我们为什么这么急？我们是在比赛吗？终点线在哪里？我们领先吗？还是远远落后？我越来越多地听到人们提出关于人工智能的这些问题，他们有一种令人不快、过度刺激的粗粝感——就像一个被允许熬夜太久、现在无法入睡的三岁小孩。自从去年11月人工智能工具突然变得“足够好”而获得广泛实用以来，这种感觉变得更加糟糕。
Why are we in such a hurry? Are we in a race? Where's the finish line? Are we in the lead? Far behind? I increasingly hear these questions about AI from people who feel a gritty sense of being unpleasantly overstimulated – like a three-year-old allowed to stay awake too long and now unable to sleep. That feeling has become worse since last November when AI tools suddenly became "good enough" to be broadly useful.
整整一代工程师——包括我在内——发现自己充满了狂热的能量，迸发出如何用这个美妙的新玩具来提升工具和流程的想法。使用量呈爆炸式增长——收入也是如此。人工智能公司终于走上了一条隐约暗示盈利的道路，它们顺势而为，加快了发布节奏。每一个新模型都感觉像是过圣诞节。在过去这十个月左右的时间里，我们已经过了很多个圣诞节。
A whole cohort of engineers – myself included – found themselves infused with manic energy, bursting with ideas on how to prompt up tools and processes with this wonderful new toy. Usage exploded – as has revenue. The AI firms, finally on a path to something vaguely suggestive of profitability, leaned in and increased their release cadence. Every new model felt like Christmas. We've had a lot of Christmases these past ten months or so.
我认识的几乎每个工程师都积累了巨额的“玩具债”，他们无法停止试验比我们任何人在整个职业生涯中都有希望掌握的更多的工具。每一个新模型都会给用户带来快速的多巴胺刺激，但这种兴奋感会消退，低谷随之而来。这就是我们现在的处境。工程师们感到筋疲力尽。通往“超级智能”（不管那是什么）的竞赛给我们留下了一种完全不同的东西：称之为“昏木智能”——那种我们吸收的东西超过了我们所能消化的感觉。更多的人工智能只会是毫无意义的过剩。
Almost every engineer I know has accrued a massive "toy debt," unable to stop experimenting with more tools than any of us could ever hope to master across an entire career. Each new model delivers a quick dopamine hit to users, but the high wears off and the slump arrives. That's where we are now. Engineers feel exhausted. The race to "Super Intelligence" (whatever that is) left us with something else entirely: call it "stupor intelligence" – the feeling that we've absorbed more than we can digest. More AI would just be pointless excess.
如果这是人工智能泡沫内部的观点，那么在外部看起来如何？情况没那么好。《华尔街日报》自信地报道称，63%的美国人赞成立即暂停或放慢人工智能的发展。他们能看出这项技术发展得太快、太狂热、而且失控了。这让他们感到不安。
If that's the view from inside the AI bubble, how does it look on the outside? Not so great. The Wall Street Journal confidently reports that 63 percent of Americans favor an immediate pause or slowdown in AI development. They can see this technology is moving too fast, in too manic a rush, and without control. It's making them uneasy.
这种无形的不安转化为了一种广泛的焦虑，即机器很快就会崛起并杀死我们所有人。这在行业内部得到了反映，人们出现了极端的精疲力竭，发布了关于迫在人类灭绝事件的长篇大论。前Anthropic员工雅各布·考克斯森（Jacob Coxon）的辞职帖之所以在网上广为流传，是因为它为人们的焦虑提供了一个焦点。暂停一下，喘口气，难道会要了我们的命吗？
That shapeless unease takes form as a widespread anxiety that the machines will soon rise up to kill us all. It's reflected within the industry as people spectacularly burn out, posting long screeds about the imminent human extinction event. Former Anthropic staffer Jacob Coxon's resignation post went viral because it gave folks a focus for their anxieties. Would it kill us to pause and catch our breath?
以下是残酷的真相：企业已经有了比它们在未来几年内所能处理的更多的技术变革需要消化。我们拥有丰富的“足够好”的人工智能——美国的、中国的和欧洲的——来彻底改变商业运营。这将会发生，但时间尺度是以年为单位，而不是天。
Here's the raw truth: businesses already have more technological change to digest than they can work through for years to come. We've a wealth of "good enough" AI – American, Chinese, and European – to completely transform business operations. That will happen, but on a timescale of years, not days.
将新的、更好的、更闪亮的人工智能模型推向市场已经成为一个收益递减的项目。不是因为模型已经陷入平台期，而是因为文化已经陷入平台期。我们根本无法处理更多的人工智能了。
Bringing new, better, shinier AI models to market has become a project of diminishing returns. Not because the models have plateaued, but because the culture has. We simply can't process any more AI.
那么我们如何停下来？模型制造商与其客户之间的盈利循环不会自动暂停。它只会变得更快、更猛烈。与此同时，我们看到了勒德分子2.0运动（Luddite 2.0）的萌芽，意图在机器取代所有工人之前摧毁它们。如果我们继续向前冲，对数据中心的抵制将是可能变得丑陋的事情的友善面孔。
So how do we stop? The profitable loop between the model makers and their customers won't pause on its own. It will only go faster and harder. At the same time, we're seeing the stirrings of a Luddite 2.0 movement, intent on destroying the machines before they replace all the workers. Resistance to datacenters is the friendly face of something that could turn ugly if we simply keep charging ahead.
有一件事可能会放慢速度：保持这些系统受控的成本。模型变得越聪明，就越难管理。每天都有更多关于“失控智能体”从似乎避开了设计安全测试环境的艰苦工作的实验室触及外部系统的报道。事实证明，更强大的模型的控制成本越来越高。最终，成本超过了效益。当前沿实验室及其产品成为不可保单的风险时，我们可能只需一场诉讼就能实现暂停。
One thing could slow us: the cost of keeping these systems under control. The smarter models become, the more difficult they are to manage. Every day brings more reports of "rogue agents" reaching external systems from labs that seem to have avoided the hard work of designing secure test environments. More powerful models could prove increasingly costly to contain. Eventually, costs outweigh benefits. We could be one lawsuit away from reaching a pause, when the frontier labs and their products become uninsurable risks.
希望我们在发生真正的恶作剧之前暂停。否则，插头可能会被拔掉，所有漂亮的圣诞彩灯都会熄灭。主动行事，保持清醒和谦逊，远比面对不可抗力要好。®
Here's hoping we pause before some real mischief occurs. Otherwise, plugs may be pulled, and all the pretty Christmas lights will go out. Better by far to act with agency, clear-eyed and humble, than confront force majeure. ®