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On June 16, according to monitoring by Lookonchain, Circle has issued an additional 1 billion USDC on the Solana blockchain today, continuing its recent trend of large-scale expansion. Data shows that in the past week, Circle has cumulatively issued a total of 3.5 billion USDC on the Solana chain, equivalent to approximately 3.5 billion USD.

[Circle Issues 1 Billion USDC on Solana Today]On June 16, according to monitoring by Lookonchain, Circle has issued an additional 1 billion USDC on the Solana blockchain today, continuing its recent trend of large-scale expansion. Data shows that in the past week, Circle has cumulatively issued a total of 3.5 billion USDC on the Solana chain, equivalent to approximately 3.5 billion USD.

Circle Issues 1 Billion USDC on Solana Today

According to monitoring by Dongcha Beating, Redis founder Salvatore Sanfilippo has refuted the claim that Chinese large models are strengthened by distilling American models. He believes that ordinary APIs can only return textual answers and cannot capture the probability distributions and internal states when models generate answers, making it impossible to replicate the core capabilities of a cutting-edge model through a few external calls. The true logical reasoning and thinking abilities of large models are hidden within extremely complex neural networks. Through API interfaces, external users can only obtain the final textual answers but cannot access the complete thought process and probability calculations behind the model's answer generation. This is akin to only seeing a few answers on a final exam, which cannot reveal the vast knowledge system in the teacher's mind. Chinese large models, represented by DeepSeek, are rising based on solid foundations of data pre-training and reinforcement learning, rather than taking shortcuts. The academic community has subdivided large model distillation into 'soft distillation', which relies on probability distributions, and 'hard distillation', which relies solely on textual answers. Soft distillation is a conventional post-training method and cannot be easily achieved through API calls; current debates mainly focus on 'hard distillation'. Major companies are primarily concerned with avoiding API abuse that circumvents service terms, where competitors use jailbreaking and prompting to force models to output derivations, validation steps, and self-correction processes that are typically hidden in products. Although these detailed step data are still in textual form and do not represent the underlying probability distributions of the model, they can significantly help competitors save hundreds of millions of dollars in blind exploration costs during reinforcement learning. Major companies find it difficult to completely block jailbreaking, as outputting detailed derivation processes is a core attribute that maintains the high intelligence of reasoning models. If they forcibly shield this to prevent theft, the model's performance will severely decline. Major companies are eager to define service breaches and API abuse as security-related 'attacks', driven by the legal void surrounding copyright. Under the current legal framework, AI-generated text does not enjoy copyright, and major companies cannot prevent competitors from reasonably using this generated text as data. This copyright void leads to a significant flaw for frontrunners, who face the dilemma of 'bearing high costs for reinforcement learning exploration while being unable to prevent competitors from legally utilizing data to catch up'. Therefore, major companies tend to package competitive behavior as 'distillation attacks' in public relations and policy, seeking moral sympathy and legislative protection in an attempt to maintain their first-mover advantage.

[Redis Founder Refutes Claims of Chinese Models Strengthened by Distilling American Models]According to monitoring by Dongcha Beating, Redis founder Salvatore Sanfilippo has refuted the claim that Chinese large models are strengthened by distilling American models. He believes that ordinary APIs can only return textual answers and cannot capture the probability distributions and internal states when models generate answers, making it impossible to replicate the core capabilities of a cutting-edge model through a few external calls. The true logical reasoning and thinking abilities of large models are hidden within extremely complex neural networks. Through API interfaces, external users can only obtain the final textual answers but cannot access the complete thought process and probability calculations behind the model's answer generation. This is akin to only seeing a few answers on a final exam, which cannot reveal the vast knowledge system in the teacher's mind. Chinese large models, represented by DeepSeek, are rising based on solid foundations of data pre-training and reinforcement learning, rather than taking shortcuts. The academic community has subdivided large model distillation into 'soft distillation', which relies on probability distributions, and 'hard distillation', which relies solely on textual answers. Soft distillation is a conventional post-training method and cannot be easily achieved through API calls; current debates mainly focus on 'hard distillation'. Major companies are primarily concerned with avoiding API abuse that circumvents service terms, where competitors use jailbreaking and prompting to force models to output derivations, validation steps, and self-correction processes that are typically hidden in products. Although these detailed step data are still in textual form and do not represent the underlying probability distributions of the model, they can significantly help competitors save hundreds of millions of dollars in blind exploration costs during reinforcement learning. Major companies find it difficult to completely block jailbreaking, as outputting detailed derivation processes is a core attribute that maintains the high intelligence of reasoning models. If they forcibly shield this to prevent theft, the model's performance will severely decline. Major companies are eager to define service breaches and API abuse as security-related 'attacks', driven by the legal void surrounding copyright. Under the current legal framework, AI-generated text does not enjoy copyright, and major companies cannot prevent competitors from reasonably using this generated text as data. This copyright void leads to a significant flaw for frontrunners, who face the dilemma of 'bearing high costs for reinforcement learning exploration while being unable to prevent competitors from legally utilizing data to catch up'. Therefore, major companies tend to package competitive behavior as 'distillation attacks' in public relations and policy, seeking moral sympathy and legislative protection in an attempt to maintain their first-mover advantage.

