Jensen Huang says Nvidia achieved AGI, again — not that it matters
Jensen Huang says Nvidia achieved AGI, again — not that it matters
黄仁勋称英伟达已实现 AGI，但这并不重要
On Nvidia’s earnings call Wednesday, CEO Jensen Huang casually announced the company had “achieved AGI,” one of the tech industry’s ultimate goals some of its biggest players have spent years chasing. Almost immediately, Huang dismissed the coveted milestone as “senseless.” 在周三的英伟达财报电话会议上，首席执行官黄仁勋随口宣布该公司已经“实现了 AGI（通用人工智能）”。这是科技行业最核心的目标之一，也是一些巨头企业多年来一直追逐的愿景。但紧接着，黄仁勋便将这一令人垂涎的里程碑斥为“毫无意义”。
He’s right. For the supposed finish line of the AI race, there is no consensus on what artificial general intelligence means, let alone how we’ll know when we’ve actually got there, which makes achieving it equally arbitrary. 他是对的。作为人工智能竞赛中所谓的终点线，目前对于“通用人工智能”的定义尚无共识，更不用说我们如何判断何时真正达到了这一目标，这使得“实现 AGI”这一说法显得同样武断。
Asked about OpenAI’s pursuit of AGI, Huang said that when it comes to Nvidia, “for many tasks, we could say that we’ve already achieved AGI.” He did not provide a precise definition or benchmark, but added, “I think of all of those milestones and all those, you know, they’re kind of senseless at this point.” He also pointed to AI moving beyond responding to simple prompts to autonomous agents capable of learning new skills and improving themselves “recursively.” What really matters, Huang said, is that AI is “doing productive and useful work” and “generating profitable tokens,” with more compute producing more tokens — and, inevitably, more profit. “This is the exact phase where we’re at. Which is the reason why everybody’s leaning in.” 在被问及 OpenAI 对 AGI 的追求时，黄仁勋表示，就英伟达而言，“对于许多任务，我们可以说已经实现了 AGI。”他没有提供精确的定义或基准，但补充道：“我认为所有这些里程碑，在现阶段看来都是毫无意义的。”他还指出，人工智能正在超越简单的提示词响应，转向能够学习新技能并“递归”自我提升的自主智能体。黄仁勋认为，真正重要的是人工智能正在“从事富有成效和有用的工作”，并“生成可盈利的 Token（代币/数据单元）”，更多的算力产生更多的 Token，进而不可避免地带来更多的利润。“这正是我们所处的阶段，也是每个人都全力投入的原因。”
This isn’t the first time Huang has said we’ve reached AGI. In March, during an appearance on the Lex Fridman podcast, he plainly stated, “I think we’ve achieved AGI.” Huang didn’t say exactly what he meant by AGI. Fridman proposed his own oddly specific definition: an AI system that’s able to “essentially do your job,” as in start, grow, and run a successful tech company worth more than $1 billion. Walking back his earlier claims, Huang said that “the odds of 100,000 of those agents building Nvidia is zero percent.” 这并不是黄仁勋第一次声称我们已经达到了 AGI。今年 3 月，在参加 Lex Fridman 的播客节目时，他曾明确表示：“我认为我们已经实现了 AGI。”黄仁勋当时并没有说明他所指的 AGI 具体是什么。Fridman 提出了他自己一个奇怪且具体的定义：一个能够“本质上完成你的工作”的人工智能系统，比如创办、发展并运营一家价值超过 10 亿美元的成功科技公司。黄仁勋随后收回了之前的说法，称“让 10 万个这样的智能体去建立英伟达的概率为零”。
Over the years, other tech leaders have capitalized on the term’s fuzziness and produced a veritable grab bag of definitions and benchmarks, all orbiting the same nebulous concept: AI capable of matching or surpassing human intelligence across a broad range of domains, despite the fact that “intelligence” also doesn’t have a universally agreed-upon definition. 多年来，其他科技领袖利用该术语的模糊性，提出了五花八门的定义和基准，所有这些都围绕着同一个模糊的概念：即人工智能能够在广泛的领域内匹配或超越人类智能，尽管事实上“智能”本身也没有一个普遍公认的定义。
