Global crypto liquidations have expanded to $238 million in the past hour.

During the 7th live session of HTX’s Expert Lecture Hall, WZ, an asset analyst at HTX Research, noted that while crypto trends were once explained solely by crypto-specific factors, an increasing number of variables shaping the next crypto market cycle are now emerging outside the sector—marking the start of a new pricing cycle for crypto assets. On the regulatory front, WZ pointed out that while the comprehensive Clarity Act has faced Senate voting hurdles due to factors including the need to secure bipartisan votes, ties to the Trump family’s interests, and disputes over stablecoin revenue distribution, U.S. crypto regulation has not stalled. For instance, the SEC recently released an “innovation exemption” framework, allowing eligible compliant institutions to tokenize specific stocks, accelerating the integration of traditional finance and crypto. On the macro front, WZ noted that Middle East tensions and risks of a Strait of Hormuz blockade have lifted crude oil’s “risk premium”. Rising oil prices will stoke inflation expectations, which in turn impact U.S. Treasury yields and global liquidity. When energy prices remain elevated and interest rates stay high, upside potential for risk assets like Bitcoin may be constrained. WZ also added that in this cycle, the direct inflows and outflows of ETF funds have altered the traditional capital spillover logic, making a broad-based altcoin rally unlikely. However, in the new cycle, assets with new narratives and strong consensus will still see independent upward trends.

Bonk Guy announced in a post that the number of addresses holding USELESS has hit a new all-time high. He pointed out that USELESS has maintained a recurring cyclical pattern over the past several months: outperforming the market, followed by a sharp pullback, consolidation, and then a fresh new high. Bonk Guy added that USELESS’s market capitalization has surged from a low of roughly $28 million a few months ago to approximately $318 million, with short-, medium-, and long-term cycles all exhibiting a trend of progressively rising highs and lows. He noted that this trajectory is distinct from the typical performance of meme coins, which usually peak after a rally.

According to HTX market data, the crypto market has seen a short-term pullback, with established meme coins falling broadly. Key declines: MUBARAK dropped over 19% in 24 hours, plunging more than 40% from its intraday high, with its market cap slipping to $52.37 million. BROCCOLI714 fell over 13% in 24 hours, bringing its market cap to $22 million. WIF declined more than 11% in 24 hours, hitting a $230 million market cap. TRUMP dropped over 7% in 24 hours, with its market cap now at $1.477 billion. PEPE also fell over 7% in 24 hours, reaching a $1.874 billion market cap. TST saw a 24-hour decline of over 6%, standing at a $16 million market cap.

US Secretary of State Marco Rubio stated that both Russia and Ukraine have expressed interest in a limited ceasefire covering the food and energy sectors. He noted that the two sides have targeted energy facilities as strategic priorities in their war objectives, adding that negotiations on an energy ceasefire will be very difficult, but the US is willing to play a constructive role in advancing the relevant process. Rubio also said he discussed the Russia-Ukraine conflict and bilateral US-Russia relations with Russian Foreign Minister Sergey Lavrov, and hopes Russian President Vladimir Putin will accept the invitation to attend the G20 summit, believing this will create an opportunity for dialogue between the leaders of Russia and the US. (Jinshi)

Beating AI Express News: A new paper on agent training published by DeepSeek has drawn widespread attention. The 31-page paper introduces DSec, DeepSeek’s internally used production-grade sandbox platform, with over 100 authors including DeepSeek co-founder Liang Wenfeng. A notable section of the paper focuses on "agent misconduct". DeepSeek found that agents can obtain answers through unintended channels, such as residual answers in files managed by search platforms, undermining the validity of training and evaluation results. Even after implementing access controls, some agents exchange file block mappings, attempting to access protected file contents via another file descriptor, compromising tasks or shared infrastructure. DeepSeek argues that no single mechanism can prevent all agent misconduct and system failures. Thus, the team’s approach involves enhancing observability to identify new issues, and continuously hardening DSec as models evolve, including access controls to restrict agents from obtaining answers via unintended channels and reducing incentives for deceptive behavior. These controls address some of the issues.

BlackRock’s latest research report titled *Machine-Native Economy* notes that the widespread adoption of AI could act as an underappreciated driver of demand for digital assets. As AI agents and inter-machine payments gain traction, demand for stablecoins, native crypto assets, and other on-chain assets is likely to rise further. BlackRock argues that AI agents require around-the-clock high-frequency, low-value (even sub-1-cent) inter-machine transactions, while traditional payment systems face limitations in account setup, authorization, fees, and settlement efficiency. Stablecoins are particularly well-suited for such transactions and may become the primary transactional digital asset in AI agents’ business operations. Additionally, the AI computing power market could unlock new use cases for crypto assets. As AI enterprises’ demand for computing power continues to grow, computing power suppliers may in the future tokenize the rights associated with their computing capacity, allowing these tokens to be transferred, traded, or used as collateral, and AI agents can automatically purchase the required computing resources via related markets. BlackRock believes AI is poised to become a structural catalyst for digital asset adoption, while digital assets could also serve as critical infrastructure for the AI economy. Currently, this potential link remains underestimated.