Anthropic 正通过使用多种芯片来处理其 AI 工作以分散风险 —— 这一策略最终可能会削弱 Nvidia 的统治地位。根据 Anthropic 周一发布的 S-1 招股说明书，该 AI 实验室表示，它将算力管理为“来自多个战略合作伙伴的单一、可替代资源池” —— 通过软件根据芯片的最高生产力所在，将工作分配到不同的芯片上。
Anthropic is hedging its bets by using multiple chips to handle its AI work — a strategy that could eventually erode Nvidia's dominance. The AI lab says it manages compute "as a single, fungible pool from multiple strategic partners" — with software that can direct its work to different chips depending on where they're most productive, according to Anthropic's S-1 filing, which came out Monday as the company prepares to go public.
Anthropic 称其使用来自四个芯片家族的硬件：Amazon Trainium、Google TPU、Nvidia GPU 和 AMD GPU。分析师表示，这种灵活性 —— Anthropic 称其“耗时多年并投入巨资构建” —— 可能会使主要 AI 公司逐渐减少对 Nvidia 的依赖，并赋予它们更多谈判筹码。
Anthropic says it uses hardware from four chip families: Amazon Trainium, Google TPUs, Nvidia GPUs, and AMD GPUs. That flexibility, which Anthropic said "took years and significant investment to build," could make major AI companies less dependent on Nvidia over time and give them more negotiating leverage, analysts said.
Moor Insights & Strategy 创始人兼首席执行官 Patrick Moorhead 表示：“真正的风险可能在于 Nvidia 的定价权，因为能够在四个平台间转移工作负载的客户，其谈判方式与无法转移的客户截然不同。”
"The real exposure could be Nvidia's pricing power," said Patrick Moorhead, founder and CEO of Moor Insights & Strategy, "because a customer that can shift work across four platforms negotiates very differently than one that can't."about Anthropic's S-1 filing Ashish Nadkarni, an analyst at IDC, added that a multichip approach also makes Anthropic less vulnerable to fluctuations in Nvidia's chip supply.
IDC 分析师 Ashish Nadkarni 补充称，多芯片策略也使 Anthropic 对 Nvidia 芯片供应的波动不那么脆弱。Moorhead 表示，尽管 Anthropic 的芯片组合并非新事物，但公司现在正将其作为核心优势向投资者推介。
Although Anthropic's chip mix isn't new, the company is now pitching it as a core advantage to investors, Moorhead said.
但这种威胁也有其局限性。Moorhead 表示，在芯片间切换仍然很困难 —— 尤其是在训练 AI 模型（而非运行模型）方面 —— 而且只有最大的 AI 公司才有资源做到这一点。Moorhead 还指出，Anthropic 仍在 Nvidia 算力上投入数十亿美元。
The threat has its limits. Switching between chips is still difficult — especially when it comes to training AI models as opposed to running them, Moorhead said — and only the biggest AI companies have the resources to do it. Anthropic also continues to spend billions on Nvidia compute, Moorhead said.
D.A. Davidson 技术研究主管 Gil Luria 表示，虽然 OpenAI 等其他主要公司很可能也采取多芯片策略，但对于规模较小的参与者来说，这可能不值得付出如此大的努力和投资。
Gil Luria, head of technology research at D.A. Davidson, said that while other major companies like OpenAI likely take a multichip approach, it may not be worth the effort and investment for smaller players.
Circular Technology 全球研究与市场情报主管 Brad Gastwirth 表示，Anthropic 的策略并不构成重大的近期威胁。
Brad Gastwirth, global head of research and market intelligence at Circular Technology, said Anthropic's strategy doesn't represent a major near-term threat.
他说，拥有更多芯片选择并不能抹去英伟达在性能、网络和软件方面的优势。如果AI算力更多地变成一种大宗商品，英伟达将面临更广泛的风险。Citadel首席执行官肯·格里芬曾警告，如果供应超过需求，可能会压低租赁价格。“GPU就像航空公司一样，运行的边际成本非常低，”他上周告诉彭博社。“一旦出现产能过剩，价格就会暴跌。”英伟达未立即回应《商业内幕》的置评请求。
Having more chip options doesn't erase Nvidia's advantages in performance, networking, and software, he said. There's a broader risk for Nvidia if AI compute becomes more of a commodity. Citadel CEO Ken Griffin has warned that if supply overtakes demand, it could drive down rental prices. "GPUs, like airlines, have a very low marginal cost to run," he told Bloomberg last week. "The moment you have overcapacity, pricing goes into freefall." Nvidia did not immediately respond to a request for comment from Business Insider.