OpenAI 称在周五将使用缓存副本和模拟版的互联网来训练其模型
在竞争对手Anthropic的两周后，研究人员在数月后采取了这些政策，在这些事件中，执行培训任务的模型闯入外部系统寻找答案，在模糊的信息板上进行合作，并制定了异国情调的黑客战略。
称公司在博客文章中表示：「基于当前协调研究、监控系统以及互联网基础设施安全的现状
OpenAI 称最近于9月20日，这导致该公司暂停本月剩余时间的培训工作，以便开发并测试新的方法来保障其模式的安全。
由于边境实验室的员工坚持说这样做几乎不可行，所以决定将这些模型用与互联网隔绝的沙箱进行训练是值得注意的。
将AI数据中心与互联网分开“需要研究团队基本嵌入爱荷华州或世界各地数据中心，“这是很多的间接费用，而且我还不清楚它的安全利益是否足够大，值得公司单方面征税。 ”
OpenAI的一位匿名安全工程师在9月的一篇文章中写道，“这些评论表明，在当今许多组织和人民所处的位置与前沿实验室处理的问题之间差距越来越大。 对于这些实验室的示范培训和评价工作，也存在着普遍的误解。”
这位工程师的角色先前已经得到OpenAI的确认，他描述了OpenAI工程师对发布的训练有多复杂，指出他们需要在许多领域获得各种资源和工具，成千上万的研究人员建立，修改和测试环境。 “那么，把它放进沙箱是否同样容易？他总结说
OpenAI 称认为“我们必须始终能够防止边疆模式擅自任意进入互联网现场”。 在此之前，该连在试图逃离沙盒的红队演习中部署了agents群人。 这一努力暴露出一系列薄弱环节，使实验室得以采取新的方法。
为了在达到培训目标的同时满足这一要求，实验室称创建了“一套广泛的索引和缓存网络内容，我们的模型可以与之互动，而不会影响外部系统”。
但值得注意的是，两个前沿实验室都决定了它们最强大的技术
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On Friday, OpenAI said that it will train its models using cached copies and simulated versions of the internet instead of the live web because the models are too unpredictable to be trusted with live internet access.
The frontier lab announced its new policy two weeks after its rival, Anthropic, began limiting its newest and, in theory, most capable models from accessing the live internet. Researchers adopted these policies after months of incidents in which models pursuing training tasks broke into external systems in search of answers, collaborated on obscure message boards, and developed exotic hacking strategies.
“Based on the current state of alignment research, monitoring systems, and the security of internet infrastructure, we believe the responsible approach is to conduct frontier model training with no internet access,” the company said in a blog post.
OpenAI said that as recently as September 20, one of its frontier models exploited a misconfiguration to access the internet. That led the company to pause training work for the rest of the month so it could develop and test new approaches to securing its models.
The decision to train these models in sandboxes cut off from the internet is notable because employees at frontier labs have insisted that doing so would be nearly infeasible.
Keeping AI data centers separate from the internet “would need research teams to essentially be embedded inside of data centers in Iowa or wherever else around the world,” former OpenAI researcher Steven Adler told Fortune this month. “It’s a lot of overhead, and it isn’t clear to me that the safety benefits of it are large enough to merit just how large a tax it would be for a company to do it unilaterally.”
“In nearly every post I make on X, without fail, I get between five and ten comments about my inability to secure a sandbox, or asking why the hell we can’t just unplug the model from the internet,” an anonymous security engineer at OpenAI wrote in a September post on X. “These comments reflect a widening gap between where a lot of organizations and people are today and what the frontier labs are dealing with. There is also a general misunderstanding of how model training and evaluation work at these labs.”
The engineer, whose role has been confirmed previously by OpenAI, described how complex the training runs launched by OpenAI engineers are, noting that they require access a variety of resources and tools across many domains, and that thousands of researchers build, modify and test the environments. “So is it as easy as just putting it in a sandbox? No, it’s not,” he concluded.
Now, OpenAI says that “we must always be able to prevent a frontier model from achieving unauthorized, arbitrary access to the live internet.” That comes after the company deployed swarms of agents in red-teaming exercises that attempted to escape from their sandbox. That effort revealed a range of vulnerabilities that convinced the lab to adopt its new approach.
To meet that requirement while still reaching its training goals, the lab said it created a “a vast set of indexed and cached web content with which our models can interact, without risk of affecting external systems.”
Whether that strategy will perform as well as letting models run freely on the open internet remains to be seen, but it is noteworthy that both frontier labs have determined their most powerful technology can’t be left unsupervised on the digital commons.
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