优步的AI推进受阻——首席技术官表示，尽管已花费34亿美元，仍面临预算问题。

优步的AI推进受阻——首席技术官表示，尽管已花费34亿美元，仍面临预算问题。
Uber’s Anthropic AI push hits a wall

原始链接: https://finance.yahoo.com/sectors/technology/articles/ubers-anthropic-ai-push-hits-223109852.html

优步在快速扩展其人工智能整合时，面临着意外的高成本。尽管2025年投入了34亿美元的研发资金，但由于工程师们热衷于采用Anthropic的Claude Code等人工智能编码工具，该公司已经超出了2026年的人工智能预算。虽然人工智能已被证明具有生产力——目前为诸如行程匹配等功能贡献了11%的后端代码更新，但由于内部激励措施鼓励使用，其使用量的激增正在推高成本。优步正在探索OpenAI的Codex等替代方案以控制成本。长期目标是“代理工程师”——能够处理整个编码流程的人工智能系统。然而，这种积极的人工智能推动引发了关于人工智能承担更多责任后，公司内部人类工程师未来角色的问题。优步预计随着人工智能成为其运营的关键且可能昂贵的组成部分，研发支出将继续增加。

## Uber 的人工智能投资遭遇阻碍 Uber 大力投资人工智能，特别是 Anthropic 的 Claude Code，但面临挑战。尽管研发预算高达 34 亿美元，该公司的人工智能专项资金据报道耗尽得比预期更快，引发了成本效益的质疑。核心问题不一定在于人工智能本身，而在于*如何*实施。许多用户报告称，Uber Eats 中的人工智能生成的菜单摘要过于笼统且无用，缺乏人工撰写描述的细微差别。内部开发人员被鼓励最大限度地使用人工智能工具，可能导致成本上升，但生产力提升不成比例。担忧不仅限于营销文案。一些人认为，Uber 正在优先考虑花哨的人工智能集成，而不是对其核心平台的根本改进——例如稳定且响应迅速的用户界面——从而导致令人沮丧的用户体验。关于当前方法是否是真正的创新驱动力，还是仅仅是展示人工智能采用的代价高昂的尝试，存在争议，一些人认为缺乏清晰的愿景和对工程师的信任正在阻碍成功。最终，讨论强调了将人工智能投资与切实改进相结合的重要性，并避免“为了人工智能而人工智能”。

原文

Uber Technologies, Inc is learning the hard way that scaling AI isn't just about speed—it's about cost. Despite spending $3.4 billion on research and development, the company has already exhausted its planned AI budget just months into 2026.

According to The Information, Chief Technology Officer Praveen Neppalli Naga said Uber is now "back to the drawing board" after a surge in the use of AI coding tools, particularly Anthropic's Claude Code, has blown past internal expectations.

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Uber didn't hold back on AI adoption. Engineers were actively encouraged to use tools like Claude Code and Cursor, even ranking them on internal leaderboards based on usage. That push drove rapid adoption—but also a sharp rise in costs.

Naga noted that Claude Code has quickly become the dominant tool, with usage surging since late last year, while Cursor has plateaued. Uber is now preparing to test OpenAI's Codex as it expands its AI stack further.

The financial pressure is already building. Uber's R&D expenses rose 9% to $3.4 billion in 2025, and the company expects that figure to keep climbing—suggesting AI may be as much a cost driver as a productivity lever.

The payoff is starting to show. Around 11% of Uber's live backend code updates are now written by AI agents, up sharply in just a few months. These systems power everything from ride-matching to pricing and bug fixes.

Naga said the longer-term vision goes further. He sees a shift toward "agent engineers"—AI systems that don't just assist but fully handle coding, testing and deployment, with other AI tools supervising the process.

Hiring hasn't slowed yet. But as AI takes on more of the workload, Uber's aggressive push raises a bigger question: how long before the engineers themselves start taking a back seat?

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优步的AI推进受阻——首席技术官表示，尽管已花费34亿美元，仍面临预算问题。 Uber’s Anthropic AI push hits a wall

优步的AI推进受阻——首席技术官表示，尽管已花费34亿美元，仍面临预算问题。
Uber’s Anthropic AI push hits a wall