Redis Founder Refutes Claims of Chinese Models Strengthened by Distilling American Models

Market data shows that ETH has surpassed $1800, currently priced at $1801.73, with a 24-hour increase of 4.78%. Due to significant market fluctuations, please ensure proper risk management.

[ETH Surpasses $1800]Market data shows that ETH has surpassed $1800, currently priced at $1801.73, with a 24-hour increase of 4.78%. Due to significant market fluctuations, please ensure proper risk management.

ETH Surpasses $1800

On June 16, the DeFi protocol Pyra announced on platform X that it will cease operations and gradually shut down. The platform stated that its business and users have been severely impacted by the Drift security incident. Despite attempts over the past few months to find a sustainable path forward, they have been unsuccessful. Currently, all user balances are still withdrawable, but new user registrations have been halted, and existing Pyra cards have been canceled. Pyra will launch a web portal in the coming weeks for existing users to manage positions and withdraw funds, while the mobile application will be shut down. Once Drift resumes token listings, Pyra will distribute to affected users through the web portal. Pyra advises users to withdraw funds and export account private keys as soon as possible; this functionality will remain available until September 15, 2026.

[DeFi Protocol Pyra to Cease Operations Due to Drift Security Incident]On June 16, the DeFi protocol Pyra announced on platform X that it will cease operations and gradually shut down. The platform stated that its business and users have been severely impacted by the Drift security incident. Despite attempts over the past few months to find a sustainable path forward, they have been unsuccessful. Currently, all user balances are still withdrawable, but new user registrations have been halted, and existing Pyra cards have been canceled. Pyra will launch a web portal in the coming weeks for existing users to manage positions and withdraw funds, while the mobile application will be shut down. Once Drift resumes token listings, Pyra will distribute to affected users through the web portal. Pyra advises users to withdraw funds and export account private keys as soon as possible; this functionality will remain available until September 15, 2026.

DeFi Protocol Pyra to Cease Operations Due to Drift Security Incident

On June 16, despite months of conflict following military strikes by the U.S. and Israel against Iran, and heightened tensions in the Strait of Hormuz impacting the global energy market, Iran's oil export revenues did not contract as significantly as expected. In fact, there were periods of revenue growth. Reports citing data from the oil and gas industry indicate that during most of the conflict, Iran's daily oil export revenues even exceeded levels prior to the outbreak of hostilities, undermining external assessments that its economy was being 'rapidly cut off.' The U.S. government had previously estimated that sanctions and military pressure would quickly compress Iran's financial capacity and weaken its ability to sustain its military and energy systems. However, the actual situation shows that despite facing sanctions and geopolitical conflicts, Iran has maintained a certain level of crude oil exports through its existing export networks, allowing its energy revenue chain to remain resilient during the conflict. This outcome has led to a reassessment of the effectiveness of sanctions and the stability of energy supplies in the Middle East. Analysts point out that the sustainability of energy exports means that Iran still possesses a degree of economic support in subsequent diplomatic and ceasefire negotiations, and its leverage in regional power dynamics has not been completely diminished.

