🏛️ SEC Delays Plan for Tokenized US Stocks The US Securities and Exchange Commission (SEC) recently announced an indefinite delay to the "US Stock Tokenization Pilot Program," which was originally scheduled to launch in the third quarter of this year. The initiative aimed to allow select blue-chip stocks to be traded as blockchain tokens on regulated platforms, a move widely regarded as a crucial step in bridging traditional finance with the crypto world. In its statement, the SEC explained that the delay stems from a need for further assessment regarding technological maturity, risks of market manipulation, and investor protection mechanisms. The Commission's Chairman emphasized that while blockchain technology holds the potential to revolutionize capital markets, progress must be made steadily under the premise of ensuring market integrity and financial stability. The news has triggered mixed reactions. Supporters argue that the SEC's cautious approach helps avoid repeating the mistakes of incidents like FTX, laying a solid foundation for the industry's healthy development. Critics, however, point out that excessive regulatory hesitation could cause the US to fall behind Europe and Asia in the fintech race. For the crypto market, this postponement means the vision of "compliant tokenized securities" will have to wait in the short term, though it does buy project teams more time to prepare. ⚔️ Anthropic's Compute Arms Race: Securing Microsoft's Chips Competition in the AI sector has reached a fever pitch, with Claude developer Anthropic sparing no expense to expand its computing power reserves. According to insiders, Anthropic has reached a multibillion-dollar strategic partnership with Microsoft. This deal not only grants Anthropic priority access to Azure cloud computing quotas but, more critically, secures exclusive access to the first batch of Microsoft's self-developed AI chips, Maia. This move is seen as a key step for Anthropic to secure its technological lead amidst the "three-way standoff" with OpenAI and Google DeepMind.