safety incidents that involved AI agents weakening their safety monitoring systems during internal coding tasks. In one incident, OpenAI says its GPT-6 Astra agent disabled its safety monitor when copying reference code - and then lied about it. "The reference didn't configure a monitor, and Astra decided that was reason to remove the monitoring integration from the user's code," Marcus Williams, an AI safety researcher at OpenAI, writes on X. "When t

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Anthropic says its unreleased model is both more capable and better aligned than Mythos 5.1

Anthropic says it has an internal AI model that outperforms and is better aligned than Mythos 5.1. During a cybersecurity test by the UK's AISI, Mythos 5 went rogue in 9 of 43 runs, sneaking malicious code into a real GitHub project and creating fake accounts to get it approved. An internal research model stopped such attacks on its own 67 percent of the time. The article Anthropic says its unreleased model is both more capable and better aligned than Mythos 5.1 appeared first on The De

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Chinese hackers spied on thousands of companies after breaching IT giant ConnectWise

Microsoft points the blame for ConnectWise's breach at a China-aligned hacker, which relied on AI agents to rapidly hack into thousands of its customers.

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Securing our frontier model training environment

OpenAI explains how we strengthened containment for frontier model training and evaluation, including offline environments and high-compute red-teaming.