If Bitcoin drops below $116,000, the mainstream CEX long liquidation pressure will reach 1.041 billion

According to an official announcement from Bitget, the platform’s stock dual-currency investment product has officially launched, with its first batch covering over 20 popular U.S. stocks and ETF-related underlying assets including rNVDA, rTSLA, rAAPL, and rMETA. This upgrade adjusts the product’s settlement time to 23:30 (UTC+8), aligning more closely with the post-opening trading sessions of U.S. stocks. In addition, Bitget has rolled out two limited-time promotions simultaneously. During the campaign period, new users participating in Bitget’s dual-currency investment for the first time who complete designated tasks such as net deposits will be eligible to receive a dual-currency experience bonus, with a maximum reward of 3,000 USDT. This promotion ends on August 21. Meanwhile, users who purchase dual-currency products during the campaign will also get limited-edition Bitget merchandise including camping sets and commemorative gold coins, with this offer running until August 28. For more details, please visit Bitget’s official website.

According to HTX market data, PUMP has gained 19.65% over the past seven days and 66.57% over the past 30 days, with its market capitalization now standing at $1.665 billion. This morning, the monthly unlock of tokens held by the Pump.fun team and its investors was completed, releasing a total of 4.94 billion PUMP tokens valued at approximately $13.6 million. The unlocked tokens were subsequently distributed to 125 wallet addresses.

Nvidia filed documents with the U.S. Securities and Exchange Commission (SEC) disclosing that as of the end of June this year, the company held approximately 123 million shares of SpaceX, with a book value of nearly $21 billion. According to the filing, due to post-IPO stock fluctuations of SpaceX, the current valuation of Nvidia’s stake is around $170 billion. This disclosure shows that Nvidia has further deepened its capital ties with core clients and AI industry chain enterprises through investment layouts. It is reported that Nvidia completed an investment in Elon Musk’s AI company xAI in January this year; xAI later merged with SpaceX, and this stake is regarded as an important return from that investment. SpaceX CEO Elon Musk previously stated that SpaceX data centers will establish an exclusive partnership with Nvidia, adopting Nvidia’s latest Vera Rubin architecture for AI infrastructure construction. In recent years, Nvidia has continuously increased its investment in the AI industry, pouring more than $100 billion into multiple AI companies and cloud computing startups, including CoreWeave, Thinking Machines, and Safe Superintelligence. In addition, SpaceX plans to significantly expand its computing capacity, and is expected to increase its data center scale to nearly 10GW by the end of 2027, further advancing AI infrastructure construction. The market believes that Nvidia is leveraging its capital advantage as the world’s largest market capitalization company to build an ecosystem covering chips, data centers, and AI applications through investments, supply chain cooperation, and financing support.

Pumpfu(@Pumpfun) unlocked another 4.85B $PUMP($13.6M) to 124 today.

According to monitoring by crypto analytics account Ai Yi, an investor encountered an extreme "paper wealth" scenario after participating in the LAB token public offering. Crypto community user Skylinee joined LAB’s public offering in October 2025, investing $5,000. The token’s value once surged to approximately $5.6 million, marking a 1,120x increase within nine months. However, due to the project team unilaterally delaying the token unlock schedule, the investor only received the tokens recently. Data shows that the current value of his held LAB tokens is just around $3,219, a roughly 99.94% plunge from its previous peak.

Western Digital’s latest analysis notes that as AI applications scale rapidly, AI data center construction is shifting from a pure GPU computing power race to a competition in data storage capacity, with storage planning becoming a core component of AI infrastructure. Citing IDC forecasts, global annual new data volume will reach 718 ZB by 2030. Data generated by AI systems does not disappear once computing tasks end; training data, model checkpoints, embedding vectors, inference logs, prompts, output results, and evaluation data will all accumulate continuously. Western Digital points out that many current AI infrastructure plans overemphasize GPU utilization while neglecting data accumulation throughout the AI lifecycle. Data generated during training and inference will become critical assets for model iteration, quality assessment, and compliance audits, with storage costs directly impacting the long-term operational efficiency of AI systems. As data scales to PB and even EB levels, a single storage architecture can no longer meet demands. Enterprises need to adopt a tiered storage strategy: using high-performance flash memory for training and real-time inference, and high-capacity HDDs and object storage for long-term data archiving, historical records, and low-frequency access scenarios. The analysis concludes that the key metrics for future AI infrastructure competition will not only be the number of GPUs, but also per-PB data storage cost, energy consumption, recovery efficiency, and data lifecycle management capabilities. If enterprises still treat storage as an afterthought to computing, they may face issues such as out-of-control data costs and reduced model iteration efficiency.