马斯克和Anthropic，要去太空找电了

Odaily星球日报Publicado em 2026-05-07Última atualização em 2026-05-07

原创 | Odaily 星球日报(@OdailyChina)

作者|Azuma(@azuma_eth)

马斯克和 Anthropic,竟然牵上手了!

北京时间 5 月 7 日凌晨,Anthropic 和 SpaceX 联合发布的一则公告,瞬间震惊了整个 AI 圈。根据公告内容,双方已签署合作协议,Anthropic 将使用 SpaceX Colossus1 数据中心的全部算力容量,这将在一个月内为 Anthropic 提供超过 300 兆瓦的新算力(相当于超 22 万张 NVIDIA GPU),直接改善 Claude Pro 与 Claude Max 订阅用户的使用体验。

这是马斯克的商业帝国首次与 Anthropic 达成如此直接、正式、且大规模的合作。过去多年间,Anthropic 的核心合作方一直是 Amazon 和 Google,无论是云基础设施、芯片供应还是模型训练,Anthropic 长期都深度绑定 AWS 与 Google TPU 体系。马斯克不仅从未公开投资过 Anthropic,甚至还曾多次公开批评其 AI 安全路线以及政治倾向。双方之间,此前几乎不存在任何公开的基础设施合作、模型合作或商业联盟记录。

当最能打的大模型公司和最具话题性的世界首富终于搭上线。这样的合作,天然就自带话题感。

马斯克的小心思

对于马斯克而言,本次合作更微妙的地方在于时间点。

就在十天前(4 月 27 日),马斯克起诉 OpenAI 一案正式已于加利福尼亚州北区联邦地区法院进入庭审阶段,双方在近些天的出庭中花式互喷,火药味十足。这场被外界视作“AI 时代第一大案”的诉讼,几乎已经成为马斯克与 OpenAI 长期恩怨的全面公开化。

而 Anthropic,恰恰正是 OpenAI 当前最核心、最直接的竞争对手之一。于是这场合作便天然多出了一层耐人寻味的意味 —— 敌人的敌人就是朋友,只要能让 OpenAI 难受,老马什么都干得出来。

而若从 AI 竞争格局的角度往深处去看,这场合作也预示着马斯克在 AI 时代下的布局思路演变。

表面上,这只是一次标准的算力交易 —— SpaceX 提供 GPU 集群,Anthropic 获得更多推理资源,双方各取所需。但这件事显然没那么简单。

因为马斯克如今围绕 AI 所做的事,早已不只是“下场做模型”。过去两年,由于马斯克亲自下场做了 xAI(如今已改名叫 SpaceXAI),外界更多把 OpenAI、Anthropic 等大模型公司视作马斯克的潜在竞争对手,但随着超级计算集群 Colossus 的建成与投用,数据中心能力开始外溢,马斯克的角色定位已悄然发生变化。

如今的马斯克已越来越像 AI 世界里的“军火商” —— 谁缺算力,都就可以来找他,哪怕对方是曾经的潜在竞争对手。

深陷“降智”风波的 Anthropic,终于等来了盖世英雄

对于 Anthropic 来说,这次合作的重要性甚至可能比外界想象得更高。

过去几个月,Claude 的口碑一直在经历微妙变化。一方面,Claude Opus 4.7 以及神秘的 Mythos 依旧被视作市面上最优秀的模型;但另一方面,关于 Claude “降智”的声音也开始越来越频繁地出现在社区之中。

尤其是在重度开发者群体里,这种情绪格外明显。有人发现,Claude 在处理长代码、复杂工程任务时,推理能力出现“断崖式下跌”;也有研报指出,Claude 部分模型的“思考预算”或回答长度被大幅削减;更多散户则反馈 Claude 的幻觉越来越严重,模型在处理复杂信息时更容易“一本正经地胡说八道”。

“降智”风波发酵之后,Anthropic 官方已发布技术复盘报告,承认在 3 月至 4 月期间,由于产品层面的调整和 Bug,导致 Claude 模型在复杂任务中出现“性能退化”。

但这一理由并未说服市场,舆论仍普遍认为,高昂的推理成本及算力短缺才是导致 Claude 等大模型产品在实际应用中性能波动的主因。

模型能力越强,推理成本越高;用户规模越大,GPU 消耗越恐怖。所有 AI 公司都绕不开一个商业矛盾 —— 用户希望模型永远“满血运行”,但公司必须控制成本。于是动态限流、推理预算调整、回答长度控制、优先级调度......这些机制几乎都会不可避免地出现,而用户最终感知就是“模型降智了”。