[Iran's Oil Exports Remain Resilient Amid Conflict, Strengthening Negotiation Leverage]On June 16, despite months of conflict following military strikes by the U.S. and Israel against Iran, and heightened tensions in the Strait of Hormuz impacting the global energy market, Iran's oil export revenues did not contract as significantly as expected. In fact, there were periods of revenue growth. Reports citing data from the oil and gas industry indicate that during most of the conflict, Iran's daily oil export revenues even exceeded levels prior to the outbreak of hostilities, undermining external assessments that its economy was being 'rapidly cut off.' The U.S. government had previously estimated that sanctions and military pressure would quickly compress Iran's financial capacity and weaken its ability to sustain its military and energy systems. However, the actual situation shows that despite facing sanctions and geopolitical conflicts, Iran has maintained a certain level of crude oil exports through its existing export networks, allowing its energy revenue chain to remain resilient during the conflict. This outcome has led to a reassessment of the effectiveness of sanctions and the stability of energy supplies in the Middle East. Analysts point out that the sustainability of energy exports means that Iran still possesses a degree of economic support in subsequent diplomatic and ceasefire negotiations, and its leverage in regional power dynamics has not been completely diminished.

Iran's Oil Exports Remain Resilient Amid Conflict, Strengthening Negotiation Leverage

On June 16, Federal Reserve Chair Walsh expressed a preference for an alternative inflation measure—namely, the 'trimmed mean PCE inflation,' which excludes extreme values before calculating the weighted average. Brian Bethune, an economics professor at Boston College, stated that the trimmed mean PCE is currently not the most reliable indicator. In short, this measure works best when inflation shocks resemble those from the period of 2009-2019 (prior to the COVID-19 pandemic crisis), as there was a better balance between positive and negative shocks during that time. However, when price shocks primarily stem from positive factors—such as supply shocks, tariffs, surging oil prices, or significant special sporting events (like the World Cup)—this measure tends to underestimate inflation. 'Therefore, I hope someone will challenge him on this,' Bethune said. Regardless of which measure is referenced, U.S. inflation remains above the Federal Reserve's 2% target, a situation that has persisted since spring 2021. (Jinshi)

[Economist: Walsh's Preferred Alternative Inflation Measure is 'Unreliable', Hopes for Challenges]On June 16, Federal Reserve Chair Walsh expressed a preference for an alternative inflation measure—namely, the 'trimmed mean PCE inflation,' which excludes extreme values before calculating the weighted average. Brian Bethune, an economics professor at Boston College, stated that the trimmed mean PCE is currently not the most reliable indicator. In short, this measure works best when inflation shocks resemble those from the period of 2009-2019 (prior to the COVID-19 pandemic crisis), as there was a better balance between positive and negative shocks during that time. However, when price shocks primarily stem from positive factors—such as supply shocks, tariffs, surging oil prices, or significant special sporting events (like the World Cup)—this measure tends to underestimate inflation. 'Therefore, I hope someone will challenge him on this,' Bethune said. Regardless of which measure is referenced, U.S. inflation remains above the Federal Reserve's 2% target, a situation that has persisted since spring 2021. (Jinshi)

Economist: Walsh's Preferred Alternative Inflation Measure is 'Unreliable', Hopes for Challenges

On June 16, the cryptocurrency payment project Pyra announced that it will officially cease operations and enter the liquidation process, stating that after evaluating all feasible paths, it ultimately failed to find a sustainable business recovery plan. The project team indicated that the closure is primarily due to the severe impact of the previous Drift-related security vulnerability incident on the business and user assets. Over the past few months, the team attempted various reconstruction and financing solutions, but none resolved the ongoing operational issues. According to the announcement, user assets can still be withdrawn normally, new user registrations have been closed, and all Pyra card services have been canceled. In the coming weeks, the company will gradually shut down the mobile application and launch a web portal for users to manage their open positions and complete fund withdrawal operations. Pyra also stated that after the official distribution of Drift recovery tokens, it will distribute them to affected users through its web portal, but the specific timing still needs further confirmation from the Drift team. The company advises users to withdraw their funds and export their account private keys as soon as possible, and stated that the relevant withdrawal functions will remain available at least until September 15, 2026, to allow users to complete asset migration and liquidation operations. The official emphasized that basic support services will be maintained during the transition period to assist users in handling their accounts.

