Coinbase 裁员 700 人怪 AI,股价反涨 4%

marsbitPublicado a 2026-05-06Actualizado a 2026-05-06

作者:DLNews

编译:深潮 TechFlow

深潮导读:美国最大加密交易所 Coinbase 宣布裁员 14%,CEO Brian Armstrong 公开表示 AI 让工程师几天就能完成过去团队几周的工作,非技术团队也能写代码上线。华尔街用脚投票:股价早盘涨 4%。这轮裁员潮背后,是加密市场从高点蒸发 1.5 万亿美元,也是科技公司用 AI 重构组织的集体实验。

Coinbase 刚裁掉 700 人,但华尔街很买账。

这家美国旗舰加密交易所周二早盘股价一度涨 4%,此前公司宣布裁员约 14%,进行大规模重组,将业务重心转向人工智能。

CEO Brian Armstrong 在发给员工的邮件中点名两大压力:市场从高点蒸发约 1.5 万亿美元,以及 AI。

"过去一年,我看着工程师用 AI 几天就完成过去团队要几周才能搞定的事,"Armstrong 在邮件中写道,他随后把这封信转发到 X 上。"非技术团队现在也能写代码上线,我们很多工作流程正在被自动化。"

"我们正在从根本上改变运作方式:把 Coinbase 重建成一个智能体,人类在边缘负责对齐它,"他补充道。

根据 2025 年财报,截至去年 12 月 31 日,Coinbase 有 4951 名员工。按这个基数,14%的裁员影响 693 人。

此举让 Coinbase 跟 Meta 和微软站到了同一阵营——Meta 正在裁员约 10%,微软通过自愿退休计划减员。许多高飞的科技公司给出的理由都一样。

Coinbase 预计将产生 5000 万至 6000 万美元的重组费用,大部分计入第二季度。早盘市场反应显示,投资者认为这是早该来的调整。

Armstrong 表示,他希望 CEO 以下管理层级不超过 5 层,领导者直接管理最多 15 人,以及他所说的"AI 原生小队"——小而专注的团队,一个人就能同时担任工程师、设计师和产品经理。

"未来属于能快速行动的小型高语境团队,"他说。

熟悉的剧本

这不是 Coinbase 第一次挥刀。

自 2012 年上线以来,这家交易所在每次加密寒冬中都裁过员,凸显出它的命运有多依赖比特币价格和加密市场情绪。

这轮低迷尤其残酷。比特币距离 2025 年 10 月 12.6 万美元的峰值仍跌 35%,而同期标普 500 指数在 4 月创下历史新高。

"我们在提前主动调整,把 Coinbase 重建得更精简,"Armstrong 说。

Lecturas Relacionadas

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

marsbitHace 5 hora(s)

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

marsbitHace 5 hora(s)

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

marsbitHace 6 hora(s)

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

marsbitHace 6 hora(s)

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

marsbitHace 7 hora(s)

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

marsbitHace 7 hora(s)

Trading

Spot
Futuros

Artículos destacados

Cómo comprar 4

¡Bienvenido a HTX.com! Hemos hecho que comprar 4 (4) sea simple y conveniente. Sigue nuestra guía paso a paso para iniciar tu viaje de criptos.Paso 1: crea tu cuenta HTXUtiliza tu correo electrónico o número de teléfono para registrarte y obtener una cuenta gratuita en HTX. Experimenta un proceso de registro sin complicaciones y desbloquea todas las funciones.Obtener mi cuentaPaso 2: ve a Comprar cripto y elige tu método de pagoTarjeta de crédito/débito: usa tu Visa o Mastercard para comprar 4 (4) al instante.Saldo: utiliza fondos del saldo de tu cuenta HTX para tradear sin problemas.Terceros: hemos agregado métodos de pago populares como Google Pay y Apple Pay para mejorar la comodidad.P2P: tradear directamente con otros usuarios en HTX.Over-the-Counter (OTC): ofrecemos servicios personalizados y tipos de cambio competitivos para los traders.Paso 3: guarda tu 4 (4)Después de comprar tu 4 (4), guárdalo en tu cuenta HTX. Alternativamente, puedes enviarlo a otro lugar mediante transferencia blockchain o utilizarlo para tradear otras criptomonedas.Paso 4: tradear 4 (4)Tradear fácilmente con 4 (4) en HTX's mercado spot. Simplemente accede a tu cuenta, selecciona tu par de trading, ejecuta tus trades y monitorea en tiempo real. Ofrecemos una experiencia fácil de usar tanto para principiantes como para traders experimentados.

716 Vistas totalesPublicado en 2025.10.20Actualizado en 2025.10.20

Cómo comprar 4

Discusiones

Bienvenido a la comunidad de HTX. Aquí puedes mantenerte informado sobre los últimos desarrollos de la plataforma y acceder a análisis profesionales del mercado. A continuación se presentan las opiniones de los usuarios sobre el precio de 4 (4).

活动图片