这也是为什么,SpaceX 这笔算力合作对 Anthropic 如此关键。

Anthropic 在公告中表示,随着合作的达成,Claude 核心用户的体验将得到直接改善:

  • 首先,Anthropic 会将 Pro、Max、Team 以及按席位计费 Enterprise 方案的 Claude Code 五小时使用额度提升一倍。
  • 其次,Anthropic 会取消 Pro 和 Max 账户在高峰时段对 Claude Code 的限流措施。
  • 第三,Anthropic 将显著提高 Claude Opus 模型的 API 速率限制。

AI 模型测评大佬 Alex Finn 就双方的本次合作表示,Anthropic 在过去几个月里一直有些熄火,额度下降,模型变笨...然后现在马斯克来救火了,他给了 Anthropic 使用全球最大超级算力集群的机会。Anthropic 的算力危机,一直是整个公司的阿喀琉斯之踵,用户口碑和市场情绪也因此一路下滑,而马斯克只靠一笔合作,就把这个问题解决了。

Alex Finn 用了一句美国球迷们更容易理解的比喻:“马斯克的帮助,相当于直接让Anthropic 拿到了文班亚马!”

最终幻想 —— 上太空找电

在合作公告中,有一段被许多人忽视了小字 —— “双方还有兴趣合作开发数吉瓦级的轨道 AI 算力”。翻译成人话就是,马斯克和 Anthropic 想把 AI 数据中心搬去太空。这听起来属实科幻,但背后反映的问题却非常现实。

AI 圈流量最高的分析师 Aakash Gupta 就此解释道:“地球上的电力、土地和散热能力,已经无法足够快地满足需求。”

Anthropic 如今已锁定了大约 15 吉瓦的算力规模,这相当于 1100 万户家庭用电量,但这依然不够......英伟达能生产芯片,Anthropic 手里也有足够的钱,但真正无法按时制造出来的,是电力、土地,以及散热能力 —— 而模型需求增长的速度已远超这些基础设施的建设速度。

算力竞赛的前沿,如今已经开始冲出地球。而全球只有一家公司,真正有能力把吉瓦级的太阳能阵列大规模送入轨道 —— SpaceX。

如果这种星际穿越般的故事最终成为现实,能做到的人,可能只有马斯克。

Leituras Relacionadas

CLARITY Act: Banking Trade Groups Push For Yield Agreement Revision – Details

US banking trade groups are urging revisions to the stablecoin yield compromise in the upcoming CLARITY Act ahead of a key committee markup. The Act currently aims to ban all passive, deposit-like interest on stablecoins to prevent competition with traditional bank savings, while allowing rewards tied to active uses like staking or transactions. In a letter, groups including the American Banking Association and Bank Policy Institute proposed stricter language to eliminate perceived loopholes for passive yield and prevent deposit flight from banks. However, these efforts are reportedly viewed as minor by some lawmakers. The Senate Banking Committee is scheduled to mark up the bill on May 14, a critical step before it can advance through Congress.

bitcoinistHá 10h

CLARITY Act: Banking Trade Groups Push For Yield Agreement Revision – Details

bitcoinistHá 10h

This Finance CEO Picks Solana Instead Of Bitcoin — Here’s Why

Finance CEO Raoul Pal prefers Solana over Bitcoin, citing its high throughput and low transaction costs as better suited for the future crypto-AI era. He believes Solana is ideal for machine-to-machine microtransactions and AI-driven DeFi activity, predicting AI agents will soon dominate DeFi users. While Bitcoin serves as a store of value, Pal sees higher growth in networks built for mass, automated transactions. This view was highlighted at Consensus 2026, where AI integration and crypto infrastructure were key themes.

bitcoinistHá 10h

This Finance CEO Picks Solana Instead Of Bitcoin — Here’s Why

bitcoinistHá 10h

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.

marsbitHá 11h

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

marsbitHá 11h

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.

marsbitHá 13h

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

marsbitHá 13h

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.

marsbitHá 13h

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

marsbitHá 13h

Trading

Spot
Futuros
活动图片

Categorias popularesright-arrow

Etiquetas Popularesright-arrow