The definition of AGI according to OpenAI – a company founded with the explicit goal of building it – leaves a lot of room for interpretation. In its charter, OpenAI defines AGI as “highly autonomous systems that outperform humans at most economically valuable work.” Altman himself has acknowledged that this is hardly a measurable standard, admitting last year that AGI is “not a super useful term.” Complicating matters is OpenAI’s different, financially-driven definition of AGI it worked out with Microsoft — reportedly systems that can generate at least $100 billion in profits. In a recent Time story, chief research officer Mark Chen estimated OpenAI is “80% of the way” to AGI, while Altman said that by the end of the year the company would have something he would call AGI. OpenAI——一家以构建 AGI 为明确目标而成立的公司——对 AGI 的定义留下了很大的解读空间。在其章程中，OpenAI 将 AGI 定义为“在大多数具有经济价值的工作中表现优于人类的高度自主系统”。Altman 本人也承认这很难成为一个可衡量的标准，并在去年承认 AGI “并不是一个非常有用的术语”。更复杂的是，OpenAI 与微软达成了一套不同的、以财务为导向的 AGI 定义——据报道，即能够产生至少 1000 亿美元利润的系统。在最近《时代》杂志的一篇报道中，首席研究官 Mark Chen 估计 OpenAI 已经完成了 AGI 之路的“80%”，而 Altman 则表示，到今年年底，公司将拥有他称之为 AGI 的东西。
The fact that both AGI and its threshold remain undefined is no secret: tech leaders say so themselves, even as they make predictions predicated on it. Anthropic CEO Dario Amodei has called AGI “imprecise,” even a “marketing term,” preferring instead to talk about “powerful AI.” Others have similarly reached for their own terms to describe broadly similar ideas. In theory, there are supposed to be distinctions between them, but in practice they all bleed together. Meta talks about “personal superintelligence,” Microsoft “humanist superintelligence,” and Amazon “useful general intelligence.” Google DeepMind’s Demis Hassabis has taken to talking about how we’ve arrived at the “foothills of the singularity.” And OpenAI cofounder Ilya Sutskever, who reportedly led employees in chants of “feel the AGI,” now runs a company called Safe Superintelligence. AGI 及其阈值至今未被定义，这已不是什么秘密：科技领袖们自己也这么说，尽管他们依然基于此做出预测。Anthropic 首席执行官 Dario Amodei 称 AGI 是“不精确的”，甚至是一个“营销术语”，他更倾向于谈论“强大的人工智能”。其他人也纷纷提出自己的术语来描述大致相同的想法。理论上，它们之间应该有所区别，但在实践中，这些概念都混在一起。Meta 谈论“个人超级智能”，微软谈论“人文主义超级智能”，亚马逊则谈论“有用的通用智能”。谷歌 DeepMind 的 Demis Hassabis 开始谈论我们是如何到达“奇点山脚下”的。而据报道曾带领员工高呼“感受 AGI”的 OpenAI 联合创始人 Ilya Sutskever，现在经营着一家名为“安全超级智能”（Safe Superintelligence）的公司。
So long as AGI remains poorly defined and carelessly used, the whole thing is senseless. Well, unless you want a handy tool for hyping up progress. So expect the industry — Huang included — to keep the AGI talk coming. Maybe an AGI will eventually show up and tell us what AGI actually means. 只要 AGI 的定义依然模糊且被随意使用，整件事就是毫无意义的。当然，除非你需要一个炒作进展的趁手工具。因此，预计整个行业——包括黄仁勋在内——会继续谈论 AGI。也许最终会有一个真正的 AGI 出现，并告诉我们 AGI 到底意味着什么。