[Cryptocurrency Payment Project Pyra Ceases Operations Due to Drift Vulnerability Impact]On June 16, the cryptocurrency payment project Pyra announced that it will officially cease operations and enter the liquidation process, stating that after evaluating all feasible paths, it ultimately failed to find a sustainable business recovery plan. The project team indicated that the closure is primarily due to the severe impact of the previous Drift-related security vulnerability incident on the business and user assets. Over the past few months, the team attempted various reconstruction and financing solutions, but none resolved the ongoing operational issues. According to the announcement, user assets can still be withdrawn normally, new user registrations have been closed, and all Pyra card services have been canceled. In the coming weeks, the company will gradually shut down the mobile application and launch a web portal for users to manage their open positions and complete fund withdrawal operations. Pyra also stated that after the official distribution of Drift recovery tokens, it will distribute them to affected users through its web portal, but the specific timing still needs further confirmation from the Drift team. The company advises users to withdraw their funds and export their account private keys as soon as possible, and stated that the relevant withdrawal functions will remain available at least until September 15, 2026, to allow users to complete asset migration and liquidation operations. The official emphasized that basic support services will be maintained during the transition period to assist users in handling their accounts.

Cryptocurrency Payment Project Pyra Ceases Operations Due to Drift Vulnerability Impact

On June 16, French Bitcoin treasury company Capital B is developing a digital credit tool aimed at the European market, structurally referencing the STRC and related products launched by Strategy. Company director Alexandre Laizet stated at the BTC Prague conference that the product will be based on a Bitcoin balance sheet, aiming to provide a 'digital credit tool' under the high tax and regulatory environment in Europe, offering new yield-generating structured products to the market. According to the introduction, the tool is expected to achieve double-digit returns by combining Bitcoin treasury assets while striving to keep volatility in a low range, and enhance capital efficiency through debt and yield mechanism design. He pointed out that Bitcoin, as the underlying asset, has the ability to support long-term yield distribution due to its long-term appreciation trend, illustrating the fund circulation mechanism with Strategy's recent example of paying dividends through the sale of a small amount of BTC and then repurchasing. Laizet emphasized that while such digital credit tools carry potential risks, including Bitcoin price volatility and custody and counterparty risks, he believes the long-term probability of Bitcoin going to zero is extremely low, and stated that the company will rely on a regulated banking system and a professional capital market team to advance the product design. Public information shows that Capital B is currently listed on Euronext Growth Paris, holding approximately 3,139 BTC, with a long-term goal of holding 15,000 BTC by the end of 2027 and accumulating 1% of the global Bitcoin supply by 2033. The company also noted that market interest in digital credit products has increased about tenfold compared to last year, indicating rising institutional demand.

[Capital B Plans to Launch STRC-like Digital Credit Tool Targeting European Market]On June 16, French Bitcoin treasury company Capital B is developing a digital credit tool aimed at the European market, structurally referencing the STRC and related products launched by Strategy. Company director Alexandre Laizet stated at the BTC Prague conference that the product will be based on a Bitcoin balance sheet, aiming to provide a 'digital credit tool' under the high tax and regulatory environment in Europe, offering new yield-generating structured products to the market. According to the introduction, the tool is expected to achieve double-digit returns by combining Bitcoin treasury assets while striving to keep volatility in a low range, and enhance capital efficiency through debt and yield mechanism design. He pointed out that Bitcoin, as the underlying asset, has the ability to support long-term yield distribution due to its long-term appreciation trend, illustrating the fund circulation mechanism with Strategy's recent example of paying dividends through the sale of a small amount of BTC and then repurchasing. Laizet emphasized that while such digital credit tools carry potential risks, including Bitcoin price volatility and custody and counterparty risks, he believes the long-term probability of Bitcoin going to zero is extremely low, and stated that the company will rely on a regulated banking system and a professional capital market team to advance the product design. Public information shows that Capital B is currently listed on Euronext Growth Paris, holding approximately 3,139 BTC, with a long-term goal of holding 15,000 BTC by the end of 2027 and accumulating 1% of the global Bitcoin supply by 2033. The company also noted that market interest in digital credit products has increased about tenfold compared to last year, indicating rising institutional demand.

