The article argues that the Federal Reserve's recent rate hike decision, while justifiable on inflation grounds, highlights a critical lack of an underlying, transparent policy framework. The core problem is that the Fed's decisions appear discretionary, leading to market uncertainty because the committee's judgment, rather than clear data, dictates policy shifts. The author proposes that the Fed adopt a formal monetary policy rule—an algebraic formula linking the target rate to indicators like inflation and unemployment—to replace subjective guidance. Implementing such a rule would provide market predictability, enhance transparency, and shield the Fed from political attacks by making deviations from the standard easily quantifiable.
Anthropic and the Export Control Dilemma
English Summary
The article argues that U.S. export control policy on advanced AI models presents an intractable dilemma, as both over-controlling and under-controlling carry significant risks. Over-controlling threatens to kneecap the domestic high-tech industry by cutting off essential revenue streams, while also encouraging foreign competitors to develop superior alternatives. Conversely, under-controlling allows adversaries to acquire critical technology for military use. The author concludes that relying on regulatory patches or export restrictions is futile; therefore, the only viable long-term strategy for maintaining national security and technological leadership is aggressively accelerating domestic innovation and 'running faster' than global rivals.
中文摘要
本文論述美國對先進人工智慧（AI）模型的出口管制政策存在一個難以解開的困境，因為無論是過度管制還是不足管制都會帶來重大風險。過度管制威脅到會切斷國內高科技產業必要的收入來源，同時也可能鼓勵外國競爭對手開發出更優質的替代方案；反之，不足管制則允許敵方獲取用於軍事用途的關鍵技術。作者總結指出，僅依賴監管修補或出口限制是徒勞無功的；因此，維持國家安全和技術領先地位的唯一可行長期策略，是積極加速國內創新，並超越全球競爭對手。
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