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@Yuchenj_UW· @Yuchenj_UW · X·· 23 天前AI 评分52
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Yuchen Jin 对比指出,扎克伯格的 AI 安全观点与多数前沿实验室相反:主流实验室认为模型越强越危险、应限制访问,扎克伯格则认为模型越强,让少数实验室掌控它越危险。扎克伯格在引用的帖文中称,各实验室有责任也有动力按安全训练所需的节奏推进,信任与对齐正在成为区分智能体和模型的关键能力,并提到 Meta 曾为专注安全与安保推迟发布 Muse 数月,以及承诺把大部分算力用于服务人们而非竞相追求递归自我改进。配图文字称,应把超级智能广泛分发给每个人而非集中掌控。

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Zuck’s AI safety take is basically the opposite of most frontier labs:

Most labs:
The more powerful the model, the more dangerous it is, so access should be restricted.

Zuck:
The more powerful the model, the more dangerous it is to let a few labs control it.

Zuck is Based. https://t.co/1AzNngKZ2m https://t.co/MGL3FS4oZ7

引用@finkd@finkd
Last month I wrote about how we can build a positive and safe future for everyone: https://t.co/eoLGVY8yad Every lab has the responsibility and incentive to move at the pace required to train its models safely, and the ability to take its own actions to ensure that happens. The reality is: - People won't want to use agents that are misaligned with them and that don't do what they ask, so labs have a strong natural incentive to make their models more aligned. There is a lot of debate about slowing progress on capabilities until alignment catches up. My view is that trust and alignment are quickly becoming the most important capabilities that will differentiate agents and models. Any lab that doesn't focus on alignment will fall behind. - Labs face significant liability if their models cause harm, so they have a strong incentive to prevent this as well. Meta delayed shipping Muse for several months to focus on safety and security. We didn't call for everyone else to do this before we would. We just did it as part of our day-to-day work because it was clearly the right thing for people and for us. I'm proud of the security foundations we've built. - Engaging independent evaluators and advisors is industry best practice. MSL already does this today in several areas because it helps produce better work. Other labs can just do this too. In general, it would be helpful for there to be a larger and more diverse ecosystem of evaluators. - Committing the significant majority of compute towards serving people rather than racing towards recursive self-improvement is one of the best ways to ensure we develop this technology safely. Meta has made this commitment and other labs can do this as well. I believe the key to building a positive future for everyone is maintaining the right balance of power. This is within our power to do.
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