Capital B Plans to Launch STRC-like Digital Credit Tool Targeting European Market

HTX data monitoring shows that BTC has surpassed 67,000 USDT, currently reported at 67,003.18 USDT, with a 24H increase of 2.01%.

【BTC breaks through 67000 USDT】HTX data monitoring shows that BTC has surpassed 67,000 USDT, currently reported at 67,003.18 USDT, with a 24H increase of 2.01%.

BTC breaks through 67000 USDT

On June 15, green energy infrastructure startup TAR announced the completion of $27 million in seed funding to develop modular 'plug-and-play' power systems for data centers, aimed at addressing the power and deployment bottlenecks faced by data centers in the AI era. Reports indicate that the solution combines solar energy, wind energy, battery storage, and natural gas backup units to achieve near-continuous (24/7) local power supply capability, reducing reliance on the public grid and circumventing issues such as grid access queuing, approval delays, and fluctuations in electricity prices. The co-founder of TAR stated that the core idea is to significantly shorten the deployment cycle of energy systems through factory prefabrication, pre-assembly, and pre-testing, enabling 'rapid deployment' capabilities for data centers. In pilot projects, the system can provide approximately 10MW of stable power and plans to deploy over 200MW of regular load capacity by 2027. The company noted that its first customer is an undisclosed 'neocloud' service provider, aiming to provide a faster energy deployment path for AI computing infrastructure. In terms of its economic model, TAR stated that its solution does not aim to be cheaper than traditional grid costs but prioritizes solving the 'speed issue.' Its off-grid energy system can be deployed in about three months, avoiding the time costs associated with grid access and land restrictions. As the demand for AI computing power continues to grow, power supply has been identified by several studies as one of the main bottlenecks for data center expansion. Industry analysis suggests that this 'off-grid energy + modular data center' model is becoming a new direction in the competition for AI infrastructure.

[Energy Company TAR Completes $27 Million Seed Funding to Address Power Issues for Data Centers in the AI Era]On June 15, green energy infrastructure startup TAR announced the completion of $27 million in seed funding to develop modular 'plug-and-play' power systems for data centers, aimed at addressing the power and deployment bottlenecks faced by data centers in the AI era. Reports indicate that the solution combines solar energy, wind energy, battery storage, and natural gas backup units to achieve near-continuous (24/7) local power supply capability, reducing reliance on the public grid and circumventing issues such as grid access queuing, approval delays, and fluctuations in electricity prices. The co-founder of TAR stated that the core idea is to significantly shorten the deployment cycle of energy systems through factory prefabrication, pre-assembly, and pre-testing, enabling 'rapid deployment' capabilities for data centers. In pilot projects, the system can provide approximately 10MW of stable power and plans to deploy over 200MW of regular load capacity by 2027. The company noted that its first customer is an undisclosed 'neocloud' service provider, aiming to provide a faster energy deployment path for AI computing infrastructure. In terms of its economic model, TAR stated that its solution does not aim to be cheaper than traditional grid costs but prioritizes solving the 'speed issue.' Its off-grid energy system can be deployed in about three months, avoiding the time costs associated with grid access and land restrictions. As the demand for AI computing power continues to grow, power supply has been identified by several studies as one of the main bottlenecks for data center expansion. Industry analysis suggests that this 'off-grid energy + modular data center' model is becoming a new direction in the competition for AI infrastructure.

Energy Company TAR Completes $27 Million Seed Funding to Address Power Issues for Data Centers in the AI Era

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Article

Trump: Strait of Hormuz Fully Opened on Friday, Agreements Signed

Energy Company TAR Completes $27 Million Seed Funding to Address Power Issues for Data Centers in the AI Era

Disclaimer：Il contenuto di cui sopra non rappresenta le posizioni di HTX.，HTX non fornisce alcuna raccomandazione di trading.。

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