Uber 总裁表示,对人工智能的投入正变得“越来越难以证明其合理性”。
Uber president says AI spending is getting 'harder to justify'

原始链接: https://www.theverge.com/transportation/937116/uber-ai-investment-hard-to-justify

Uber 正在重新评估其激进的人工智能投资策略,因为其 2026 年的预算在短短四个月内就已耗尽。尽管投入了巨额资金(包括 2025 年 34 亿美元的研发预算),但首席运营官 Andrew Macdonald 表示担忧,因为目前尚无明确证据表明 Token 消耗量的增加与交付具有实际意义的用户功能之间存在相关性。 虽然首席执行官 Dara Khosrowshahi 此前通过缩减人力规模来平衡不断上升的 AI 成本,但该公司现在正质疑这种权衡的可持续性。Macdonald 指出,尽管 Token 使用量等内部指标呈“天文数字般”增长,但对生产力的实际影响仍然难以量化。因此,Uber 计划审查其 AI 工具的成本效益,并暗示除非公司能够明确 AI 支出与产品功能提升之间的直接联系,否则目前的投资水平可能将难以维持。

Uber 总裁近期表示,该公司在人工智能方面的支出正变得愈发难以自圆其说,这一表态在 Hacker News 上引发了关于当前 AI 投资狂热的批判性讨论。 评论者们对这些巨额开支所带来的回报持怀疑态度,并指出网约车服务的核心用户体验在很大程度上并无变化。批评者嘲讽近期推出的 AI 功能(如“Eats for the way”)是噱头,既不实用也不必要。 这场讨论反映了人们对企业“强制 AI 化”的广泛不满。许多用户认为,公司正在盲目跟风,迫使工程师为了满足管理层或投资者的需求而“消耗代币”,而非解决实际的业务问题。参与者将当前的这种压力与此前的区块链和微服务等行业热潮进行了对比,并指出,尽管公司往往在基础设施建设上斤斤计较,却又莫名热衷于为每位员工补贴昂贵的 AI 订阅费用。总的来说,人们普遍认为,企业将“采用 AI”的外在表现置于实用价值之上,导致了严重的浪费,却未能带来任何实质性的创新。
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原文

After reportedly exhausting its annual AI budget just four months into 2026, Uber is now questioning whether it’s actually seeing meaningful returns on its investments. In an interview with Rapid Response, Uber president and chief operating officer Andrew Macdonald said the company isn’t seeing a connection between rising token consumption for Claude Code and more useful features being delivered to consumers.

“That link is not there yet, right? I think maybe implicitly there is more that is getting shipped, but it’s very hard to draw a line between one of those stats and, ‘Okay, now we’re actually producing 25 percent more useful consumer features,’” said Macdonald. “I think over the coming quarters and years, maybe that will become clearer, but I think today it’s hard, even if some of the underlying metrics are trending in a really astronomical direction.”

Uber spent $3.4 billion on research and development efforts in 2025, 9 percent more than it had spent the previous year. Earlier this month, Uber CEO Dara Khosrowshahi said the company was making up for its increasing AI investments by hiring fewer human employees.

“We’re going to have to start talking about token consumption and the associated cost versus headcount,” said Macdonald. “So if you’re not actually able to draw a direct line to how much useful features and functionality you’re shipping to your users, that trade becomes harder to justify.”

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